Artificial Lighting Design for Primary Learning Environments

Artificial Lighting Design for Primary Learning Environments A study on the effect of non-uniform distribution of artificial light on pupil behaviour during class

Imke Wies van Mil

Colophon

A study on the effect of non-uniform distribution of artificial light on pupil behaviour during class

PhD Dissertation © The Royal Danish Academy – Architecture, Design, Conservation © Henning Larsen © Imke Wies van Mil Supervisor: Olga Popovic Larsen Co-supervisors: Karina Mose and Signe Kongebro Printing and binding: PrinfoDenmark A/S Publisher: The Royal Danish Academy – Architecture, Design, Conservation Published: 2020

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This research concerns an industrial PhD project, meaning the research is embedded in practice and has been carried out by the researcher (the author of this thesis) in collaboration with a commercial partner, architecture practice Henning Larsen, and an academic partner, the Royal Danish Academy - Architecture, Design, Conservation. The project has been financially supported by Innovation Fund Denmark (innovationsfonden *).

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FOREWORD

Key Partners

•

Architecture practice Henning Larsen was keen on exploring how they, as shapers of built environment, can address the design and application of artificial light in their work processes more consciously to eventually provide occupants with better supportive (learning) environments.

•

The Royal Danish Academy wanted to contribute new knowledge to the field of architectural research, and the subfield of architectural lighting in particular, as well as teaching with a stronger anthropological undertone so that people take the centre stage in architectural education and design.

•

The researcher’s own ambition with the research was to raise awareness within the built environment community that artificial lighting can contribute beyond making “things” visible or attractive, and can play an active role in improving people’s performance, health and well-being. See below.

Personal Motivation Before commencing as well as during this research, I have been acting as a professional architectural lighting designer. During these years of active engagement in a broad range of architectural projects, I observed that daylight generally receives substantial attention throughout the design process, and particularly during the early stages thereof. Artificial lighting however is given much less consideration, and most often only in a relatively late stage of this process. The responsibility for the design and integration of artificial lighting (systems) in the built environment traditionally lies with the electrical engineers in dialogue with the building’s * https://innovationsfonden.dk/en/programmes/industrial-researcher/industrialphd-all-areas-private-sector-0

Foreword

The shared interest of the partnership at the commencement of the project was to explore how artificial lighting can act as a meaningful instrument to design and create contemporary educational environments for young pupils to thrive, learn and grow in. Yet each partner contributed a unique motivation for the research:

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architect. Often their joint stance is that artificial light is required to supplement when and where natural is lacking to ensure occupants can visually perceive their surroundings well to safely move around, and to perform their activities (visually) comfortably. In the bestcase scenario the design team also strives for a visually pleasant integration, often by choosing aesthetically attractive luminaires that are aligned well within the architectural framework.

Foreword

But considering that most of our regularly occupied building stock, including our learning environments, tend to also be used during poorly or non-existent daylit hours, we are significantly dependant on artificial lighting to set the right visual conditions. It would therefore be arguably imperative to give artificial light more attention and priority during the design process. In addition, a range of recent technological advancements in light sources, materials and control systems has opened up for new prospects. Exploring these whilst aware of the (growing body of) knowledge about how artificial lighting impacts building occupants, allows for a broader palette of artificial light use and applications to be developed. I therefore believe the conventional attitude towards artificial lighting and the role it commonly serves in the architectural industry should change. Artificial lighting needs to be recognized for having a significant influence on occupants’ daily lives indoors. Its impact should be considered beyond pleasing the eye and regarded an active environmental parameter co-shaping occupant behaviour, performance and well-being inside the built environment. My personal goal is therefore raising awareness for and pushing the topic of artificial lighting higher up the architectural agenda. In addition, I recognized that getting more out of artificial lighting to serve occupants visual needs as we currently provide is not solely reliant on increasing awareness within the built environment community, it also requires challenging the current building regulations and recommendations for illuminating (educational) environments. These regulations predominantly originate from the time that ensuring for visual clarity was key, as paper-based materials and chalkboards were the main educational tools and teacher-orientated learning the prevailing pedagogical method. Today this has significantly changed. In Denmark, but also worldwide similar trends are occurring where (digital) screens as tools, and active, diversified and collaborative learning styles are becoming dominant. These substantial changes now question what the purpose of general lighting of learning spaces is, or may need to be. Arguably this should not revolve (anymore) around guaranteeing occupant’s visual performance to do (paper- based) tasks, but to be redefined to service our visual experience holistically and align this experience with the learning activity at hand. This research seeks to contribute to raise awareness of the value and significance of artificial lighting, and by providing evidence that our current building regulations should be reassessed.

To create a safe and non-obtrusive test environment, certified lighting equipment robust enough to withstand the challenges of typical primary educational environments, for example to withstand reasonable impact and minor acts of vandalism, had to be secured. Fagerhult A/S, a well-recognized Scandinavia-based lighting manufacturing company was found willing to sponsor and provide twenty-four professional luminaires, including necessary control devices and electrical connectors, as well as the shipping thereof to the school’s site. In return, Fagerhult A/S became a (passive) research partner and has been referenced in all dissemination activities about this research. It was also necessary for this new lighting equipment to be installed (and removed) safely and securely in the learning spaces appointed to host the experiment. Hereto the services of professional electrical installer ELTeam Vest were procured, who also had been responsible for installing all the existing electrical lighting throughout the newly built school, which was inaugurated in 2016. Their knowledge of these existing installations proved highly valuable to realize successful implementation of the experimental lighting system, and herewith operation of the experiment itself. To fund ELTeam Vest’s services, additional financial support was sought with and granted by Elforsk, Denmark’s Energy Research and Development program. In return, Elforsk requested to include an energy-monitoring study into the project. The rationale being that the research needed to explore how the energy consumption of the learning spaces overall would be affected by the introduction and use of the experimental lighting installation. Hereto the energy consumption of the learning spaces hosting the experiment has been monitored and compared throughout the experiment. In order to document and disseminate these findings, the researcher was required to submit a technical report documenting the entire research (including the energy study) in a format that could be freely shared with their audience. This report has been published in 2018 on the funding bodies’ website *. * https://elforsk.dk/sites/elforsk.dk/files/media/dokumenter/2018-11/349_062_ slutrapport.pdf

Foreword

This research is centred around an experimental field study that was setup and performed in a real-life primary school in Denmark. The study explored the implications of different artificial lighting conditions in the learning space on pupil’s behaviour and learning performance. The experiment took place during normal school hours and curricular activities and included real pupils and teachers. To ensure the experiment would not compromise the educational program nor pupil’s and teacher’s health and safety, an authorised experimental lighting installation had to be implemented in the learning spaces hosting the field experiment. In order to achieve that, professional support was sought from two external parties: Fagerhult A/S and ELTeam Vest.

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Professional Support

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Most of this report (circa 75%) has been contributed and written by the author of this thesis. However, some sections include content contributed by the two external research collaborators, who are further detailed below. Some sections in this thesis will therefore bear resemblance to sections in this technical report. When such overlap appears, this is clearly stated in this thesis, and references are made to third party’s contributions.

Academic Collaborations To support some of the data gathering during the experimental field study and the interpretation thereof, two external academic expert groups have been consulted. The Indoor Climate and Energy Unit of Aarhus University (AU) was consulted about the monitoring of the indoor climate in the learning spaces hosting the experiment, and the measuring of pupil’s learning performance. Their time, the use of their measurement equipment and unique pupil performance tests, as well as their support in analysing the subsequently collected data sets was funded by the beforementioned Elforsk grant.

Foreword

A second partnership was set up with the Architectural Acoustics group at the Technical University of Denmark (DTU). This collaboration allowed to collect and analyse detailed sound data in the learning spaces hosting the field explement. Separate funding was sought and granted by Dansk Lyd (Danish Sound *) for one student worker to assist with setting up the audio recorders correctly, translating the collected rudimentary data into audible decibel files, and in collaboration with the researcher, interpret this data. Contributions made by either of these two collaborators are clearly stated throughout this thesis.

Acknowledgements Many others than beforementioned have supported this research, which took place between 2015 and 2020, and herewith I have many to thank personally. Foremost I would like to acknowledge my two key partners in this research, Henning Larsen and the Royal Danish Academy – Architecture, Design, Conservation, whom without this research would not have come into being. Herewith I would like to thank Signe Kongebro, Jakob StrømannAndersen and Anne Gade Iversen of Henning Larsen for providing me the opportunity to undertake this research from within their working environment, for me to partake in and be inspired by architectural projects ongoing in the office and granting me access to various of their resources and contacts. I specifically would like to thank Margrete Grøn, the architect at Henning Larsen who was heavily involved in the design and building of Frederiksbjerg School. Margrethe assisted me greatly by setting up contacts with * https://ufm.dk/forskning-og-innovation/forsk2025/indkomne-indspil/netvaerk/ innovationsnetvaerket-dansk-lyd

I am most grateful for Frederiksbjerg School’s willingness to host the experiment. Most notably, school leader Jette Bjørn Hansen for providing me access into the school, allowing me to intervene in four of the school’s learning spaces, connecting me with the school’s administration to attain consent from parents, pupils and teachers, and to collaborate with the school’s maintenance team on installing and maintaining the experimental lighting setup. I am also most thankful for the collaborations with six fantastic teachers, Kristian, Ulla, Trine, Mathias, Thomas, and Heidi, who not only allowed me into their classes as an observer, but also shared highly valuable insights and perspectives with me during our interviews. Without their willingness and openness, I would not have been able to learn as much as I did. And off course, I’d like to thank all lovely pupils (and their parents) who accepted me into their learning spaces, even though my Danish wasn’t highly developed. I would like to thank all other collaborators and funding supporters of this research. In non-hierarchical order: Werner Osterhaus, Steffen Petersen, Maria Garcia Alvarez and Sophie Stoffer of Aarhus University; Cheol-Ho Jeong, Baltazar Brière and Finnur Pind of DTU; Henrik Clausen of Fagerhult A/S; Henrik Møller and his team of ELTeam Vest; and Innovationsfonden, Elforsk and Dansk Lyd for their financial support of the research. And last – but so much not least, my dearest family and friends, who stood by and supported me during these intense though fruitful years of practice-based researching. My husband, Hugo Mulder, who truly without I could not have done this. The endless hours we spend together discussing the project and managing my travels, while growing our family with two beautiful children along the way. Hugo, Nova and Otto – I love you dearly and I very much look forward to less evenings spend typing away. To all my other family and close friends, I thank you for listening to my highs and enduring my lows. I thank you all. X

Foreword

I am very thankful for the guidance and continuous support by both my supervisors from the Royal Danish Academy - Architecture, Design, Olga Popovic Larsen and Karina Mose. They allowed me to follow my interests, supported my choice to research by means of field experimentation – which required to setup and deal with a significant number of collaborations as well as perseverance – while probing my approach along the way with insightful questions. I am particularly grateful for their patience for the last year of the research, during which this thesis has been formed. Their feedback and suggestions were invariably insightful and encouraging in order to arrive at the thesis document as presented now here.

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the school and stirring up interest to host the field experiment. I also like to thank all other colleagues at Henning Larsen who took the time to discuss the research with me and share their perspectives, or simply welcomed me as part of the team.

ABSTRACT p. 8

The author of this PhD is an educated, professional architectural lighting designer with an interest to investigate how artificial lighting could be applied in contemporary educational environments to benefit pupils learning. The project concerns an industrial PhD and has been conducted in collaboration with architectural practice Henning Larsen and the Royal Danish Academy - Architecture, Design, Conservation.

Abstract

The context of the research is Denmark’s system for primary and lower secondary education, or Folkeskole, which underwent a significant pedagogical reform in 2014. The reform amongst others called for improved conditions for undisturbed learning. Those conditions were found most pertinent during so called focussedlearning activities such as mathematics and reading practice, during which pupils need to concentrate on a task that requires their sustained attention. Research found that disturbances during class are predominantly caused by pupils themselves, and a typical manifestation thereof is noise. Fields studies in three contemporary school buildings, undertaken in the first phase of this project, evidenced the common approach by school designers thus far is to mitigate the impact of noise, for example by applying sound absorbing materials. However, an arguably more effective approach could be to prevent (noise) disturbances caused by pupils from occurring. Typically, disruptive behaviour is addressed by teachers through various management techniques which predominantly rely on interaction between teachers and pupils. But the physical learning environment itself may also yield potential as research evidenced various environmental features, including the indoor climate variables light, sound, temperature and air quality, have the capacity to influence occupant behaviour. This knowledge provides prospects for school designers looking to address the need to improve the environmental conditions for undisturbed learning. This research investigates the potential of one particular environmental feature, namely that of the artificial lighting, to address the issue of disruptive pupil behaviour. Research from amongst others the fields of lighting science and environmental psychology established that artificial light has an impact beyond making things visible in the learning space. Artificial light has for example also been found to bring about change in pupil’s mood, motivation, and social interactions, which in turn have been found to affect pupil’s behaviour and learning performance. This research seeks to explore if and how artificial lighting could be specifically utilized to decrease disturbances created by pupils during focussedlearning activities, and herewith improve the conditions for the pupils to concentrate on their educational task and ultimately, better their learning performance.

In order to gather evidence for this position, a field experiment was developed that assessed the implications of two different artificial lighting conditions on the behaviour and learning performance of circa 200 pupils aged between six and twelve years old. Hereto an experimental lighting intervention was designed and implemented in four learning spaces of the newly built Frederiksbjerg school in Aarhus (DK). The electrical lighting system installed allowed to exposure pupils (and their teachers) to two significantly different artificial lighting conditions: (A) the standard uniform light condition typically found in today’s primary learning spaces, and (B) a specifically designed non-uniform pools-of-light condition. The uniform condition typically refers to a relatively equal distribution of light across a space, while a non-uniform light conditions refers to non-equal distribution of light, and typically features brighter and darker areas across the space. In order to avoid compromising pupils’ learning and teaching processes, the setup of the lighting installation was non-prescriptive and allowed teachers (and pupils) to select a light condition considered most suitable for their activity at any moment in time. The experiment took place during several continuous weeks in the Spring and Autumn semester of 2017, and followed a crossover research design that allowed to expose the pupils partaking in the experiment to both artificial light conditions whilst continuing their normal curricular routines and activities. During these exposures, change in pupils’ behaviour and learning performance was assessed by monitoring three associated variables: noise levels during class, three typical observable disruptive behaviours, and pupils’ cognitive performance. To lower the risk of data contamination, fourteen additional environmental conditions were monitored or measured too. Analysis of the different data sets suggests that the use of the experimental lighting installation, and the pools-of-light condition in particular, led to improved conditions for pupil’s learning. Less occurrences of disruptions caused by pupils (which divert pupils’ attention away from their learning task) were observed during focussed-learning activities when the pools-of-light condition was activated, and pupil’s performance on a focussed learning task modestly improved. This outcome implies that a lighting design that allows for variation in the artificial light condition in the learning space, benefits learning outcomes. This finding is further supported by the decision of Frederiksbjerg school to make the temporary lighting intervention permanent, and to install similar interventions in other learning spaces too.

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Field Experiment

LIST OF PUBLICATIONS p. 10

This thesis provides for a complete overview of the research undertaken with the aim to contribute to fulfil the requirements to be granted a PhD degree. Some of the writing has been published or otherwise disseminated throughout the process of conducting this research. Parts of the writings in this thesis can therefore be found in other articles and/or reports already put out in the world. Unless otherwise stated, these occurrences concern writings done by the author herself. When writings of others are used in this thesis, appropriate references are made. The most notable publication referenced is the Elforsk report, and these occur predominantly in Chapter 3. As this report includes contributions by others, when those are included into this thesis, it is stated clearly and referenced appropriately. The full list of publications is as following: Van Mil, I.W., Iversen, A. & Strømann-Andersen, J. (2016). Bright Ideas. College – Planning & Management, 19(3), 43 – 45.

List of Publications

Van Mil, I.W., Popovic Larsen, O., Mose, K., & Iversen, A. (2017). Design with knowledge – Light in learning environments. Symposium Proceedings. Transitions Europe – Inhabiting innovative learning environments, (1), 99 – 106. (*) Van Mil, I.W., Popovic Larsen, O., & Mose, K. (2017). How to illuminate learning environments well? A lighting designers’ perspective. Scandinavian Journal of Optometry and Visual Science, 10(2), 3. (*) Van Mil, I.W. (2018). Design with knowledge – light in learning environments. Conference Proceedings. Professional Lighting Design Conference, (8), 21 – 23. (*) Grønkjær, L., van Mil, I.W. (2017). Nye lamper i klassen sænker støjen markant. Newspaper: Politiken, Special edition: Skoleliv. van Mil, I.W., Brière, B., Jeong, C., Popovic Larsen, O., Iversen, A., & Pind, F. (2018). Noise measurements during focus-based classroom activities as an indication of student’s learning with ambient and focused artificial light distribution. Conference Proceedings. European Congress + Exposition on Noise Control Engineering, (11), 1767 – 1772. (*) Van Mil, I.W. (2018). How Light Can Be an Aid to Learning – a Study of Artificial Lighting in the Classroom. DETAIL – Review of Architecture + Construction Details. School Edition, (9), 86 – 87.

Van Mil, I. W., Iversen, A., Osterhaus, W., Garcia Alvarez, M., Petersen, S., & Jeong, C-H. (2018). Light at eye level is a means to create energy savings and space for learning, focus and concentration. Research Report for the Danish Electricity Research Fund (Elforsk).

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Bay, A. (2018). Lys i øjenhojde skaber ro og koncentration. Lys Design Bogen, 12 –13. Dansk Center for Lys.

Van Mil, I.W. (2020). Artificial Lighting in Schools. In Hofmeister, S (Ed.), School Buildings – Special Edition, (1), 26 – 31. Munich, DE: Detail Business Information GmbH. (*)

A selection of full-length articles, which are marked with an (*) in the beforementioned publication list, can be found om Appendix X. All images, photos, drawings and other visual material incorporated in both the thesis and appendix document is, unless otherwise stated created and owned by the author of this thesis.

List of Publications

Van Mil, I.W., Popovic Larsen, O., Mose, K., & Iversen, A. (2021). Design with Knowledge – Light in Learning Environments. In M. Mahat, W. Imms. (Ed.), Teacher Transition into Innovative Learning Environments – A Global Perspective, (1). 203- 313, Singapore (SE): Springer Singapore. (*)

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Table of Contents

1. INTRODUCTION 1.1

Denmark’s Folkeskole Learning Environment 1.1.1 1.1.2 1.1.3 1.1.4 1.1.5

1.2

17 18

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TABLE OF CONTENTS

Reform’s Implications for School Buildings The Environment Influences Pupil Behaviour Artificial Lighting as a Behavioural Tool Light Pattern to Improve Quietness in Class Research Question

Research Methodology

1.2.1 Phase I – Preliminary Studies 1.2.2 Phase II – Field Experiment

Research Contributions 1.3.1 1.3.2 1.3.3 1.3.4

1.4

New Knowledge Tool for Teachers Enlighten Design Practitioners Improve the Indoor Quality of Schools

Structure of the Thesis

LEARNING SPACES AND PUPIL BEHAVIOUR

2.1

The Learning Environment 2.1.1 2.1.1 2.1.2 2.1.3

2.2

Denmark’s Folkeskole The 2014 Reform of the Folkeskole Three Reform Points relevant for Architects New Challenges for School Designers

A Field Study of Architectural Responses to the Reform

2.2.1 Typical Design Responses by Architects 2.2.2 An Apparent Missing Response

2.3

Disturbances Caused by Pupils

2.3.1 Type of Disturbances Caused by Pupils 2.3.2 Three Types of Disruptive Behaviours 2.3.3 Definition of Disruptive Pupil Behaviour

2.4

The Physical Environment and Pupil Behaviour

2.4.1 The Physical Learning Environment Matters 2.4.2 Behavioural Implications Associated with the Physical Learning Environment 2.4.3 Three Categories of Environmental Features

2.5 Summary

ARTIFICIAL LIGHT AND PUPIL BEHAVIOUR

3.1 Light and Human Behaviour 3.2 A Theoretical Framework

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3.2.1 3.2.2 3.2.3 3.2.3

3.3

Five Behavioural Outcomes Affected by Light The Pathways Through Which Light Works Three Behavioural Implications by the Physical Environment Conceptual Theoretical Framework

Literature Review: Artificial Light in Learning Environments 3.3.1 3.3.2 3.3.3 3.3.4 3.3.5

Light Intensity Light Colour Light Intensity and Colour Light Pattern The Artificial Light Characteristic of Interest

3.4 Summary

Table of Contents

1.3

ARTIFICIAL LIGHTING DESIGN FOR LEARNING SPACES

4.1

Designing Artificial Lighting for Indoor Environments

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4.1.1 4.1.2 4.1.3 4.1.4 4.1.5

4.2

Artificial Light in the Folkeskole Learning Environment 4.2.1 4.2.2 4.2.3 4.2.4

4.3

Architectural Lighting Design The Electrical Lighting System Design Aspirations for Artificial Lighting Our Visual Impression of a Space The Artificial Light Pattern

Artificial Lighting in the Learning Spaces Teacher’s Experience with Artificial Lighting The Architects Approach A Local Brightness Pattern

The Artificial Light Pattern to Encourage Quietness during Class

103

4.3.1 Suggestions from Research Literature 4.3.2 Ideas from Architectural Practice 4.3.3 The Alternative Light Pattern: Pools of Light

4.4 Summary

THE FIELD EXPERIMENT VARIABLES 5.1

An Experimental Field Study 5.1.1 5.1.2

5.2

106

109 110

Motivations for Experimenting in the Field Considerations for the Research Design

Treatment Variable: The Artificial Light Pattern

112

5.2.1 The Standard Uniform Light Pattern 5.2.2 The Non-Uniform Pools-of-Light Pattern 5.2.3 Assessment Methods Table of Contents

5.3

Outcome Variables: Pupil Behaviour and Performance 5.3.1 5.3.2 5.3.3 5.3.4

5.4

Intervening Variables 5.4.1 5.4.2 5.4.3 5.4.4 5.4.5

115

Study I: Noise During Class Study II: Disruptive Pupil Behaviour Study III: Cognitive Performance Data Collaborations

124

Architectural Variables Interior Variables Indoor Climate Variables Subject Variables Activity Variables

5.5 Summary

134

THE EXPERIMENTAL CONTEXT, SETUP AND DESIGN

137

6.1

138

The Experiment’s Learning Spaces 6.1.1 6.1.2 6.1.3 6.1.4 6.1.5 6.1.6

6.2

The Experiment’s Lighting Installation 6.2.1 6.2.2 6.2.3 6.2.4 6.2.5

6.3

Pupil Age Groups Spatial Organisation Interior Design Acoustic Properties Lighting Conditions Curricular Schedule

154

Light Tiles The Pendants Installation of the Experimental Lighting Making the Artificial Light Patterns Analysis of the Different Lighting Scenarios

The Experiment’s Research Protocol

170

6.3.1 Spring Experiment – Study I + II 6.3.2 Autumn Experiment – Study III

6.4 Summary 6.4.1 Comparability 6.4.2 Control and Experimental Situations

180

DATA COLLECTION, ANALYSIS, RESULTS AND CONCLUSION

185

Part I Spring Experiment 7.1

Study I: Noise During Class

187

7.2

Study II: Disruptive Pupil Behaviour

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7.1.1 Data Collection 7.1.2 Analysis 7.1.3 Results 7.1.4 Discussion

197

7.2.1 Data collection 7.2.2 Method of Analysis 7.2.3 Results 7.2.4 Discussion

7.3

Intervening Variables Studies

219

7.3.1 Natural Light 7.3.2 Temperature and Air Quality 7.3.3 Interior Variables 7.3.4 Subject Variables 7.3.5 Activity Variables 7.3.6 Discussion

Part II Autumn Experiment Study III: Cognitive Performance

231

7.4.1 Data Collection 7.4.1 Analysis 7.4.2 Results 7.4.3 Discussion

7.5

Indoor Climate Variables Studies

237

7.5.1 Analysis 7.5.2 Results 7.5.3 Discussion

Part III Summary and Conclusions 7.6 Summary 7.6.1 7.6.2 7.6.3 7.6.4

Study I – Noise During Class Study II – Disruptive Pupil Behaviour Study III – Cognitive Performance Intervening Variables

7.7 Conclusion

8. DISCUSSION 8.1

Research Contributions 8.1.1 8.1.2 8.1.3 8.1.4 8.1.5

8.2

244

247

251 251

Artificial and Natural Light, a Joint Condition Variable Lighting Conditions Tool to Influence Pupil Behaviour Permanently Installed and Expanded Design Design Approach and Recommendations

Experimental Field Study

259

8.2.1 Validity 8.2.2 Reliability 8.2.3 Repeatability 8.2.4 Generalizability

8.3

Future Research

265

8.3.1 Variations in Artificial Lighting Designs 8.3.2 Relationship with the Indoor Environment 8.3.3 Applied Research

REFERENCES 269

Table of Contents

7.4

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Introduction

Light in buildings does not only define how well we can see, it has also been found to affect our mood, motivation, social behaviour, performance, health and general well-being (Boyce, 2014). For educational environments these implications of light have been found to affect pupils’ learning outcomes. This study aims to advance our knowledge about the relationship between light and learning by exploring if exposure to different artificial light conditions in class influences pupils’ behaviour and performance. Primary education has evolved significantly over the past decades and widely shifted from a teacher-orientated approach to a more student-orientated approach that, amongst others, embraces a more diversified palette of learning activities. This shift has not only changed the instructional and managerial load for teachers; it also sets new requirements for the spaces hosting this new pedagogy. As an architectural lighting designer who advocates light in the built environment should support the occupant’s visual and non-visual needs, my interest became to investigate what role artificial lighting could play in the creation of learning spaces that are supportive of the new pedagogy, and herewith enhances the learning outcomes. From my professional experience thus far and from conversations with practicing school-designers it appears that attention for light in learning spaces primarily goes out to optimize the natural light conditions, while artificial light is mainly considered an add-on to guarantee good visibility during all hours of use. This approach is also endorsed by most building regulations as these typically focus on visibility aspects. As a result, it appears this approach led to the widespread use of ceiling-based lighting systems that typically illuminate the entire learning space relatively evenly. Although this type of lighting design typically ensures good visibility, it does not offer much prospect to address the changes brought about by the new pedagogy. This research explores whether an alternative lighting design approach could support pupil’s new learning better. This chapter introduces the research that was undertaken hereto. Section 1.1 describes the context it is situated in, that of the Danish Folkeskole, and outlines a specific challenge it looks to address, namely, to improve quietness during class as advocated by the 2014 reform of the Folkeskole pedagogy. Section 1.2 outlines the twophased research design that has been followed and summarises the different research methods applied per phase. Section 1.3 outlines the contributions this research seeks to make to the academic fields of lighting science and environmental psychology as well as to the practice field of architectural design and the educational community in general. Section 1.4 functions as a reader’s guide and outlines the structure of this thesis further.

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INTRODUCTION

Introduction

1.1

Denmark’s Folkeskole Learning Environment

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This research has particular pertinence to Denmark, where a significant reform of the national system for primary and lower secondary education, the Folkeskole, took place in 2014. The reform aims to better pupils’ learning outcomes and introduced amongst others a longer school day and a broader palette of learning activities. It also encourages pupils to be more physically active as part of the overall curriculum. Another focus point of the reform is to improve the indoor conditions of the learning environment to benefit pupils’ well-being in general, and explicitly states the need to improve quietness during class (UVM, 2014). This is specifically addressed by the reform because disturbances, most notably in form of noise, were found prevalent in the Danish Folkeskole (Søndergaard et al., 2014). This is problematic because disturbances interrupt pupils’ attention to their learning, which has been found to negatively affect their performance (Woolner & Hall, 2010; Sala & Rantala, 2016). The aim of this reform point is to reduce class disturbances and herewith better learning outcomes.

Introduction

1.1.1

Reform’s Implications for School Buildings

The changes brought about by the reform did not only set new challenges for teachers and school management, they also presented new conditions for school-building designers to address. One particular challenge lies in the observation that the longer school days, diversified learning activities and increased physical play are seemingly at odds with the need for creating a calmer or more quiet, learning environment. While the first changes may benefit from spatial flexibility, openness and allowances for (social) interactions, the latter may require a setting that radiates greater intimacy, shielding and privacy. This research seeks to explore in what ways the learning environment itself can support teachers to manage these different learning settings, and specifically looks at how it can assist teachers to improve quietness during class.

1.1.2

The Environment Influences Pupil Behaviour

An important task for teachers is to help pupils concentrate on activities that require sustained focus. These activities are referred to in this research as focussed-learning activities. Typically, pupils’ ability to concentrate is compromised by disturbances occurring during these activities. Disturbances may have various causes, both originating from outside or inside the learning space. Though generally it was found that pupils themselves are the main cause, often expressed in form of noise (Emmer, 1984; Stavnes, 2014). The traditional way for teachers to manage pupil behaviour considered disturbing is through classroom management strategies, which

Thus far architects have mainly responded to the reform’s demand to improve quietness during class by addressing the symptoms of disturbances, for example by applying sound absorbing materials to mitigate noise. A reason for such symptom approach may be that most of the research exploring the impact of (a feature of) the environment on pupils has focussed on measuring change in their academic performance. Although these studies reveal numerically how the environment may support or hinder learning outcomes, they do not provide insight in underlying behavioural mechanisms such as change in attention, motivation and social behaviour that are incited by these environmental qualities. But in order to design constructive learning spaces that can also be effectively managed, it is critical for designers and school-users to understand those underlying relations. Therefore, advancing our knowledge about the relationship between (features of) the learning environment and pupil behaviour more fundamentally seems highly relevant.

1.1.3

Artificial Lighting as a Behavioural Tool

One particular environmental feature found capable of influencing occupant behaviour is light. Light in the built environment is generally considered to foremost service human vision during all hours of use so that occupants can see their surroundings well, move around safely and perform their tasks. But theoretical models as proposed by Peter Boyce (2014) and Jennifer Veitch (2001) also point towards several non-vision related workings of light, amongst others by stimulating our perceptive-cognitive system. Through this pathway light has been found capable to provoke emotional responses in occupants affecting one’s mood, to influence cognitive processes like attention and motivation, which in turn affect

Introduction

However, research has revealed that certain environmental features have the capacity to influence pupil behaviour in various ways too. For example, the type of furniture, the arrangement thereof and the layout of the learning space itself have been found to influence how pupils interact and collaborate (Gifford, 2007; Simonsen et al., 2008; Tanner, 2009). Flexible provisions as movable wall dividers and partition screens were shown to affect pupils’ sense of privacy and shelter, and herewith their level of attention to their task (Gifford, 2007; Tanner, 2009; Cheryan et al., 2014). The sound, light, temperature, and air quality conditions in the learning space were found to particularly affect pupils’ (dis)comfort, mood and academic performance (Küller & Lindsten, 1992; Heschong, 1999; Wargocki & Wyon, 2007; Marchand et al., 2014). These findings imply that besides the teacher (features of) the learning environment itself are also capable of informing pupil behaviour.

p. 19

commonly rely on interactions between teachers and pupils. Most of the critical tools available here are of instructional or procedural nature such as levels of pupil engagement or rules for speaking in class (Simonsen et al., 2008).

behavioural outcomes such as task performance (Veitch, 20o1; Boyce, 2014; de Kort, 2014). These findings imply that light, as a feature of the physical environment, has the capacity to influence occupant behaviour. p. 20

The light condition in spaces occupied by people during daytime is typically composed of natural and artificial light. A review of literature associated with the fields of lighting science and environmental psychology revealed researchers have been working the past decades towards comprehending the visual and non-visual implications of light (see Chapter 3). Although natural and artificial light have been documented to affect occupants via both pathways, design practitioners appear to typically consider natural light a primary quality of indoor spaces, and to pay significant attention towards optimizing natural condition in their buildings. Artificial light on the other hand is mostly considered complementary to safeguard appropriate visibility when the natural light is lacking.

Introduction

The latter is an important observation as the availability of natural light is bound to certain hours and weather conditions, and its availability is therefore uncertain. While artificial light is produced by an electrical lighting system and available on-demand; often as simple as flipping a wall switch. Another quality of artificial lighting is that one can precisely define where it is present in a space, and where not. These system design decisions result in a composition of lighter and darker areas in a space, also referred to as a light pattern. In comparison to natural light, artificial lighting thus allows for much greater control over when and where light emitted by the lighting system is present in a space. This control affords to explore how artificial lighting, and the artificial light pattern in particular, could act as a tool to address certain pupil behaviours, and herewith improve quietness during class as advocated by the 2014 reform.

1.1.4

Light Pattern to Improve Quietness in Class

Field studies in six Danish Folkeskole revealed that these learning spaces typically feature the same type of artificial light pattern that can be described as relatively uniform, meaning featuring little variation between darker and lighter areas. This uniform pattern is typically the outcome of a ceiling-based lighting system that distributes the emitted light relatively evenly across the learning space. This type of pattern appears to align well with the design practitioners’ view concerning the purpose for artificial lighting in learning spaces as argued in the previous section, namely, to attend to the visual needs of pupils placed anywhere throughout the space. Research exploring potential implications of the light pattern for room occupants is still scare, but those available indicate that the light pattern influences the observers’ visual impression of a space, and that certain patterns appear preferred over others (Flynn et al., 1973; Loe et al., 1994). These impressions and preferences appear

The alternative light pattern chosen to investigate this proposition is referred to as pools-of-light. The choice for this pattern was informed by beforementioned research findings as well as by observed teaching practices in the visited Folkeskole. The lighting system to create the pools-of-light pattern was developed together with experienced school designers at Henning Larsen. In essence, the pools-of-light pattern features brighter zones (pools) of light set in relatively darker surroundings. The intention with this pattern is to attract pupils into these brighter areas where they would feel safe to withdraw into their own world. It is hypothesized that such stateof-being would direct pupil’s attention inwards and discourage behaviours that typically result in noise or other forms of unrest. As less disturbances equals less interruptions to pupil’s attention, such change could ultimately benefit their learning performance.

1.1.5

Research Question

Central to this research is the quest to create learning environments that are supportive of pupils’ learning performance. It specifically addresses the need to improve quietness during class as called for by the 2014 Folkeskole reform. A quieter environment can be achieved by reducing disturbances, which are found to be mainly caused by pupils. It is hypothesised that the artificial lighting in the learning space, besides enabling good sight, can also act as a tool to reduce the occurrence of disturbing behaviours. In order to test this hypothesis, this research investigates whether exposing pupils to an alternative artificial light pattern, referred to as pools-of-light, elicits desired behavioural change. The questions this research looks to address are therefore formulated as: Does exposure to the pools-of-light pattern in the Folkeskole learning environment discourage disturbing pupil behaviours and herewith improve quietness during class? And if so, does this change significantly affect pupils’ learning performance? In order to answer these questions, an experimental field study has been performed in a real-life Folkeskole learning environment. This study explored whether exposure to the pools-of-light pattern affected pupils’ behaviour and learning performance compared to exposure to the standard uniform light pattern.

p. 21 Introduction

to be shared experiences. Findings also suggest that light patterns incite mood responses which in turn affect the observer’s behaviour and performance (Veitch, 2001; Govén et al., 2011). A mechanism that may explain the workings hereof is for example the ability of the light pattern to direct the observer’s attention, particularly towards high-brightness areas. This mechanism may improve the observers’ attention to a task when accentuated relative to its surroundings. These findings inspired this study to explore if exposing pupils to an alternative light pattern could encourage a behavioural change in pupils that reduces disturbances and herewith improve quietness during class.

1.2

Research Methodology

p. 22

This research is embedded in the academic fields of environmental psychology and lighting science, and the professional field of architectural lighting design. Methods, tools and techniques from all fields were used to collect the necessary data. The research can be split into two sequential phases of data collection activities: •

Phase I – a first round of data collection that informed the formulation of the research question (preliminary studies).

•

Phase II – a second round of data collection that informed the answer to this research question (experimental field study).

Figure 1.1 provides a schematic overview of these two consecutive phases. The following sections will further introduce the two illustrative diagrams presented in this schematic overview and summarize the research methods and techniques used per phase. Phase I – Preliminary Studies

Phase II – Experimental Field Study

Folkeskole Learning Environment

Research Question

(A) uniform light

Outcome Variables

(I) noise

(II) behaviour

(III) performance

(B) pools of light

Intervening Variables

Treatment Variable

Introduction

(1) architecture (2) interior

(3) climate

Findings

(4) pupils

(5) activity

Figure 1.1 Schematic overview of the two-phased research methodology

1.2.1

Phase I – Preliminary Studies

The preliminary studies revolved around exploring two topic-areas within the context of the Folkeskole learning environment: •

the physical environment in which the learning takes place, and specifically the artificial lighting therein; and

•

pupil behaviour, and particularly those behaviours found disruptive to or to hinder pupils’ attention to their learning.

The diagram shown in Figure 1.2 (enlargement of Figure 1.1) serves to illustrate the relationship between these topic-areas.

p. 23 Figure 1.2 Schematic diagram of the research context and topic areas of interest

The diagram in Figure 1.2 is made up out of five circles. The outer circle represents the context of this research: the Folkeskole learning environment. A learning environment as a whole is typically informed by the adhered to pedagogy, the management style and organisational structure, the pupil population as well as the physical context the learning takes place in (Higgins et al., 2005; Barrett et al., 2015). The two medium-sized circles represent the two topic areas of the learning environment this research focusses on: •

The first topic area is the physical environment, which is represented by the light-yellow medium-sized circle in the diagram, and a subtopic area in particular, the artificial lighting, which is represented by a dark-yellow small-sized circle in the diagram.

•

The second topic area is pupil behaviour, which is represented by a light-blue medium-sized circle in the diagram. Pupil behaviour may refer to a whole range of ways that pupils can act in a school environment including their (pro)social behaviours, learning behaviours, and disruptive or aggressive behaviours. The latter, disruptive behaviours, are the type of behaviours of particular interest in this research. This subtopic area is represented by a darker-blue small-sized circle in the diagram.

This research explores the relationship between the two subtopic areas of interest: artificial lighting as a feature of the learning environment, and disruptive pupil behaviour. This relationship is represented in the diagram by a green-coloured area representing the overlap between the two small-sized subtopic circles.

Introduction

Note: the size of each circle is illustrative only and not representing any weighting

Reseach Methods

p. 24

During the preliminary studies the Folkeskole learning environment in general, and the two subtopics artificial lighting and disruptive pupil behaviour in particular, have been studied in order to arrive at a meaningful research question. These studies included three data collection methods: (1) literature review, (2) field studies, and (3) expert interviews. (1) A review of literature associated with the 2014 Folkeskole reform, the implications of the physical learning environment, and artificial lighting and its effect on building occupants allowed to ground the research in existing knowledge.

Introduction

(2) Two rounds of field studies in six different Folkeskole further informed the direction of the research. The first round of field studies took place in four newly built or renovated school buildings since the 2014 reform and provided insight into the solutions and responses applied by architects thus far. The second round of field studies took place in two school buildings designed before the 2014 reform, and two school buildings thereafter. All four are in use today. These comparison studies provided insight in the typical condition of the (artificial) lighting in the Folkeskole learning spaces today. (3) Two rounds of interviews allowed to uncover what is missing or lacking in today’s Folkeskole learning environments. These interviews were held with two types of learning environment experts: teachers and school-designers. The first round of talks included six teachers currently active in the Folkeskole with the purpose of gaining insight into how they use the artificial lighting, how they experience the subsequent lighting conditions, and to uncover what is malfunctioning or lacking in their opinion. The second round of talks included four schoolbuilding architects, with the purpose of gaining insight in their approach to designing the artificial lighting, and the requirements it has to fulfil. Both experts were also consulted about potential alternative artificial lighting designs that could help improve quietness in class. The findings from these three data sets jointly allowed to formulate the question this study looks to address. Chapters 2,3 and 4 describe these three studies and findings further.

1.2.2

Phase II – Field Experiment

To answer the research question, a full-scale field experiment has been conducted in a live Folkeskole. This method of research was chosen for (1) perceptual, (2) behavioural and (3) temporal reasons:

Our experience of light conditions in the built environment depends heavily on the complex interactions between the light itself, and the architectural context it is placed in. This experience is not easily replicable in a laboratory or a virtual setting. Experimenting in a full-scale, real-life environment allows to investigate realistic occupant experiences with light.

•

Because the interest of this research is to assess inflicted (change in) pupil behaviour, studying pupils in their real habitat while continuing their normal routines allows to reveal realistic behavioural change opposed to simulated ones.

•

In order to move beyond the novelty of being exposed to the (temporary) experimental lighting pattern, pools-of-light, a relatively long exposure time to the pattern is necessary, which is most often not feasible in laboratory or virtual setting.

p. 25

•

The treatment variable in the field experiment, or the variable manipulated, is the artificial light pattern in the learning space. The two light patterns were compared are: A) standard uniform light pattern and B) experimental pools-of-light pattern.

•

The three outcome variables of the field experiment that were respectively monitored, observed or measured for change are: (I) noise levels, (II) disruptive behaviours, and (III) cognitive performance. The first two variables are considered to reveal changes in pupil behaviour that affect quietness in class, most notably vocal change. The third variable reveals any change in pupil’s cognitive performance by means of specialized tests. This variable was included in the study because ultimately, the purpose of a quieter learning environment is to enable pupils to concentrate better on their learning and perform better.

•

Fourteen potentially intervening variables were identified for this experiment. These were grouped into five categories (1 – 5). Some of these variables were controlled during the experiment, while others had to be monitored for significant change.

Figure 1.3 (enlargement of Figure 1.1) provides a schematic overview of these three types of variables included in this research. In order to collect data on all these variables, the field experiment included a broad range of data collection methods and tools. Chapter 5, 6 and 7 describe the methods used, the context and setup of the experiment, the data collection procedure applied, the processing of this data, and interpretation of the results.

Introduction

The field experiment took place in four learning spaces of a real Folkeskole environment, namely Frederiksbjerg School located in Aarhus (DK). Three variable-sets have been studied during the experiment: treatment variable, outcome variables, and potentially intervening variables that may confound the research findings.

Folkeskole Learning Environment

(A) uniform light

Outcome Variables

(I) noise

(II) behaviour

(III) performance

(B) pools of light

Intervening Variables

Treatment Variable

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(1) architecture (2) interior

(3) climate

(4) pupils

(5) activity

Figure 1.3 Schematic diagram of the research context and topic areas of interest

1.3

Research Contributions

Introduction

This research looks to contribute with: (1) new knowledge about how the built environment, and light in particular, influences occupant behaviour; (2) an exemplary design of how artificial lighting may act as a tool for teachers; (3) specific design information for the architectural industry, and (4) a contribution to the broader debate about improving indoor quality of learning environments in general.

1.3.1

New Knowledge

The aim of this research is to add new knowledge to the academic fields of environmental psychology and lighting science about how artificial lighting in the learning environment affects pupil’s learning. It does this by investigating the underlying mechanism through which the artificial light pattern may affect behavioural outcomes in pupils that influence their ability to concentrate on their learning. In addition, the research also provides methodological contributions through learnings from the performed field experiment itself.

1.3.2

Tool for Teachers

The research also revolves around capacitating teachers to use the artificial lighting as a behavioural tool. The fact that the setup of the experiment is not prescriptive in how and when certain lighting features were to be used, allowed to explore how the artificial lighting could be best used as a tool to manage disruptive pupil

1.3.3

p. 27

behaviours. And because the experimental lighting installation has been kept in place after the experiment, and its design principle extended into other learning spaces of the school too, makes this installation itself also a concrete contribution to a particular learning environment, namely Frederiksbjerg Skole, with the potential to be implemented in other learning environments too.

Enlighten Design Practitioners

Constructive Design Tool The research, setup as a practice-based research project, directly contributes to Henning Larsen’s ambition to grow their expertise of how their designed environments can (deliberately) affect occupant behaviour. This knowledge will serve the wider architectural community too. In addition, by being embedded in practice this research also allows to exemplify how artificial lighting can be a constructive design tool that the building industry can apply in order to create indoor environments in which occupants can perform their tasks or activities to the best of their abilities.

The research also points towards adjusting the current building regulations with regards to artificial lighting. Commonly these regulations include recommendations that guide built environment designers towards appropriately configured light applications that, at the very least, ensure minimal visual comfort so that users of these environments can perform their activities as well as possible. Recommendations for learning spaces, as for example provided in European standard EN-12464-1, prescribe average illuminance levels to be maintained across the horizontal working plane, combined with a degree of uniformity. Guidelines like this offer very little room to design anything other than standardized artificial lighting. However, the findings of the field experiment may suggest that doing just that, deviating from the standardized solution, might improve the conditions for learning.

Cost Effective Solution Another reason to focus on artificial lighting as a means to improve the learning environment, is that it is a relatively (cost) effective tool in comparison to other features of the environment such as those dealing with air quality or noise treatment. This might be particularly relevant for those schools looking to renovate instead of building new. Where a new building naturally allows architects to apply best practices for indoor quality into its design, renovation projects often encounter significant limitations as one has to work with what is already there, and often while being in active use. This is particularly relevant for Denmark, where about 90 percent of the Folkeskole building stock was built before1970, and only about ten

Introduction

Building Regulations

p. 28

percent thereafter (Kristensen et al., 2004). The consequence is that the majority of school buildings is outdated by today's standards, and upgrading these facilities is desired. For some cases this might involve a completely new building, however for the majority it will likely concern renovations due to governmental budget limitations. Artificial lighting may be one of the tools through which learning environment improvements may be relatively easily attained in renovation projects. Existing luminaires are often placed in fairly accessible locations and retrofitting these with newer products can be relatively straightforward. Advancements made within the lighting industry for example in light source and control technology and miniaturization also allow for greater efficiency, reduced maintenance and higher durability of artificial lighting in the built environment. These advancements also offer opportunities to expand the capabilities of artificial lighting with features such as intensity and colour control, adaptivity and daylight mimicking. The challenge lies in defining constructive applications for this broadened palette of artificial lighting tools to benefit pupil’s learning performance. This research contributes by exploring one particular type of artificial solution: variability of the light pattern.

1.3.4

Improve the Indoor Quality of Schools

Introduction

The research also responds to more general call to improve the indoor quality of learning environments as various research has revealed it is inadequate in many of today’s schools. Indoor quality is amongst others linked to the indoor climate variables light, sound, temperature and air quality. These variables have been linked to significantly influence pupils’ learning outcomes. For example, researchers in the UK studied the status of the indoor climate in153 classrooms across 27 very diverse primary schools and compared these against pupils’ academic results (Barrett et al., 2015). This study revealed that these variables are responsible for about eight percent of the variation in learning progress over a year. Several research initiatives uncovered that the status of the indoor climate in many schools does not meet today’s recommendations. In Denmark, a nation-wide study in 2011 looked at air quality and reported that 56 percent of the 743 measured Folkeskole learning spaces exhibited poor ventilation rates (Toftum et al., 2011). A more extensive follow-up study in 2017 found that of the learning spaces surveyed at some point during use 91 percent exceeded the recommended CO2 level, 63 percent exceeded the recommended maximum sound level, and 49 percent exceeded or fell below the recommended thresholds for lighting levels (Alexandra Institute, 2017; Center for Indeklima og Energi, 2017). Outside of Denmark similar findings emerged. In Sweden for example, a study including 324 schools exposed the status of the perceived quality of the indoor climate in schools by probing 7000+

p. 29

teachers for their experiences (Andersson et al., 2008). Findings showed that the most significant complaints concerned noise, dust and “stuffy” bad air, and to a lesser extent, varying temperatures. Fatigue, heavy headedness and headache were frequently reported and often related to both noise and deteriorated indoor air. In the USA the Heschong Group conducted a large study investigating the impact of daylight access in the classroom on pupils’ cognitive performance measured by standardized tests in more than 2000 classrooms (Heschong, 1999, 2003). They found that pupils exposed to higher amounts of daylight would score significantly better than peers in less exposed situations.

1.4

Structure of the Thesis

This PhD thesis book comprises eight chapters. Between Chapter 1 Introduction and Chapter 8 Discussion, the thesis is broadly structured in two parts: •

Part I_Framework – Chapter 2, 3 and 4 provide background and context, and describe the theoretical foundation for this research.

•

Part II_Experiment – Chapter 5, 6 and 7 describe the design, execution, data analysis and findings of a field experiment investigating further the relation between light and behaviour.

See Figure 1.4 for an illustration of the overall thesis structure. _________________________________________________________ Chapter 1 – Introduction, introduces the project, describes the problem it looks to address, and explains why artificial lighting was chosen as a means to explore a solution. This is followed by the formulation of the research question. The chapter then outlines the contributions the research seeks to make to the academic fields of lighting science and environmental psychology as well as towards the practice fields of architectural lighting design and education. The chapter concludes with an overview of the thesis structure. * https://realdania.dk/projekter/skolernes-indeklima https://www.sustainablebuild.dk/tag-en/det-gode-indeliv/ https://www.gate21.dk/project/lighting-metropolis/

Introduction

These studies expose that the indoor quality of many schools can be considered inadequate, and the authors called for improvements. In Denmark, this has triggered several public and private initiatives encouraging academics and practitioners to collaboratively explore ways to improve the indoor conditions in its schools. Examples thereof are: “Skolernes indeklima” by Realdania, “Den Gode Indeliv” by Sustainable Build, and “Lys i Skole” by Lighting Metropolis / Gate21 *. This research contributes to this call by exploring how artificial light can help improve the overall indoor quality of learning environments.

Thesis Structure

Ch.1 Introduction

p. 30

I Framework

Ch.2 The Learning Environment and Pupil Behaviour

Ch.3 Light and Human Behaviour

Ch.4 Artificial Lighting Design for Learning Spaces

II Experiment

Ch.5 The Field Experiment Variables

Ch.6 Experimental Context, Setup and Design

Ch.7 Data Collection, Analysis, Results and Conclusion

Introduction

Ch.8 Discussion

Figure 1.4 Thesis Structure

Part I: Framework (Chapters 2, 3 and 4) Chapters 2, 3 and 4 outline the underlying foundations of this study by respectively providing a background setting, theoretical framework and practical context. Chapter 2 – The Learning Environment and Pupil Behaviour, outlines the motive for undertaking this research, namely a specific implication of the reform of Denmark’s Folkeskole system in 2014 that requires schools to improve the conditions for undisturbed learning. The main cause of disruptions appears to be the pupils themselves. The approaches taken by architects to help reduce disruptions during class are described, which reveals a missing response. As research revealed the physical environment is capable of influencing pupil behaviour, there is an apparent opportunity for architects to address disruptive behaviours in their building designs, and herewith contribute to a calmer learning environment.

Chapter 4 – Artificial Lighting for Learning Spaces, introduces the practice of artificial lighting design, and how it shapes the occupant’s visual impression of physical space. Some practical aspects of lighting design are introduced that inform the research approach, and the design freedom of the lighting designer is sketched as the light pattern–an assemblage of lighting qualities such as intensity, colour and spread. A field study in four representative primary learning environments in Denmark allowed to define the current state of the artificial lighting herein, and how it is experienced by their users, and what is missing. Supported by conversations with educational architects, the idea is presented to investigate whether a non-uniform pools-of-light design may elicit behavioural changes in pupils that benefit their concentration. _________________________________________________________ Part II: Experiment (Chapters 5, 6 and 7) Chapters 5, 6 and 7 describe the field experiment itself. Chapter 5 – The Field Experiment Variables, introduces the field experiment as a method, and outlines the three variable-sets that have been monitored during the study: (1) the treatment variable, constituted by two artificial light patterns pupils have been exposed to in their respective learning spaces; (2) the three outcome variables that were employed to investigate an effect of these light patterns on pupil’s behaviour and learning performance: classroom noise levels, three observable disruptive behaviours, and cognitive performance; and (3) fourteen potentially intervening variables that were identified to potentially contaminate the data. For each variable the method used to collect the necessary data is provided. Chapter 6 – Experimental Context, Setup and Design, outlines the experimental context, setup and design of the research. It details the conditions of the four learning spaces that hosted the experiment and describes the design and functioning of the lighting system temporarily installed to enable controlled exposure to two different artificial lighting conditions. It also details the research design that was applied, and the protocol followed to collect the data consistently and reliably.

p. 31 Introduction

Chapter 3 – Light and Human Behaviour, argues that artificial lighting could be one of the learning environment’s features available to influence pupil behaviour. Hereto, the theoretical context of the research is presented. Most notably, Jennifer Veitch’s work describing the various influences of light on human performance, and Peter Boyce’s conceptual framework outlining three (known) pathways through which lighting conditions influence human performance. A review of associated literature allows to specifically discuss what is known about the effects and workings of light on occupants of learning environments.

p. 32

Chapter 7 – Data Collection, Analysis, Results and Conclusion, covers the data collection itself, the analysis thereof and interpretation of the results for each proxy variable, as well as handling of the fourteen potentially intervening variables. The chapter concludes with relating these findings to the original research question. _________________________________________________________ Chapter 8 – Discussion. This chapter discusses findings that may not directly be relevant to answer the research question, but are of value to the academic and practice fields this research is associated with. The chapter reviews learnings from the field experiment as a research method, and elaborates on the field experiment’s validity, reliability and replicability. It concludes with suggestions for future research.

Appendix Book

Introduction

Alongside this thesis book, a complementary appendix book is issued that is supportive to the material presented in this document. Throughout the thesis references are made to the relevant appendix section(s) ranging between A and X.

Introduction

p. 33

p. 34

Learning Spaces and Pupil Behaviour

This chapter introduces the research context and outlines the problem it looks to address here. The context is the Folkeskole— Denmark’s institutions for primary and lower secondary education, where in 2014 a reform provided for guidelines to improve the indoor quality of these learning environments. The reform explicitly highlighted the need to improve quietness during class. One way to achieve this is to reduce the occurrence of disturbances, of which the dominant cause is found to be the pupils themselves. This chapter outlines the premise that (features of) the physical learning environment could be one of the tools available to manage disruptive pupil behaviours and wherewith attain greater calmness during class as encouraged by the reform.

p. 35

LEARNING SPACES AND PUPIL BEHAVIOUR

Figure 1.1. illustrates the two topic-areas, the physical learning environment and pupil behaviour, discussed in this chapter within the context of the Danish Folkeskole learning environment. Learning Spaces and Pupil Behaviour

FFiigguurree 22..11 Schematic Schematic diagram diagram of of the the research research context context and and topic-areas topic-areas of of interest interest

This chapter is structured in five sections. Section 2.1 outlines the implications of the Folkeskole reform, specifically for school buildings. Section 2.2 presents findings from field studies exploring architectural responses to the reform thus far. Section 2.3 describes what is understood by disruptive pupil behaviour, the main causer of unrest during class. Section 2.4 defines how the physical learning environment could assist with managing these behaviours. Section 2.5 provides for a summary of the chapter and explains how findings discussed in the preceding sections informed the problem this research looks to address.

2.1

The Learning Environment

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This section introduces the Folkeskole learning environment and describes the ensuing challenges brought about by the 2014 reform that are particularly relevant for school designers. One of these is the improvement of the learning environment by reducing disturbances, in particular from noise. The source of disturbances may reside either outside or inside the classroom, though the dominant cause is found to be the pupils themselves. A potential tool to manage disruptive pupil behaviours may reside in the psychical learning environment itself.

2.1.1

Denmark’s Folkeskole

Learning Spaces and Pupil Behaviour

The learning environment is generally understood to be the whole of social, physical, psychological, and pedagogical aspects that constitute the learning context *. Although this study eventually focusses on one component, namely the physical component, it is important to acknowledge it does not stand-alone but is related to other components of the learning environment too. The Folkeskole, the specific learning environment this research is addressing, is Denmark’s system for primary and lower secondary education for pupils between the ages of circa 6 and 16. The key motivation to focus on this particular typology is a reform that came in place in 2014. Of a number of changes relative to the Folkeskole before 2014, this reform significantly affected how school buildings should be used, and therefore, designed. Where a learning environment traditionally is understood to be the domain of teachers that manage classrooms and educate pupils, this reform implicitly reaffirmed the importance of the disciplines that shape the physical learning environment, i.e. the multiple disciplines of building design. The architect Herman Herzberger, known for his work on schools and universities, has compared learning with the creation of architectural space:

To learn is to create order and coherence in the mind, to form structures where there had been none. Making space is applying structure where emptiness or chaos once prevailed. Learning, then, is a way of creating space in one’s head: space for other aspects, ideas, relations, interpretation, associations. So learning is perhaps the finest imaginable approach to the concept of space. (Herzberger, 2008, p. 67)

As Herzberger suggests, understanding the changes brought about by the reform and interpreting their implications for the physical conditions of the learning environment is an important prerequisite for the reform’s success. * As defined by the OECD (Organisation for Economic Co-operation and Development)

The 2014 Reform of the Folkeskole

The 2014 reform of the Folkeskole was widely supported politically and was initiated to maintain and develop the strengths and academic standards of the primary schools (UVM, 2014). This has brought about significant change in how pupils are being taught, the type of activities that take place, and how a school day is programmed. Not only does this set new challenges for management, teachers and staff, but also for the physical environments, the school buildings that host this new learning.

p. 37

2.1.2

2.1.3

Three Reform Points relevant for Architects

Three of these focus points bear specific significance for this research, as they raise questions towards the use and design of the physical learning environment that support the new teaching: •

Point 1: A longer and more varied school day,

•

Point 3: More physical exercise (PE) and activity; and

•

Point 13: Better learning environment and quietness in class.

Point 1 introduces a longer and more varied school day that is characterised by more teaching time, diversified pedagogical methods and more emphasis is placed on catering for individual pupil preferences. This allows teachers to better support the individual academic development of pupils, and to practice more practical, student-led, and application-oriented forms of teaching. One of the consequences of these new methods is that learning and teaching settings now may take many different forms and shapes; ranging from rather traditional ways of individual work and group tutoring, to self-regulating activities requiring pupils to collaborate more and learn-by-doing together. As a consequence, the way that the learning environment is to be used for teaching and learning activities and the needs it should fulfil, has diversified significantly. Point 3 addresses physical activity during teaching and in breaks. The reform prescribes that pupils need to move, play or otherwise be physically active for at least 45 minutes in total each day. The reasoning behind it is that increased physical activity is found to be related to higher levels of motivation and to improvements in the

Learning Spaces and Pupil Behaviour

The 2014 reform was developed around three main goals: (1) improving pupil achievement (or academic level), (2) equity, and (3) well-being. To support these three goals, the ministry of education defined sixteen focus points in which the changes were articulated (UVM, 2013, 2014). These focus points address issues such as pedagogical methods, curricular subjects, a simplification of learning, teacher support, and community engagement.

p. 38

overall learning process. The reform is not prescriptive in how physical activity is to be made part of the curriculum. It may take place during fewer longer stretches, such as PE classes or break sessions, but also in multiple shorter intervals with the option of integration in other learning activities. Thus, the learning environment, including the formal teaching areas, needs to accommodate interventions that encourage pupils to be more physically active in-between the formal learning activities. Point 13 addresses the importance of creating an environment supportive of pupils’ learning, and to specifically improve quietness during class. A supportive learning environment contributes to pupils’ general well-being, their aspiration to learn, and their actual ability to learn in the classroom. Improving quietness during class is specifically emphasised by the reform because disturbances and unrest, particularly in the form of noise, were found prevalent in the Danish Folkeskole (Søndergaard et al., 2014). This is considered a problem because disturbances as noise interrupt pupils’ concentration, which adversely impacts learning performance (Woolner & Hall, 2010; Sala & Rantala, 2016).

Learning Spaces and Pupil Behaviour

Disturbances may present in audible, visual or physical form. They may be environmental disturbances and originate either outside the learning space, for example traffic noise or sun glare, or inside the learning space, for example ventilation system noise or flickering lighting. However, the dominant source of unrest during class is found to be the pupils themselves as they partake in (learning) activities (Emmer, 1984; Stavnes, 2014). In order to attain a quiet learning environment, both environmental as well as behavioural causes of disturbances need to be addressed.

2.1.4

New Challenges for School Designers

Points 1, 3 and 13 prompted significant organisational and pedagogical change, but also set new challenges for school designers (UVM, 2014): •

Point 1: The longer and more-varied school day requires that the physical learning space allows for greater variations of use than was needed before 2014;

•

Point 3: The need for the formal learning activities to be alternated frequently with different states of physical activity requires school buildings to facilitate a broader range of play and movement;

•

Point 13: The need for the learning environment to support pupil well-being and improve quietness during class, requires comfortable environmental conditions and mitigating or preventing disturbances from occurring, whether caused by environmental sources or pupils.

Each of the three challenges (1, 3 and 13) brought about by the reform thus seemingly increase the teachers’ curricular and behaviour management load, indirectly taking time away from their pedagogical tasks and teaching in general. To act upon these challenges, it seems critical that the designers and users—teachers, staff, and perhaps pupils—of school buildings explore together how the physical learning environment may host and serve these diversified curricular and physical activities, while at the same time provide for supportive environmental conditions that help minimise disturbances during class – without the need to significantly increase the teachers’ management load. In order for these goals to be achieved, teachers should be capacitated to easily and effectively manage their learning environments.

2.2

A Field Study of Architectural Responses to the Reform

This section discusses the findings from a field study that was undertaken as part of this research to reveal what architectural responses so far have been implemented to address the reform demands. In three representative school buildings, a range of architectural solutions was identified that were meant to improve the learning environment. These solutions however do not seem to directly address the problem of disturbances caused by pupil’s behaviour; a task apparently left with the teachers. The question then emerges whether the physical learning environment itself could be able to assist teachers in managing these behaviours.

2.2.1

Typical Design Responses by Architects

Even though the 2014 reform itself is relatively young, architectural responses to the specific challenges following point 1, 3 and 13 could be identified in a number of recently built or renovated school buildings. As part of this research, field investigations in three representative school buildings were undertaken, that were

p. 39 Learning Spaces and Pupil Behaviour

Considering these three challenges jointly, another overarching challenge surfaces, that of an increased teacher management load. Point 1 and 3 encourage teachers to frequently change between different learning activities as well as movement breaks. This requires the teachers to repeatedly manage their pupils’ state of mind, behaviour and the learning setting to correspond with that specific type of activity, as well as to manage the transitions between these different activity forms effectively. Point 13 advocates to better the learning environment in general, and specially to decrease disturbances during class. As indicated, the dominant causes of disturbances are the pupils themselves. Addressing their behaviour also requires active management by the teacher.

p. 40

assessed in line with the three focus points of the reform. The first two schools, Frederiksbjerg Skole and Sophieskolen, are newly built, while the third school, Kirkebjerg Skole, includes renovation of an existing building complemented by a newly built extension. See Figures 2.2 – 2.4 for impressions of the three school buildings.

Learning Spaces and Pupil Behaviour

Figure 2.2 Frederiksbjerg Skole (2016) in

Figure 2.3 Sophieskolen (2016) in Nykøbing

Figure 2.4 Kirkebjerg Skole (2016) in

Aarhus. The new building was designed

Falster. The new building was designed by

Copenhagen. The renovation design was

by Henning Larsen Architects and GPP

TNT Arkitekter and Creo Arkitekter. The

done by KANT Arkitekter; the new

Arkitekter. The school hosts just under

school serves circa eight hundred pupils in

building by Core Arkitekter. The school

thousand pupils in central Aarhus *

the Guldborgsund municipality of Falster *

serve just over thousand pupils in the

(photo credits: Henning Larsen)

(photo credits: Creo Arkitekter)

Vanløse district of Copenhagen * (photo credits: KANT Arkitekter)

From the field observations it was possible to identify four types of architectural responses performed towards reform points 1, 3 and 13. These responses can be loosely defined as: (1) flexible learning units, (2) activity provoking interventions, (3) controlled natural light, and (4) improved acoustics. This section provides for a summary thereof. For an extended discussion on the field study, the school buildings and identified response typologies, see Appendix A. (1) Flexible learning units are considered the architects response to reform point 1: the longer and more diverse school day. To accommodate and support the diverse curricular activities, the architects of the three field study buildings focussed on creating subject-orientated learning clusters, that are placed throughout the school building. A cluster typically contains multiple spaces, that do not display a predefined use and furniture layout. Instead, the architects employed adaptable spatial provisions, such as retractable walls or moveable space dividers, and flexible furniture, such as movable desks and seats. These design solutions allow teachers and pupils to rearrange their space’s setup quickly, and redistribute pupils easily in different arrangements, for example in small teams, individually or as a larger group, herewith offering significant flexibility and adaptability to address the needs per activity. * https://uddannelsesstatistik.dk (visited February 2020)

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(2) Activity provoking interventions are considered the architects response to reform point 3: more PE and physical exercise and activity. In the three school buildings, architects designed and integrated a selection of playful interventions in the school’s premises that encourage pupils to engage in physical activities in and around the learning clusters. These interventions range from dedicated play and activity rooms hosting longerduration, scheduled activities, as well as integrated interventions in hallways or staircases, to provoke physical activity for example when pupils transition between clusters.

(3) Ensuring pupils (and teachers) are well exposed to natural light whilst occupying the learning space has been found to positively affect the health and well-being of pupils, and herewith their academic performance (Heschong, 1999, 2003). Window design optimised for natural light intake at each location has been given significant attention by the architects. At the same time, provisions such as blinds or shaders to avoid solar glare and internal heat gains were included too, enhancing the quality of the indoor climate as a whole. The artificial lighting appeared to be designed to contribute when natural light would be insufficient to ensure good visibility to all pupils. The two newly built schools featured a control system that would monitor light levels and adapt the output of the light system accordingly, herewith preventing unnecessary energy consumption. Herewith, it appears natural light is commonly considered a dominant light source, both for human comfort and health as well as from a sustainability perspective. (4) In response to the reform’s request to reduce disturbances during class, the architects seemingly choose to focus on attenuating noise disturbances by optimizing the learning space’s acoustic properties. For example, they attempt to dull sound levels inside a learning space through abundant use of sound-absorbing measures, including the chosen materials, selection of furniture, and use of flexible desk dividers. Attention also went out to attempt locking out external noise by applying double or triple glazing towards the surrounding environment and using (glazed) separation walls between the different learning spaces to limit noise travel. As well as specifying low sound producing building system such as the ventilation and blinds. Through these measures, architects attempt to reduce the impact of noise inside the learning space.

Learning Spaces and Pupil Behaviour

The remaining two responses (3) controlled natural light and (4) improved acoustics—deal with the design and quality of the indoor environment as discussed in point 13: better learning environment and quietness in class, and particularly through the indoor climate variables light and sound. In all three field study buildings it appeared specific attention was given to improve natural light intake and bettering the acoustic conditions in the learning spaces.

2.2.2

An Apparent Missing Response

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A critical observation about the solutions applied by architects thus far is that these do not seem to directly address the problem of disturbances caused by pupil’s behaviour; a task apparently left with the teachers. Their solutions focus mostly on attenuating the impact of noise, but seemingly not explore how to prevent noise, or any other types of disturbances for that matter, from occurring. But prevention could arguably be a more effective approach to accomplish quietness during class than only mitigating the impact. Architects have limited scope to avert disturbances from outside the learning space form occurring, but they could explore how the environment itself can assist in preventing disturbances originating inside the learning space. As pupils are found the dominant cause of disturbances, this approach would require that the learning environment assist with addressing disruptive pupil behaviours.

The Environment to assist in managing Disruptive Behaviour Learning Spaces and Pupil Behaviour

Managing disruptive pupil behaviour is typically a responsibility left with the teacher. The traditional way of influencing pupil’s behaviour is through various classroom management techniques, which predominantly rely on interactions between teachers and pupils. Classroom management can be described as a series of actions aimed at establishing a setting in which pupils engage in learning activities designated by the teacher, and in which disruptive and/or unproductive behaviours (to the learning) are kept to a minimum (Emmer, 1984). Most of the critical tools of classroom management are of instructional or procedural nature, such as varying the levels of pupil engagement or rules for speaking in class (Simonsen et al., 2008). However, these techniques bear heavily on teacher involvement, who already experience an increased management load due to the changes introduced by the reform itself (see section 2.1.3). In addition, a study initiated by the Danish Ministry of Education, found that disruptive pupil behaviour, and noise in particular, is prevalent in the Danish Folkeskole (Søndergaard et al., 2014). Teachers have said they spend a significant amount of their time addressing pupil behaviours that cause disturbances instead of putting this time towards their teaching, which effectively burdens the management load further (Emmer, 1984; Stavnes, 2014). Another trend that also amplified the teacher’s management load, is the steady increase of the number of pupils per class over the past years (Clausen et al., 2017). The number of pupils in Folkeskole classes have risen from an average of 20.1 pupils per class in 2009 to 21.5 pupils per class in 2015. Although this is a relatively small increase, it is important to state that the average contains considerable variations. In about 20% of the classes there are now more than 24 students in a single class. This is a significant greater

p. 43

group management load in comparison to the pre-reform situation. As a result, the teachers management load in the Folkeskole has significantly increased, particularly since the introduction of the new reform. Relying solely on the teacher’s skill to better quietness during class through the traditional management techniques may be insufficient. This research therefore set out to explore if and how the physical learning environment could assist teachers in the task of managing pupils (disruptive) behaviours instead of solely mitigating disruptive output such as noise. But in order to validate the potency of this premise, it is essential to first establish what constitutes disruptive pupil behaviour, and secondly, how this behaviour is found to implicate the teaching and learning.

Disturbances Caused by Pupils

This section unpacks how pupil’s attention during class is typically disturbed. Pupil-made disturbances typically manifest in audible (noise), visual or physical form. The behaviours found responsible for many of these disturbances are classified as: (a) irrelevant externalized expressions, (b) non-learning related social interactions, and (c) out-of-seat behaviours. Based hereon, a definition of disruptive pupil behaviour in general is provided which is adhered throughout this research.

2.3.1

Type of Disturbances Caused by Pupils

The attention of the architects for noise attenuation to improve quiet during class as described in the previous section, is not surprising because various studies have found that noise is one of the most significant disruptors during class, preventing pupils to maintain a state of concentration, which negatively impacts their learning performance (Emmer, 1984; Stavnes, 2014). It has also been documented that noise has detrimental effects on pupil’s cognitive performance, for example their language and reading development (e.g. Emmer, 1984; Shield & Dockrell, 2003; Woolner & Hall, 2010; Stavnes, 2014; Sala & Rantala, 2016). These findings, which are mostly attained by means of experimental and observational studies applied either in a laboratory or field setting, are relatively consistent and indicate that noisy conditions are a cause for annoyance and distraction. Noise is in essence unwanted sound, though it depends upon the listener and circumstances whether sounds are considered noise (Clausen et al., 2017). A study of the perceived quality of the indoor climate in Denmark’s public-school reports that about a third of its pupils’ experience ‘every day’ or ‘almost every day’ problems with noise in their learning environments, and about a fifth report having difficulties to concentrate at school because of that

Learning Spaces and Pupil Behaviour

2.3

p. 44

(Villumsen & Møldrup, 2013). These findings may be further explained by another study reporting that the measured sound levels in Danish classrooms frequently rise above recommended limits (Søndergaard et al., 2014; Clausen et al., 2017; Fangel & Andersen, 2017). Measured sound levels in occupied indoor spaces typically include two type of sound groups: (1) environmental or background sounds and (2) pupil-made sounds.

Learning Spaces and Pupil Behaviour

(1) Environmental or background sounds. All learning environments deal with an accumulation of environmental, or background, sounds which may include external sounds such as from traffic, internal sounds (not by pupils), such as by the ventilation system or teaching appliances (projectors and smartboards), or sounds penetrating from other areas of the building. In principle, these environmental sounds are considered disruptive noise as it does not contribute to the learning. The higher the accumulation, the more disruptive. Importantly, these sounds cannot be directly controlled by the teacher. Often the designers of school buildings will make efforts to mitigate the impact of these sounds as much as possible through their design choices (see section 2.2.1). (2) Pupil-made sounds. The second group of sounds are those produced by the pupils themselves as they take part in their learning activities. Pupil sounds are often found the most significant contributor to noise experienced during class, and include both vocal sounds and activity sounds as pupils move around the classroom or move learning objects and furniture (Shield & Dockrell, 2003; Woolner & Hall, 2010; Sala & Rantala, 2016). Where the first group, environment or background sounds are generally found to be relatively stable, the level of pupil-made sounds may vary greatly depending on the task or activity at hand. However, in contrast to background noise, not all of these pupil-produced sounds are necessarily considered noise as this is context dependant. Some of the pupil-made sounds may even be imperative to the learning activity at hand. For example, during collaborative or group exercises where pupils and teacher discuss, explain or question out loud. But at other times, for example during activities that require pupil’s focussed attention or concentration on a task such as mathematics or reading, pupil-made sounds are commonly considered distractive noise. More broadly considered, noise is only one type of disturbance caused by pupils. In fact, disruptions may also occur in visual or physical format, for example in form of fidgetiness or wandering around. Regardless of the expression, any disturbance diverts pupils’ attention away from their learning activity at hand or averts a teacher from operating effectively in the learning space (Sala & Rantala, 2016). The next section outlines three type of behaviours commonly considered to disrupt pupil’s attention to their learning.

A review of associated literature revealed three types of behaviours that are commonly considered to inflict visual, audible (noise) or physical disturbance to pupils learning attention (Emmer, 1984; Houghton et al., 1988; Stavnes, 2014): •

Externalized expressions by pupils without being relevant or asked for. For example, shouting out loud but not directed at someone, sighing or general laughter. It may also include small, seated physical expressions such as fidgetiness, wobbling on a chair, tapping fingers on a desk, and other forms of restless behaviour.

•

Non-learning related forms of social interaction between pupils. For example, off-topic social talk, joking together, or seeking attention from a peer pupil located elsewhere in- or outside the learning space for example by waving or clapping hands.

•

Out-of-seat behaviour such as needlessly wandering around in the classroom. This includes physical actions that take the pupil away from one’s seat or placement, and that are not related to the learning activity or for reasons such as visiting the toilet or taking learning-related materials from a cupboard.

What these behaviours have in common is that they all interrupt pupil’s attention, which has been found to negatively impact learning performance outcomes. However, there is no conclusive way to argue that these behaviours always qualify as disruptive, because this is highly dependent on the context and setting it occurs in (Stavnes, 2014). For example, externalized expressions such as talking out loud may be considered acceptable ‘noise’ during group discussions, but is likely to be experienced disturbing when pupils need to individually focus on a mathematical exercise. Thus, no conclusive list of behaviours can be formulated that is consistently experienced as disruptive. But a general definition of what is understood as disruptive behaviour is feasible.

2.3.3

Definition of Disruptive Pupil Behaviour

Based on the beforementioned descriptions, the definition of disruptive pupil behaviour can be formulated as: Pupil behaviours considered disruptive are behaviours that cause interruption or diversion of one’s own and/or others’ attention away from the (learning) activity or task at hand. This study further adheres to this definition when discussing the concept of disruptive pupil behaviour.

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Three Types of Disruptive Behaviours

Learning Spaces and Pupil Behaviour

2.3.2

2.4

The Physical Environment and Pupil Behaviour

p. 46

This section outlines current knowledge about the relationship between the physical learning environment and behavioural outcomes in pupils and outlines how this knowledge validates the premise that this environment, as designed by architects, can act as a tool to affect pupils’ behaviour, and ultimately, herewith their learning performance.

2.4.1

The Physical Learning Environment Matters

Learning Spaces and Pupil Behaviour

Researchers in fields such as education research, sociology and psychology study pupils’ behaviour. The field of environmental psychology, an interdisciplinary field that can be understood as a sub-field of psychology, addresses in particular the behaviour of pupils in relation to their environment. Environmental psychologist Robert Gifford, the author of a leading publication in this field, reviews a selection of studies situated in educational environments, and based thereon provides a framework for understanding the person-environment relations therein, see Figure 2.5 (Gifford, 2014). In this framework Gifford proposes five factors that are at play in the learning environment: the pupils themselves, the school climate, and features of the physical learning setting. Interactions between these influence pupils’ attitude and behaviour, ultimately affecting the teaching and learning.

Figure 2.5 Gifford’s Framework depicting five related factors in the learning environment (2014, p303).

Behavioural scientist Rudolf Moos proposed a similar model to understand how the learning environment, or classroom climate as he refers to, is influenced by multiple factors (Moos, 1979). In his model Moos outlines five determinants and relationships between these that are together responsible for the classroom climate. Along with some organisational and human factors, Moos explicitly recognises the physical and architectural features of the environment as a significant factor (see Figure 2.6).

Figure 2.6 Moos’s Model of the determinants of the classroom climate (1979).

What the models by Gifford and Moos share is that both recognise pupil’s learning is influenced by a complex process of contextsensitive interactions, meaning moderated by the situational, social and instructional context of where the learning takes place, and that the physical learning environment is one of these influential factors. However, both stipulate the environment itself usually does not affect the teaching and learning directly, but can facilitate or hinder the effectiveness thereof. Effective learning may thus take place best there where the physical learning setting has been considered similarly mindful as the curriculum, pupils, teachers’ abilities, and other teaching aids. Or in other words, the physical context matters to create optimum learning conditions.

2.4.2

Behavioural Implications Associated with the Physical Learning Environment

A comprehensive review of studies reporting on behavioural implications associated with (features of) the physical learning environment has already been conducted by Higgins et al. (2005). The authors of this review collected over 200 references, mostly published in journals from the UK, the US and Europe dating back to the 1960s. They organised the behavioural implications discussed in these references into five categories: (1) attainment, (2) engagement, (3) mood and motivation, (4) wellbeing and health, and (5) attendance. These are further described as following:

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The Moos model displays unidirectional arrows for reasons of simplification, but in the accompanying text Moos articulates various bidirectional relations between these factors. Herewith he suggests that positive choices or changes selected by the teachers and pupils or in the environment tend to cause further positive changes in a ‘virtuous cycle’, whereas negative ones might cause a vicious cycle of decline.

(1) Attainment. These studies look for measurable change in pupils’ academic achievements, either cognitive or task performance. This is typically measured by standardised tests or exams, or monitored and assessed by teacher observation. p. 48

(2) Engagement. These studies typically look for observable changes in pupils’ levels of attention. To collect such data, researchers typically interview pupils and teachers and/or conduct observational studies looking for signs of interrupted concentration by monitoring change in pupils’ on-and-off-task behaviours, distracted or disruptive behaviors, and social behaviours. These studies often take place directly in the field, or by help of video recordings thereof. (5) Mood and Motivation. These studies look for changes in selfesteem for teachers and pupils or changed levels of academic self-concept. The also look for emotional responses like surprise, excitement, confusion, agitation, fear or boredom. Typically, these studies apply research methods as self-report surveys, and open or closed questionnaires to collect their data.

Learning Spaces and Pupil Behaviour

(6) Wellbeing and Health. These studies look for changes in the physical self or impacts that relate to (dis)comfort. These studies commonly apply methods as self-report surveys, and open or closed questionnaires to collect data. (7) Attendance. These studies look for fewer or more instances of lateness or absenteeism by pupils. This data is often drawn from school records and absentees’ lists. These five categories of behavioural implications are measurable and can be considered either quantitative or qualitative research variables. A critical observation towards Higginswork however is that most of the studies reviewed focussed predominantly on assessing implications of the environment by evaluating change in pupil’s attainment, and to a lesser extent, attendance. This is not surprising as attainment, also referred to as academic performance, and attendance are typically quantitative measurements, and therefore can act as objective assessors of change in pupils that can be applied across different school contexts and generalize findings. But what these studies do not reveal much about, is the ‘how’ or ‘why’ pupils’ attainment or attendance was affected. Or in other words, what underlying mechanism(s) were responsible for the change. These mechanisms are more closely represented by the other three behavioural implications referenced, namely pupil’s engagement, mood and motivation, and health and wellbeing. The diagram in Figure 2.7 represents an interpretation of how these two categories of behavioural implications may be related.

underlying behavioural implications

output

Engagement Attainment Learning Environment

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input

Mood & Motivation Attendance Well-being & Health

The input variable in the diagram is (a feature) the physical learning environment. The output variables are the five behavioural changes that can be incited by a change or certain condition of the input variable. These output variables can be split in two categories: (1) the underlying changes in pupil’s engagement, mood and motivation, and health and wellbeing; and (2) the subsequent changes brought about in pupil’s attainment and attendance. The three underlying behavioural implications, engagement, mood and motivation, and health and wellbeing, appear to be relatively difficult or challenging to study. One reason could be that these are variables typically more qualitative in nature. They also are more context dependant and can be influenced by many more factors than solely the environmental (feature) of interest (Higgins et al., 2005). But to design constructive learning environments that can also be effectively managed, it is critical for the designers of school environments to understand these underlying relations. This study’s interest is to investigate if (a feature of) the physical learning environment can reduce the occurrence of disruptive pupil behaviours to ultimately better their learning performance. Following Higgins’ categorization, this would entail exploring change in pupil’s engagement and/or mood and motivation brought about by an environmental feature. Changes in either of these two variables may ultimately influence pupil’s attainment. The remaining two variables, well-being and health, and attendance are not directly of interest as these are not related to affect disruptive behaviour. Figure 2.8 provides an illustration of the three behavioural implications of interest in this study.

2.4.3

Three Categories of Environmental Features

This section outlines what features of the learning environment already have been found capable of inflicting change in pupils’ behaviour, mood and performance. Studies by Higgins et al. (2005) and Barrett et al. (2015) have informed this exercise in particular:

Learning Spaces and Pupil Behaviour

Figure 2.7 Diagram of the five environment’s effects on pupils (Higgins et al., 2005).

input

underlying behavioural implications

output

p. 50

Engagement Attainment Learning Environment

Mood & Motivation Attendance Well-being & Health

Figure 2.8 Diagram of the specific environment’s effects of interest for this study highlighted.

Learning Spaces and Pupil Behaviour

•

Higgins et al. (2005) defines two groups of features. Firstly, the four indoor climate variables light, sound, temperature and air quality, and secondly, three room-design features colour, layout and scale.

•

Barrett et al. (2015) documented the impact of six environmental features: the indoor climate variables, space density, room scale, flexibility to re-arrange furniture setup, colour applications and openness/ privacy balance.

Based on these two studies, supplemented by few other studies separately referenced in the text, the environmental features that bring about behavioural implications documented to date are categorized into three groups: 1. Indoor climate features, 2. Temporal features, 3. Architectural features. These three groups are presented in hierarchical order, indicating their relative capacity for impact. The variables in the first category, indoor climate, are found to have the most profound impact on pupils’ learning and wellbeing, while the impact found for variables in the second and third categories are weaker. For each category examples are provided how architects responded to the respective findings in their school designs to date.

Indoor Climate Features The set of environmental features found to have the most evident impact on pupils are those referred to as the indoor climate variables – alias the light, sound, temperature and air quality conditions in the learning environment. Researchers exploring their relevance, documented that pupils in learning spaces with

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abundant natural light without causing for visual or thermal discomfort, with a high circulation of fresh air, comfortable room temperature, and with good acoustic properties present higher academic performance and increased well-being in general (e.g. Küller & Lindsten, 1992; Heschong, 1999; Wargocki & Wyon, 2007; Tanner, 2009; Shaughnessy et al., 2012; Cheryan et al., 2014; Marchand et al., 2015).

Temporal Features The category of temporal features refers to elements of the learning environment that can be easily changed or adapted by the teachers and pupils. Most notably, the type and arrangement of seating and desks. Different setups hereof have for example been found to influence the form and level of interactions between pupils. Furniture arranged in small groups was found to encourage collaboration, while single seats or row setups were found to direct a pupil’s attention towards an individual task. The application of desk dividers or partition screens to separate pupils more actively from each other was found to further improve one’s concentration. Other examples are more of decorative nature. Putting pupils’ works or achievements on display in the learning space has been found to act as a motivator and provoke pro-learning behaviour. The choice of dominant colours in the learning space was found to affect pupils’ behaviour and mood. Significant use of the colour red for instance was found to rouse agitation, while blue was found to ease or unwind pupil’s mood (e.g. Gifford, 2007; Simonsen et al., 2008; Tanner, 2009; Cheryan et al, 2014). Most of these are examples (except permanent colouring of walls or furniture) of environmental features that teachers can relatively easily change or re-arrange in their learning space to coordinate with the activity, curricular theme or season at hand. These features were found to affect predominantly pupils’ state-of-mind and (social) behaviours and are believed to influence pupils’ overall learning performance.

Learning Spaces and Pupil Behaviour

This knowledge inspired architects to explore optimizing building components responsible for attaining and maintaining a supportive indoor climate. Examples hereof are large window surfaces to increase natural light intake combined with deployable shading to prevent for glare or excessive heat, as both a cause for discomfort; a ventilation solution that allows adjusting fresh air circulation, for example to revive sleepy pupils or to eliminate unpleasant smells quickly; or the application of acoustic wall decorations and soft movable furniture to help mitigate the impact of noise. Solutions as these, provided by the architect but managed by the occupant, allow to actively influence pupils’ comfort, behaviour and ultimately, learning performance.

Architectural Features

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The architectural features of the learning environment concern permanent elements, incorporated in the design of a learning space by the architect, and were found to affect pupils’ behaviour more indirectly. Examples of architectural choices that could affect behaviour are open versus closed spaces or fixed versus deployable separation walls. While fixed boundaries limit the teacher’s ability to rearrange furniture, movable boundaries allow a space to open up for more arrangement opportunities. And expanding and connecting spaces allows greater freedom to rearrange pupils throughout the learning space. Similarly, the amount of space the architects allocate per pupil defines the range for teachers to move pupils apart. Less space per pupil means less opportunity to vary seating arrangements or levels of privacy (e.g. Gifford, 2007; Simonsen et al., 2008; Tanner, 2009).

Learning Spaces and Pupil Behaviour

Choices towards architectural features as described cannot be (easily) adapted when a building is finished and generally define a teacher’s allowances permanently. Herewith these affect pupils learning long-term.

The Impact of Adequate versus Inadequate Features Higgins et al. (2005) concluded their review with the notion that the effects of environmental features on pupils’ learning appear most evident when it concerns inadequate environmental features such as loud noise, poor lighting and crowdedness due to lack of space, while positive effects appeared much harder to distil per feature with some degree of unanimity. Higgins provides two reasons for this apparent limitation. The first reason, he states, is that most study’s conclusions tend to be rooted in a particular context. Specific findings from one environment only are difficult to translate, or generalize, to others (see also section 2.4.1). The second reason is that most of the reviewed studies become rather inconclusive when the overall design of the studied learning environment reaches a reasonable standard of quality. If there is not a single environmental factor that performs very poorly, the complexity of environmental interactions comes into play as outlined in section 2.4.1, obscuring cause and effect relations of the various factors. Nevertheless, researchers exploring person-environment relationships in educational settings have started to uncover how pupils’ behaviour and learning is modulated by the physical environment, as designed by architects and treated by teachers. Advancing our knowledge about these person-environment relations provides a prospect for those designers proactively seeking to help teachers reduce disruptive behaviours from occurring and improve quietness during class with help of features in their learning environments.

The 2014 reform of the Folkeskole has an impact on how school buildings are to be used, and thus designed. This impact has been unpacked in the first section based on three focus points of the reform relevant for architects: (point 1) the need for a more varied school day, (point 3) the need to alternate educational activities with more movement, and (point 13) the need to reduce disturbances including noise during class so that pupils maintain a state of concentration. These demands however imply an inherent friction between the need for more varied activities and the need for a calmer learning environment that is devoid of disturbances, which appear to be largely caused by pupils themselves. This friction in particular has impacted the teachers’ management load notably. To assist teachers in this challenge, the goal for this research became to investigate how architects can capacitate teachers to effectively manage their environments in the post-reform Folkeskole. A field study has been undertaken to uncover the practical implementation of these reform points thus far in three new and refurbished school buildings. From these observations, it appeared architects integrated several solutions to cater for point 1 and 3, but seemingly dealt with point 13 only by mitigating the impact of noise through sound absorbing measures. Addressing the dominant cause of noise, the pupils themselves, appears left out in their approach thus far. The same accounts for other pupil behaviours identified to cause for distractions. Traditionally, managing pupil behaviours is done through classroom management techniques, which predominantly rely on interactions between teachers and pupils. However, if the environment were to assist in managing disruptive behaviours, calmness may be achieved more effectively. Literature was consulted on what is already known about these occupant-environment relationships. It appears some environmental features, and particularly inadequate ones, have been found capable to influence pupils in various ways, for example their performance, engagement, behaviour, mood, motivation and health. The type of features found to have such capacity most evidently are the indoor climate variables light, sound, temperature and air quality. Supported by these findings, this study looks to investigate whether the physical learning environment, or a feature thereof, could become one of the tools at the disposal of teachers to manage disruptive pupil behaviours. Lesser occurrences of disturbances will improve the quality of the learning environment in general, and in particular support pupils to maintain their attention on their learning tasks – ultimately benefitting their learning performance. The following chapter argues that one of the features of the learning environment capable to act as such a tool, is the artificial lighting.

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Summary

Learning Spaces and Pupil Behaviour

2.5

p. 54

Artificial Light and Pupil Behaviour

This chapter provides a review of the current body of knowledge about how (artificial) light is found to influence occupants, and through what workings. These findings substantiate the premise that the artificial lighting can be considered one of the learning environment’s features available to influence pupils’ behavior. The preceding chapter already referenced an apparent link between the light conditions in the learning space and pupils’ cognitive performance, particularly when this condition is assessed to be inadequate. This chapter details further what is known about the relationship between (artificial) light and (pupil) behaviour.

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ARTIFICIAL LIGHT AND PUPIL BEHAVIOUR

Figure 3.1 illustrates the two topic areas, artificial lighting and pupil (or occupant) behaviour, discussed within the context of the learning environment in general (thus not specifically for the Folkeskole).

Artificial Light and Pupil Behaviour

Figure 3.1 Schematic diagram of the research’s theoretical framework.

This chapter is structured into four sections. Section 3.1 introduces the field of lighting research, where the visual and non-visual effects of (artificial) light on people is explored. Section 3.2 presents the theoretical framework that underpins this research. This framework is informed by three theoretical models of Veitch (2001), Boyce (2014), and Higgins et al. (2005). Section 3.3 presents the current body of knowledge about the effects of artificial light on pupil behaviour and discusses three characteristics of artificial lighting documented responsible hereof. Section 3.4 provides a summary of the chapter, and makes the argument to explore the potency of the artificial light pattern, one of these characteristics, to incite the desired behavioural change in pupils this study aims for.

3.1

Light and Human Behaviour

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The overall purpose of light in buildings is to service people’s visual and non-visual needs. Central herein is the need for visibility, because it is the detection and organization of light patterns (alias variations in lighter and darker areas) that allows an observer to analyse and evaluate their environment (IESNA, 2011). Historically, lighting-related research focused predominantly on understanding these visibility needs to ensure adult workers had enough light to see fine details (Boyce, 2014). Hereto perceptual processes have been extensively analysed by studying effects on our visual performance by systematically varying the properties of a light stimulus along one or more of its physical dimensions. Knowledge derived from this type of research has informed our fundamental understanding of the (adult) visual system in terms of visual appearance – what things look like, and visual performance – how well visual information can be processed (Boyce, 2014).

Artificial Light and Pupil Behaviour

More recently, lighting-related researchers have also been focussing on discovering other humans needs for light than sight. These studies explored a range of psychological and physiological effects of light, for example on our mood, motivation, perception, cognition, (social) interactions, well-being and health (Veitch, 20o1; Boyce, 2014; de Kort & Veitch, 2014). These effects may come about through different mechanisms that, in essence, are theoretical constructs, but useful to organize and interpret empirical evidence (Veitch 20o1). Knowledge derived from both strands of research that is relevant for the contextual setting of this study and the question it looks to answer, is discussed in the next two sections.

3.2

A Theoretical Framework

The works of two lighting-related researchers bear specific relevance for this study. The first, Jennifer Veitch (2001), authored a framework that provides an overview of five effects of light on human behaviour. The second, Peter Boyce (2014), drafted a framework that outlines three systematically documented pathways by which these effects occur. This section discusses these two frameworks.

3.2.1

Five Behavioural Outcomes affected by Light

Since the 1990’s Jennifer Veitch, a prominent lighting researcher based at the National Research Council of Canada, and her team have extensively investigated how light, both natural and artificial light, impacts human behaviour, predominantly in work or office environments. Task performance is a particular effect they regularly used to assess the impact of lighting conditions on people, but other behavioural effects have been studied too.

input

…effect on…

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Based on their findings, Veitch defined five behavioural effects in response to luminous conditions: (1) visual performance, (2) mood, (3) appraisal, (4) social interactions, and (5) health and well-being (Veitch, 2001). These effects, which occur concurrently, co-define our overall behaviour. Figure 3.2 provides an illustrative diagram. output

Visual Performance

Mood

Light ing Co nd it io n

Appraisal

H u m a n B e ha vio u r

Social Interactions

Well-being & Health

Figure 3.2 Illustrative diagram of Veitch’s five behavioral implications of light (2001)

(1) Visual performance is greatly influenced by how well the lighting supports one’s visual needs within a given spatial context. How well one can see has been found to directly influence one’s ability to perform a task or activity, or task performance. The workings of the adult visual system and how visual information is processed has been significantly researched. Human visual performance is therefore relatively well understood. (2) Mood refers to the effect light has on one’s emotional state of mind. Different lighting conditions produce different interpretations (impressions) of an environment, which may induce different mood states such as happiness, alertness, satisfaction, relaxation, and motivation. Light can also compromise mood when causing for visual discomfort for example. Different mood states have been documented to affect task performance and other behavioural outcomes. (3) Appraisal, or aesthetic judgements about the environment, make how well the lighting reveals architectural or spatial characteristics thereof so that the resulting visual experience conveys meaning to the observer. Appraisals contribute to the observer’s understanding of the space. This includes for example whether the lighting creates sufficient visual hierarchy, for instance by reinforcing architectural rhythms or applying a pattern of light in coherence with architectural form. Environmental appraisals differ from our emotional response as described in the previous point, as it relates to our inherent need to make sense of what we see. But appraisals do ultimately affect ones’ mood state, and herewith behavioural outcomes.

Artificial Light and Pupil Behaviour

Veitch describes these behavioural outcomes as following (2001):

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(4) Social interactions between observers are affected by the lighting condition they take place in. Light has been found capable to elicit pro-social behaviour (Steidle et al., 2013) and improve collaborations between observers (Baron et al., 1992). But also, to compromise social interactions by provoking negative behaviours such as greater dishonesty (Zhong et al., 2010). Of particular importance for these social effects appears to be how light is rendering human faces. Facial appearance influences social interactions, and facial recognition impacts feelings of safety (Boyce, 2014). The overall brightness appearance of a space is another factor, as it informs the observer about the level of intimacy versus openness of a space.

Artificial Light and Pupil Behaviour

(5) Health and well-being are found particularly affected by (severely) uncomfortable lighting. The health effects of prolonged visual discomfort include headaches and eye strain, and sudden changes in brightness can give rise to acute alertness stress. Light has also been found to affect human circadian photoreception, which drives physiological rhythms such as the sleep-wake rhythm, core body temperature, and hormone secretion. Misalignment has been found to significantly affect one’s general well-being. These health and well-being complications are found to negatively impact task performance and other behavioural outcomes. These behavioural effects, which occur concurrently, may come about through several parallel mechanisms which Veitch divides into two broad categories (Veitch, 2001): psychobiological processes such as visibility, arousal and photobiology, and psychological processes such as attention, appraisal, and affect – also referred to as our emotional responses to light. For this study, which seeks to uncover if the artificial lighting in the learning environment can encourage behavioural change in pupils causing less disruptions during class and improve pupils’ attention to their learning (task), the psychological processes are of particular interest. Another framework, developed by Peter Boyce, is discussed in the following section, outlines these underlying mechanisms believed to produce behavioural effects in response to luminous conditions, in greater detail. One pathway, the perceptual pathway, associates with Veitch’s psychological processes.

3.2.2

The Pathways Through Which Light Works

Peter Boyce, also a prominent lighting researcher, developed a conceptual framework portraying three pathways believed to underlie the lighting-behaviour relationship: (a) the visual pathway; (b) the perceptual pathway, and (b) the circadian timing pathway. These are parallel processes that occur simultaneously when a light stimulus is detected by the human eye. A diagram of his original framework is shown in Figure 3.3 (Boyce, 2014, p.116), with the three pathways highlighted in red (visual pathway), green

Artificial Light and Pupil Behaviour

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(perceptual pathway) and blue (circadian timing pathway). The five behaviour effects are also highlighted. Although each effect is positioned inside one pathway, each effect is typically influenced by other pathways too, and often interact (see arrows).

Figure 3.3 Conceptual framework of the three pathways through which light works

(Boyce, 2014, p. 116)

These three pathways can be added to the illustrative diagram shown in Figure 3.2, as these are the mechanisms that bring about the five behavioural effects described by Veitch. See Figure 3.4 *. input

…working through…

…effect on…

output

Visual Performance

Light ing Co nd it io n

Visual Pathway

Mood

Perceptual Pathway

Appraisal

Circadian Pathway

Social Interactions

H u m a n B e ha vio u r

Well-being & Health

Figure 3.4 Illustrative diagram of Veitch’s five effects of light (2001) and Boyce’s three pathways (2014) * For illustrative purposes the diagram presents the pathways and effects as successive steps. However, these work simultaneously.

The Visual Pathway

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The visual pathway provides the most direct and obvious path for the effect of light on human performance, namely via one’s visual performance (highlighted in red in Figure 4.1). Visual performance is found to be directly influenced by how well the lighting supports the observer’s visual needs within a given spatial and contextual circumstance. This in turn has been found to influence one’s ability to perform a task or activity, also referred to as task performance. When the lighting conditions fall outside the comfortable range, task performance is found to be compromised (Boyce, 2014).

Artificial Light and Pupil Behaviour

The visual pathway has been most researched thus far (de Kort & Veitch, 2014), and typically explored the effect of a luminous condition on an observers’ perception of lightness, brightness and colour appearance in order to determine their thresholds for visual (dis)comfort, and their findings informed our understanding of visual performance in adult populations (Boyce, 2014). This is for example illustrated by the Relative Visual Performance (RPV) model which defines the luminous conditions under which we are able to see well and comfortably (Rea, 1986). Visual performance affects our task performance but is not the only component. Boyce’s framework refers to two other components that impact task performance, namely cognitive performance – the process of how sensory stimuli are interpreted, and appropriate action is decided, and motor performance – the process by which these stimuli are manipulated to extract information and the actions decided upon are carried out. Visual, cognitive and motor performance are thus shown to collectively influence task performance. Herewith Boyce underscores that light, or a lighting condition, is capable of affecting human performance, but that the outcome thereof is moderated by others influences too. Knowledge derived from the studies referenced and others have particularly informed building lighting regulations, for example EN 12464-1:2011, for architects to ensure the built environment provide occupants with the minimum conditions that serve their visibility needs comfortably. Because these regulations also apply to educational buildings, it may be expected that learning spaces designed according to these regulations provide for adequate visibility, and offer suitable control solutions, for example sun shading and dimming controls, to avert over- or under-exposure or visual discomfort for pupils and teachers. Considering the ambition of this research is to encourage behavioural change in pupils, the visual pathway as described does not offer direct opportunity to inflict such change unless pupil’s visual needs are not well cared for. As a result, while exploring how artificial lighting may act as a behavioural tool, pupil’s ability to see should not be compromised to avoid counterproductive outcomes.

The perceptual system, according to Boyce, takes over once the retinal image at the eye has been processed by the visual system (highlighted in green in Figure 4.1). It deals specifically with the psychological impact of experiencing light, or a lit environment. The perceptual system has been found to influence human performance and other behaviours by inciting a mood change brought about via three routes: (i) visual (dis)comfort, (ii) visual impression, and (iii) visual experience. The following descriptions of these routes are summarized interpretations of Boyce’s work (2014):

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The Perceptual Pathway

(ii) When the visual system is triggered by the lit environment, the observer not only assesses its visual clarity and comfort, he/she also interpret the visual impression itself. A scene may for example be interpreted as calm, lively or intimate. These kinds of interpretations produce an emotional response which subsequently induces certain mood states that, in turn, has been found to amongst others affect our cognitive performance, concentration, and social behaviour. (iii) When our visual system is triggered as described above, the observer also makes an appraisal judgement thereof (see also point 3 of Veitch’s model, section 3.2.1). Appraisal commonly deals with how well the lighting reveals architectural or spatial characteristics so that the resulting visual experience conveys meaning to the observer. When this appraisal eventually is compared to one’s preferred condition, it may change one’s mood, and subsequently affect cognitive performance, concentration, and social behaviour (Veitch & Newsham, 1996). In theory, the perceptual pathway thus substantiates the notion that artificial lighting can incite behavioural change in pupils by deliberately inflicting a mood change. But to incite such change, the artificial lighting has to significantly change pupil’s visual comfort, impression of and/or experience with the learning environment. However, the literature around this pathway also indicates that these psychological, or mood, effects have not yet been much researched, and the few that did, describe their findings as relatively weak. Boyce credits the limited success of this area of research thus far to five possible reasons (Boyce, 2014):

Artificial Light and Pupil Behaviour

(i) The simplest output of the perceptual system is a sense of visual discomfort, which may negatively change the observer's mood, particularly if the effect is prolonged. If the visual scene is severely uncomfortable for a prolonged amount of time, it may even cause health effects which negatively impact the observer’s functioning. Poor visual comfort thus causes agitation and ultimately reduced performance. These are undesired outcomes and to be avoided.

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1. The key reason appears to be that these findings about mood are considered context-dependant. Meaning, they may be true for the context they are found in, but they do not necessarily translate to other circumstances. Generalizations about the psychological ‘mood’ effects of light are thus seemingly difficult to make. Different conditions in the same context need to be studied. For example, the effect of light on pupils’ mood in different schools in order to arrive at general suggestions for learning environments. 2. The fact that mood and emotions, in the real-world context, are influenced by many more factors than solely lighting. Very likely, within this web of multiple factors, lighting may only play a relatively minor role, which makes potential findings difficult to detangle from other factors at play. To address this complexity, one needs to identify all potential intervening variables and monitor these alongside the variables of interest.

Artificial Light and Pupil Behaviour

3. The limited range and variety of the lighting conditions that have been tested so far. The light conditions that have been tested are relatively conventional, as most of these studies took reference from workplace environments, and the artificial lighting designs studied were aligned with conformist applications for this contextual setting—compliant with the relevant lighting recommendations at the time, such as the horizonal illuminance levels to be maintained across the working pane with a minimum uniformity ratio. This means that no unconventional lighting designs were explored that would fall outside the recommendations and that could have potentially yielded stronger evidence. This implies that the effects of unconventional lighting designs are to be studied too. 4. The exposure time of observers to the tested lighting conditions most often has been relatively limited, often only one day or just a few hours. It may very well be that these observers simply ignored a disliked condition for that amount of time. But that does not exclude the option that the effect may become more impactful if the condition were experienced for a longer duration. Researching mood effects over a prolonged amount of time may thus reveal stronger findings. 5. The majority of these studies were placed in abstracted settings, typically in form of simulated lab experiments which do not fully represent the context of a real-world environment. Where visual performance may be studied independent of context as it investigates a direct relationship between an illumination condition and the observer, mood and aesthetic appraisals rely heavily on the context these occur in. They are outcomes of a triangular relation between the light, the environment and an observer. Studying ‘mood’ impact of light should therefore ideally take place in real-life environments

Exploring psychological effects of light on pupil behaviour should thus ideally take place in a real-life environment, with (also) nontypical lighting conditions that do not compromise pupils’ visual comfort and performance and allow for a longer duration of exposure. One should also attempt to identify and monitor other factors in the environment that may also affect pupil’s mood.

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instead of simplified or abstracted environments. The latter may not bring forth significant measurable change in emotions, tough real-life environments does allow to uncover genuine implications.

The circadian timing system is the third route through which light has been documented to affect human performance, behaviour and well-being in general. This system responds to light in a manner that is fully or partially separated from the visual system and produces non-image forming, physiological effects. For example, short-wavelength (blue-enriched) light is found effective in regulating the human biological clock. Exposure to light with a significant high blue content was found to positively influence pupil’s alertness and cognitive performance (Keis et al., 2014). While pupil’s natural sleep and wake rhythm was found disrupted by exposure to light lacking blue content, causing for delayed sleep and lower performance levels (Figueiro & Rea, 2010). Although these findings are insightful and informative towards creating learning environments serving pupils wellbeing holistically, meaning visually, emotionally and physiologically, the literature reveals the workings of the circadian pathway are little understood. Research about the workings of circadian pathway has only started to emerge since about a decade ago, yet much is to be uncovered. Within the context of this study the circadian pathway is considered an unsuitable route to explore as it inherently concerns non-image forming effects of light. Because this research is placed within architectural practice, interest goes out to investigate visual implications of (artificial) light as these are outcomes directly moderated by the architect and building users. Together these manage the placement and presence of light, and its interaction with the surrounding environment.

3.2.3

Three Behavioural Implications by the Physical Environment

Higgins et al. (2005) outlines five behavioural implications that are specifically associated with (features of) the physical learning environment. These concern measurable effects on pupil’s attainment, engagement, mood and motivation, health and wellbeing, and attendance. Three of these implications bear specific relevance to this research:

Artificial Light and Pupil Behaviour

The Circadian Pathway

Pupils’ engagement with their learning task. Engagement in this context refers to typical behaviours such on-and-off-task behaviours, distracted or disruptive behaviors, and certain forms of social behaviours, that indicate whether a pupil is engaged with, or focussing on, their learning (task).

•

Pupil’s mood and motivation, which represents any emotional change in, or responses by, pupils brought about by the environment.

•

Pupil’s attainment, also referred to as academic performance. Both changes in pupils’ engagement and mood are considered underlying behavioural implications affecting attainment.

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•

Higgins’ framework is discussed in detail in section 2.4.2. and Figure 2.8. provides a diagrammatic representation thereof.

3.2.4

Conceptual Theoretical Framework

Artificial Light and Pupil Behaviour

This study investigates how the artificial light in the learning environment can help reduce disruptive pupil behaviours and herewith improve pupil’s attention to their learning. The theoretical framework to underpin this work has been informed by elements from the discussed frameworks by Veitch’s (Figure 3.2), Boyce (Figure 3.4) and Higgins (Figure 2.8). Combining certain elements allowed to define which behavioural implications are of interest for this study, and through what mechanism these occur. In essence, the conceptual framework for this research is rooted in the understanding that different lighting conditions produce different interpretations of and experiences with our environment via the perceptual pathway. These in turn cause different emotional responses, or mood states, for example change in the observer’s alertness, motivation or relaxation. In learning environments these changes have been found to affect i.e. pupil’s engagement, (social) behaviour, and ultimately, their learning performance (e.g. Veitch, 2001; Boyce, 2014, de Kort & Veitch, 2014). Behavioural change in pupils may thus in theory be incited by significantly changing the lit appearance of the learning environment. An illustrative diagram of the subsequent conceptual framework through which these implications (or route) of light work is shown in Figure 3.6. The lit appearance of the (learning) environment is orchestrated by the architect, who defines the expression of the physical context itself and specifies the (artificial) light components therein; and the end-users (teachers and pupils) who control the settings of these lighting components. The challenge therefore is to investigate how (artificial) light can be applied so that the appearance of the learning environment incites a mood that discourages disruptive pupil behaviours, and encourages pupils engagement with their learning. The process of orchestrating the lit appearance of a (learning) space is further discussed Chapter 4.

…working through…

…underlying behavioural implications …

output

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input

Engagement Visual Pathway Mood & Motivation Lighting Condition

Attainment

Perceptual Pathway Well-being & Health Circadian Pathway Attendance

Figure 3.6 Illustrative diagram of the Conceptual Framework underpinning this research

The proposed framework, which is grounded in the perceptual pathway, serves this research’s particular ambition to explore whether artificial lighting can incite certain behavioural change in pupils. However, it is important to state that this framework addresses only part of the entire process that takes place when observers are exposed to a luminous environment. Besides processing ‘light’ information via the perceptual pathway, this information will also pass through the visual and circadian pathways. The outcomes of these pathways cannot be simply ignored. For example, if a lighting condition compromises pupils’ visual needs, subsequent negative implications via the visual pathway could outweigh any beneficial effects the same condition brings about via the perceptual pathway. When investigating the impact of a lighting condition on human functioning, one should thus consider the entire (currently known) processing structure of visual information, and not only the outcome of one pathway.

3.3

Literature Review: Artificial Light in Learning Environments

This section provides an overview of the current body of knowledge about how artificial light in the learning environment has been found to incite behavioural change in pupils. Initially researches focussed on understanding visibility needs to ensure adequate and comfortable sight (Boyce, 2014; de Kort & Veitch, 2014). These needs are relatively well documented and understood by now, and informed lighting recommendations provided in most school building regulations. Eventually the research community directed its attention also towards understanding other implications of light in learning environments. Most notably, Rita and Kenneth Dunn, who pioneered research looking at the impact of the environment on pupils learning, identified that the lighting conditions herein

Artificial Light and Pupil Behaviour

Critical Note

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play an important role, and argued that light impacts pupils' learning beyond solely via visibility and visual comfort (Dunn et al., 1978, 1985). They insisted that the light condition in a school environment is to be considered an active element of the total educational environment, and not solely an attribute to make tasks, people and the surroundings comfortably visible. The Dunn’s herewith set-off a path of discovery in what ways light in learning environments influences learning outcomes, either through the visual, perceptual or circadian pathways (see section 3.2.2).

Generalization Issues Even tough researchers’ efforts to reveal non-sight implications of light in learning environments, the literature review revealed that convincing empirical evidence hereto still remains limited. It appears that findings from these studies are more difficult to generalize as they often differ in (Boyce, 2014):

Artificial Light and Pupil Behaviour

•

research methodology – for example field studies versus lab experiments.

•

contextual situation – for example the type of space studied such as a typical classroom versus an open plan learning space.

•

typical (architectural) features of that space – for example the furniture layout, room dimensions, and decorations.

•

the type of lighting system – for example the type of light source, colour, quantity, and distribution of the light.

•

the population under review – for example school children, adolescents or adults.

•

evaluations measures – for example qualitative versus quantitative measurements.

Because of these differences in the research context, setup, and methods, findings from of one study are typically only considered true for the specific context they emerged from, or at most, only relevant for environments that are significantly alike. The issue of generalisation represents one of the major challenges for researchers exploring emotional and behavioural effects of light (Boyce, 2014). To arrive at acceptable generalisations that in turn can be used to develop lighting recommendations for a particular context of interest, for example learning environments, typically requires a substantial body of research. This is particularly true for research looking to untangle effects of light brought about via the perceptive pathway, dealing with attention and mood responses incited by light as described in section 3.1.3. But the literature review conducted for this study, indicates this sub-area of research is steadily growing. Findings thereof are presented in this chapter.

Artificial light on the other hand is a source of light fully controllable. Building designers, typically the electrical engineer, specify an electrical lighting system, while the end-user (occupant) decides how and when to use it. Artificial lighting therefore offers greater opportunity to act as a tool to encourage the desired behavioural change in pupils, than natural light. Particularly so when architects and users act collaboratively. Hereto this section discusses findings exclusively from studies that investigated the implications of artificial light for pupils. This review thus covers a broad palette of implications of artificial light. Predominantly those brought about via the perceptual pathway, the pathway of interest for this study. But also touches upon some findings on implications via the visual and circadian pathways. Reason for reporting on these is that most of the studies reviewed address more than one effect. Their findings may be difficult to separate per effect.

Organization of the Literature Review The literature review itself is structured according to three key characteristics of artificial light in architectural space, and one combination thereof: (1) intensity, (2) colour, (3) intensity and colour, and (4) pattern. This structure allows to reveal what characteristic of the artificial lighting was responsible for documented effects. This provides insight into how artificial lighting in the learning environment may be manipulated to encourage a particular mood state or behavioural change in pupils. In addition, where most of the studies reviewed looked at effects on pupil populations as a whole, some studies differentiated their findings according to for example age or gender. These studies revealed that differences within a pupil population do exist. This affects the notion of what could be considered a ‘favourable’ lighting condition.

Artificial Light and Pupil Behaviour

First a distinction is made between natural and artificial light. The lighting conditions in learning environments are typically a combination of both. The importance of providing natural light in the learning environment has been emphasised by a range of studies (see appendix X). These studies predominantly highlight health benefits, such as circadian synchronization that supports our day and night patterns, or they stipulate the meaningfulness of its natural variation and the sense of place and time that it provides for occupant well-being (e.g. Benya, 2001, Heschong, 1999, 2003; Barrett et al., 2015). A critical limitation of natural light, however, is that it cannot be controlled. It is geographically specific, only available between sunrise and sunset, weather permitting, and it is not modifiable on demand. It may be blocked or filtered by means of blinds or curtains, but other than that, it manifests as it does. It therefore does not offer a reliable, on-demand opportunity to act as a tool for teachers to modify pupil behaviour as aspired by this study, beyond regulating its presence in the learning space.

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Natural versus Artificial Light

3.3.1

Light Intensity

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Illuminance is the measure of the intensity of light that falls onto or passes through a surface as perceived by the human eye (IESNA, 2011). Illuminance is expressed in lux; which ranges between 0 lux (perfect darkness) to 100.000+ lux (direct sunlight). Typically, researchers interested in understanding the influence of light intensity on pupils, looked at what illuminance levels at working desks are ideal to perform visual tasks common in learning environments easily and comfortably. Initial research focused on understanding the direct effects of different illumination levels on the horizontal desk surface on pupils’ visual performance. Boyce (2014) writes that in general the more light reaches the eye, the smaller the details that can be perceived, and the easier it becomes to perform certain tasks. However, he noted that this improvement is only significant for relatively low light levels, which are typically exceeded in real-life indoor conditions. Boyce concluded that increases in quantity of light above a threshold level of around 50– 100 lux thus have negligible effect on visual performance for 18 to 65-year olds.

Artificial Light and Pupil Behaviour

Price (1980) looked at the effect of quantity of light on the visual performance of school aged children. He concluded that school aged children require similar minimum illumination to see fine print comfortably. But he also stated that ultimately each person's eye sensitivity develops slightly differently, influencing the level of light necessary for personal comfort. That need is biologically determined, and although it changes gradually with age, it appears to remain fairly constant during a three to five-year period among children typically 6 to 10 years old. This allows to study pupils from this age group with a relative degree of consistency. There is little research regarding minimum and maximum light levels requirements for classroom settings. Lōfberg et al. (1975) studied the impact of illuminance levels between 60, 250 and 1000 lux at horizontal desk level amongst other environmental variables for school children on task performance. One of their tasks was an addition test written on paper sheets with different contrasts. For that test there was indication that performance increased under higher illuminances. Lōfberg suggested that levels below 100 lux can be associated with decreased cognitive performance and academic performance. Other studies indicate that relatively high levels of illumination may also have a negative effect as they have been associated with glare issues. There is some evidence for visual discomfort at quantities above 1000 lux, and separate evidence for levels above 2500 lux in uniformly lit rooms (Rea, 1982, 1983; Smith & Rea,1980) Visual discomfort may affect visual performance negatively. These findings indicate that pupils are able to visually function adequately while exposed to a relatively large intensity range. However, light levels below 100 lux or above 1000 lux may negatively affect pupil’s performance.

The studies discussed thus far related illuminance levels to pupil performance outcomes. These studies looked at the effect of light via the visual pathway. Schreiber (1996) however attempted to relate mood effects to illuminance levels. Thus, exploring the perceptual pathway. They found that the group of young pupils studied became more relaxed and interested in learning activities when the overall brightness in the learning space was reduced. This finding suggests that light levels may influence pupils’ mood state. But because no other studies have been found that link illuminance levels directly to mood changes in pupils, Schreiber’s findings cannot be confirmed. There are studies that do investigate the relation between pupils’ mood state and light levels combined with certain colour settings. These are discussed in section 3.2.3.

Variation to Attend to Individual Needs and Preferences The studies referenced so far look at the impact of illuminance levels on a group of pupils as a whole, and typically suggest that illuminance levels between 100 to 1000 lux do not compromise their overall performance. However, it was also uncovered that within this range, individual differences do exist. McColl & Veitch (2001) for example pointed out that different preferences manifest for specific demographic sub-groups, or even individuals. When studies of whole classes or schools are done, they argue, large or adverse effects on a few learners may be obscured by the absence or reversed effects on the other learners. In the early 1980s Krimsky (1982) attempted to identify preferences of nine and ten-year olds for studying in either brightly or dimly lit areas. Those pupils who indicated a clear preference were tested for reading speed and accuracy in an extremely bright, and then extremely dim instructional setting. Results showed that those who * European standard EN 12464-1. (2011). Light and lighting - Part 1: Indoor workplaces.

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Lighting regulations are typically informed by these target ranges as described. For example, EN 12464-1 * recommends maintaining illuminance levels at the horizontal working plane in classrooms between 300 – 500 lux, which falls well within the recommended ranges by Lōfberg et al. (1975) and Rea (1982, 1983; Smith & Rea,1980). In real-life, however it appears these recommendations are not always adhered to. For example, Winterbottom & Wilkins (2009) measured mean averages well above this range. He examined a sample of ninety secondary classrooms across the UK and measured illuminance levels at desks level. Results showed that the average illuminance was more than 25% in excess of 500 lux in 88% of the classrooms. In 84% of classrooms illuminance measurements at certain areas exceeded the level at which visual comfort decreases. Winterbottom pointed at excessive natural and artificial light as causes. His work points out that variations in illuminance levels in actual classrooms may be rather large, despite these recommendations.

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preferred bright light performed statistically better when tested in brightly lit areas, and those who reported a preference for reading in dim light did equally as well when their preference was matched in a low-light environment. Both groups performed significantly less well when tested in mismatched conditions. No statistical differences were evident in reading speed and accuracy between students with learning style preferences for either bright or dim light. Similar findings emerged from the study by Dunn et al (1978, 1985) who too found that pupils who prefer brighter light perform better in bright light, and those pupils who prefer dim light perform better in dim light. Both groups performed significantly less well when tested in mismatched conditions.

Artificial Light and Pupil Behaviour

There may be underlying physiological reasons for these different preferences. Riding & Pugh (1987) for example found that students with short dark-interval thresholds (DIT, sensitivity to flicker) read more accurately in relatively brighter conditions, and students with a long DIT read more accurately in relatively dim light. These students were found to intuitively position themselves in a brightness condition matching their physiology. No other studies have been found to provide further clarity on such potential underlying mechanisms. Nevertheless, what the studies discussed do stipulate is that within the boundaries of the comfortable illuminance range, there typically is a degree of individual, or possibly demographic, variation in needs and preferences. In order to optimize individual visual performance in a learning space, offering different illuminance zones would allow each pupil to place oneself in a zone corresponding to their personal needs. This is an important finding as most lighting regulations recommend a relative high uniformity ratio * across the horizontal working plane of a classroom. For example, EN 12464-1 recommends a uniformity ratio of 0.6. The intention of such recommendation is typically to ensure all possible places within the classroom would allow for appropriate and comfortable sight. However, at the same time it does not allow much variance in illuminance levels. The studies discussed seemingly agree that light intensity affects pupils’ visual performance, and herewith their learning outcomes. If light levels in a learning space fall outside the comfortable range of circa 100 to 1000 lux, pupils’ performance may be compromised. Yet, within this range there are still preference differences. Some pupils prefer relatively dim conditions while others prefer relatively brighter conditions. A learning space that offers a degree of light level variation (within the comfortable range) may provide the best conditions to optimize each pupils’ visual performance. In what way light intensity (as a characteristic on its own) affects pupils’ mood and behaviour is not yet very well known. * Uniformity ratio is the ratio of the minimum lighting level to the average lighting level in a specified area.

Light Colour

There are two types of light colour characteristics: correlated colour temperature and colour spectrum. As these are inherently different, findings about the implications of each are discussed separately.

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3.3.2

Correlated Colour Temperature

Research exploring the implications of colour temperatures in learning spaces focussed on its effect on pupils’ mood. Rautkylä et al. (2010) looked at the effects of relatively cool colour temperatures in lecture environments on pupils’ alertness. They compared alertness levels in pupils exposured to neutral white (4000K) with pupils exposed to very cool white (17000K), also referred to as blueenriched light, under similar illuminance levels. Pupils’ alertness was monitored during lectures both in the spring and autumn semester, for both morning and afternoon periods. Their data suggests that pupils exposed to very cool white (17000K) compared to pupils exposed to natural white light (4000K), in particular for autumn afternoon lectures, maintained higher levels of alertness. These findings suggest that colour temperature is a characteristic of light able to affect pupils’ mood state. What Rautkylä et al. (2010) did not detail is whether any demographic differences in mood responses occurred within the group of pupils studied. Untangling whether significant variations in mood responses between the respondents exist is necessary before arriving at any generalizations. Knez (1995) hereto compared behavioural tendencies and mood responses in male and female pupils exposed to neutral room light (4000K) versus warmer room light (3000K), both exposed to the same light intensity of 500 lux. He found that neutral white induced the least negative mood in males, but warm white the least negative mood in females. His later studies showed a consistent correlation between sex, mood, and colour temperature of lamps (Knez, 1998; Knez & Enmarker, 2001). In addition, Knez (1995) also found that individual preferences to colour temperature differ between pupils, and that exposure to the colour temperature one prefers most, enhances this pupil’s individual performance on cognitive tasks. While exposure to the colour temperature least preferred, compromised their performance. This outcome corresponds with both Riding’s and

Artificial Light and Pupil Behaviour

Correlated colour temperature (CCT) describes the colour appearance of light emitted from a light source and is expressed in kelvin (K). Essentially, it is a measure of how yellow or blue a colour appears. Generally, high temperatures (above 5000K) are referred to as cool white (bluish white), while lower temperatures (below 3000K) are referred to as warm colours (yellowish white). Temperatures in-between these ranges, typically around 4000K, are considered neutral white.

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Dunn’s findings for light intensity (see previous section 3.2.1): pupils who prefer brighter light perform better in bright light, and pupils who prefer dim light perform better in dim light. Allowing a degree of variation in illuminance levels and colour temperature in the learning environment allows pupils to choose their individual, optimal lighting condition to be seated in. The findings discussed indicate that the colour temperature of a light source can act as a mood inducer, but that the actual mood outcome may differ between pupils and might be demographically predisposed. Therefore, generalizations about colour temperature, preferences and mood are not straightforward.

Colour Spectrum

Artificial Light and Pupil Behaviour

The colour rendering index (CRI) of a light source is the quantitative measure of its capability to reveal the colours of objects faithfully, in comparison with wide-spectrum daylight. The CRI of an artificial light source is dependent on its spectral characteristics and typically ranges between 60 (low spectrum) to 90+ (high spectrum) (Boyce, 2014). A CRI value of 100 represents an ideal full-spectrum source (IESNA, 2011). The literature indicates that the influence of CRI on pupils in learning environments has been typically investigated by conducting field or lab experiments in which pupils were exposed to two or more types of lamps with different spectra. A broad range of effects, for example on pupils’ health, mood and behaviour have been investigated. While it appears a common belief that full spectrum light is beneficial to human health and well-being in general, the findings from these experiments in learning environment were found to be mixed. Maas et al. (1974) examined the effects of full-spectrum lamp against cool-white low spectrum fluorescent lamps. They found no differences between the two groups on self-reported fatigue in pupils. However, objective measurements via tests revealed less perceptual fatigue and better visual acuity in the full-spectrum condition. London (1987) reported that full-spectrum light was beneficial to the health of elementary school children. Pupils in full-spectrum light classrooms showed fewer illness-related absences than a control group exposed to coolwhite fluorescent light. Ferguson & Munson (1987) reports a decrease in grip strength and an increase in hand steadiness among school children who worked in full-spectrum light compared to those who worked in cool-white fluorescent light. However, these changes occurred only after several weeks, and no effects were found on other behaviours. Boray et al. (1989) exposed pupils to three different spectra of light: poor spectrum warm white, poor spectrum cool white, and full-spectrum white light. Their study showed no results on performance, mood, and evaluation, across gender. They argued that if differences

McColl & Veitch (2001) performed a meta-analysis of a large pool of studies, including those above, looking at the effect of light spectrum on building occupants in general. They concluded that full spectrum lighting has no dramatic effect on human behaviour or health. They also pointed out that those studies that did report certain effects, that these effects in fact were not prompted by the spectrum property of the light sources investigated in the study, but that the influencing parameters were actually the light source’s intensity and colour temperature. Based on the findings discussed, it can be concluded that the colour spectrum of light in itself is not capable to bring about significant change in pupils’ performance, mood or behaviour in a typical learning environment.

3.3.3

Light Intensity and Colour

Variable, or dynamic, lighting is a relatively recent type of artificial lighting application in which two beforementioned characteristics, light intensity and colour temperature, can be varied. These applications generally include a number of pre-defined intensity and colour temperature combinations, which can be activated by the occupant on demand. A few researchers have looked at the implications of a variable lighting system in learning environments, most notably on pupils’ performance though some attempted to uncover emotional and behavioural responses too. These studies took place in real-life school environments as field experiments. Küller & Lindsten (1992) studied the attention levels and social behaviour of Swedish elementary school pupils while exposed to a warm white, medium intensity light condition (300 lux at 3000 K) versus a cool white, low intensity light condition (200 lux at 5500 K)

Artificial Light and Pupil Behaviour

As a whole, the studies discussed present conflicting and weak findings. This suggests that the colour spectrum of light may not cause consistent nor reliable effects in pupils. However, one reason for these findings is the fact that the experimental studies discussed all took place in spaces with windows, and thus with natural light present in addition to the artificial lighting under review. Natural light is a full-spectrum source with a CRI of 100. The CRI of the indoor light as experienced by pupils, is thus a blend of the CRI of natural light and the CRI of the specific artificial light. Typically, the mean CRI experienced by pupils would be higher than the CRI of the artificial light alone. This distortion may have weakened or tweaked some research outcomes. However, as learning spaces typically have natural light present, the findings of these studies remain representative for real-life pupil experiences.

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among warm white, cool white, and full-spectrum fluorescent actually did exist, these would be quite small, present themselves only at individual level, or only showed after a long-term exposure.

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within the same classroom setting. Daylight was present in both conditions. They noticed a trend towards increased concentration when the cool white, low intensity condition was activated, and a trend towards increased communication (social behaviour) when the warm white, medium intensity condition was activated.

Artificial Light and Pupil Behaviour

Sleegers et al. (2013) investigated if a variable lighting system would affect the concentration of Dutch elementary school children by evaluating results of a pre- and post-intervention performance test. They compared the results of two groups of elementary school children exposed to a variable lighting system, with two comparable control groups exposed to a static lighting system. The static lighting system provided for a constant lighting condition of 600 lux and 4000 K. The variable lighting system allowed four setting options: (1) standard setting of 300 lux and 3500 K, (2) focus setting of 1000 lux and 6500 K; (3) calming setting of 300 lux and 2900 K, and (4) energy setting of 650 lux and 12000 K. The different settings could be activated by the teacher, who was given the instructions to use the standard setting for regular activities; the focus setting for activities that required concentration, such as tests; the energy setting in the morning and after lunch to give pupils energy; and the calming setting during collaborative group activities or when pupils seemed overactive. The average use of the different settings in the experimental classrooms was standard 51%, focus 14.2%, calm 31.4% and energy 1.4%. This indicates that during the field study, pupils in intervention rooms were approximately half of the time exposed to other than normal artificial lighting conditions. When comparing pre and post-test results after one month of experimenting, it appeared that the performance of the pupils in the intervention classrooms improved more than the performance of their peers in the control groups. A similar study was performed in the US, only for a much longer time frame, that of one academic year. Mott et al. (2012) used a similar variable lighting system, but only looked at the impact of two settings: (1) a standard setting of 500 lux and 3500 K, and (2) a focus setting of 1000 lux and 6500 K. They tested the system in four elementary classrooms over de course of one academic year and found that the focus setting improved pupils’ reading performance. This suggests that high intensity, cool lighting may have beneficial effects on pupils’ performance of specific curricular activities such as reading. They did not however find any significant effect on pupils’ reported levels of concentration and motivation when switching between standard and focus settings. Another longduration study took place in Barkmann et al. (2012). During this nine-month study, the researchers compared test performance of two elementary school classrooms with a variable lighting system against two classrooms fitted out with a standard, static lighting system. The settings for the variable lighting were the same as the Dutch study by Sleegers et al. (2012). Their results showed that pupils in the intervention classrooms made fewer errors,

Overall, findings from these studies suggest that a variable lighting system, which allows a teacher or pupil to select different light intensity and colour settings, may play part in improving pupils’ overall performance. However, the underlying mechanisms of behavioural and mood changes brought about by these variable systems has not been well documented yet. Sleegers et al. (2012) suggests that one of the opportunities for variable lighting is that it can incite different mood states such as alertness as well as relaxation in pupils. While Wessolowski et al. (2014) suggests that different lighting conditions affect behavioural outcomes such as fidgetiness, aggressive and prosocial behaviour. Both studies herewith imply that the incited mood states or behaviours could be aligned with the needs of different learning activities. Research looking at the impact of variable lighting (alias light intensity and colour temperature combinations) on pupils’ learning, and their behaviour and mood in particular, is still scarce. But those studies currently available do share the same view that variable lighting improves pupils’ learning outcomes in comparison to the traditional one-fits-all lighting condition. The benefit appears to reside therein that variable lighting allows occupants to adapt the lighting condition in the environment to match with their particular needs. This is an important finding as lighting regulations typically recommend installing one specific lighting condition only. In contrast, these findings suggest it is beneficial for pupils’ learning outcomes to allow for variable lighting conditions to serve different activity and occupancy needs.

3.3.4

Light Pattern

The characteristic light pattern differs from characteristics light intensity and colour temperature because it is not an intrinsic characteristic of light, but characterises how light intensities and colours are distributed in a space. The subsequent light pattern, a composition of lighter and darker areas, interacts with the space’s physical characteristics such as form, materials and finishes. It is these interactions that inform our visual impression of that space (Boyce, 2014). Changes to the intensity or colour of artificial light typically strengthens or weakens our visual impression thereof, whereas changes to the composition of lighter and darker or colour

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particularly fewer errors of omission, on a standardised reading test when exposed to the focus setting. In a follow-up study they also looked at several behavioural effects (Wessolowski et al., 2014). Their findings show a significant decline in observed fidgetiness and aggressive behaviours, and a tendency towards increased prosocial behaviour for pupils in the intervention classrooms. From their own perspective though, the intervention pupils did not rate themselves as being calmer or less aggressive, nor did their motivation, and interpretation of classroom atmosphere change during the nine-month period.

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areas inherently changes the expression of the light pattern itself. The latter affects our visual impression of a space more profoundly. Three experimental field studies by Flynn et al. (1973), Loe et al. (1994) and Govén et al. (2011) report their findings about how variations in the light pattern result in different visual impressions of the same space.

The Light Pattern Changes our Impression of a Space

Artificial Light and Pupil Behaviour

John Flynn, a well-known lighting researcher, pioneered studying light patterns and our visual impression thereof in architectural context. In the 1970s, Flynn already argued that: “In a luminous environment, a complex system of light patterns guides our behaviour and affects our sense of place” (1977, p. 96). He describes a light pattern to be a composition of contrasts—of brighter and darker areas—and considers the human visual system to be contrastsensitive rather than light-sensitive. He also suggests that our response to a light pattern, to some extent, is a shared experience. Flynn’s study took place in a real-life conference room fitted out with a desk (task) area and a lighting system capable of creating six different light patterns (Flynn et al., 1973, 1977). He examined observers’ subjective responses to each of the six patterns, which were created by activating one or more of three artificial lighting principles: (1) focused overhead lighting, (2) diffuse overhead lighting, and (3) peripheral wall-wash lighting (see Figure 3.5). The respondents partaking in the study were asked to rate their impression of the conference room according to a predefined rating scale. The study included adult respondents only.

Figure 3.5 Schematic illustrations of the six light patterns (Flynn et al., 1973)

Flynn found that the most significant rating scales by which respondents formulated their visual impressions of the illuminated conference room: (a) pleasantness, (b) clarity, and (c) spaciousness. (a) Typically, respondents judged the conference room most pleasant when all three lighting principles were activated (illustration 6, Figure 3.5). This light pattern is characterised by relatively high contrast ratios. While light patterns with the least contrast were considered dull and uninspiring (ill 2 and 5).

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(b) Flynn argues that clarity relates to how well respondents could distinguish spatial hierarchy in the room and herewith interpret its purpose. He found that when the desk (task) area was highlighted, attention of respondents was drawn towards it. Particularly when set in a relatively darker periphery (illustrations 1 and 4, Figure 3.5). When the task area was not accentuated, respondent’s attention was more drawn to the room’s periphery (illustration2 and 3, Figure 3.5). (c) These varying appraisals led to different spatial interpretations. The respondents judged the room to appear more spacious when the walls were illuminated. While when unlit, the room appeared more cramped.

Figure 3.6 Photographs of the eighteen lighting conditions (Loe et al., 1994)

Artificial Light and Pupil Behaviour Downloaded from lrt.sagepub.com at EASTERN KENTUCKY UNIV on May 27, 2015

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Similar shared preferences were also found by Loe et al. (1994), who performed a comparable study to Flynn in an office environment, exposing their respondents to eighteen different lighting conditions (see Figure 3.6). These respondents too preferred the office room to be lit so that it appeared ‘bright’ and ‘interesting’. 122

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What these findings indicate is that the same space can appear differently and herewith radiate a different message to the observer depending on how different brightness areas are organized. The light pattern thus influences our visual impression and herewith appraisal of a space. Flynn also found that these interpretations were agreed amongst respondents, alias shared experiences. The same was found true for the respondents’ preferences in regard to the different light conditions. The preferred conditions, which were for the room to appear bright (which correlates with a well-lit periphery), and interesting (which relates to a degree of nonuniformity of light pattern).

Mood and Performance Implications

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However, what neither Flynn et al. (1973) nor Loe et al (1994) investigated in these two studies is if, and how, the different light patterns and subsequent impressions affected the respondent’s mood, behaviour or performance. In follow-up study, Flynn did attempt to investigate how a light pattern affected behaviours such as circulation patterns, seat selection, posture and gestures (1973). This study was placed in a restaurant setting, and respondents were given the free choice to sit in differently lit seats. Flynn found that his respondents typically preferred to face a relatively bright surface, in this case a lit wall. By changing the placement of this brightness area relative to the seating, he was able to change the respondents’ seat selection. They now chose to sit in those seats facing the newly placed bright wall surface. This study revealed that the way the room was lit affected people’s seating choice. It thus had behavioural implications.

Artificial Light and Pupil Behaviour

Govén et al. (2011) also attempted to explore behavioural implications by the light pattern. He investigated the effect of two different light patterns in the classroom on pupil’s performance by administering academic tests, pupil’s mood by conducting surveys, and pupil’s physiology by taking blood samples to measure cortisol levels (a hormone related to sleep/wake cycle, or activation and relaxation). The data collection took place at regularly scheduled morning intervals over the course of one academic year. The study included four classrooms all with south-facing windows. Two classrooms functioned as control rooms. These were fitted out with standard, ceiling-based overhead luminaires, which distributed their light relatively evenly across the horizontal plane of the room. The two other classrooms were setup as experimental classrooms. Both classrooms were fitted out with suspended direct/ indirect luminaires, which increased the brightness of the ceiling, and ceiling-based wall-wash luminaires, which brightened the back-wall of these classrooms. Illumination levels across working areas were set between 300 - 500 lux, ensuring pupil’s visual performance would not be compromised. When comparing the data collected by Govén et al. (2011), the initial findings indicated that the two groups of pupils in the experimental classrooms with relatively bright ceilings and backwalls, overall featured a more positive mood, higher cortisol levels (suggesting pupils are more activated, or less sleepy) and increased academic performance. These findings were particularly evident during the winter months when natural light’s availability is limited. Although no more detailed results are not (yet) available for this study, the data does suggest that the way that a learning space is illuminated, alias the subsequent light pattern, influences pupils’ mood, behaviour and certain physiological processes, that ultimately may impact learning performance.

Three studies describe some findings related to directing our attention with light. Hopkinson & Longmore (1959) reports that their observers’ attention on a vertical visual task was best when the task was locally illuminated, then when it was lit from general ceiling illumination alone. A small, high-brightness light source below the task attracted shorter off-task glances, whereas a larger, low-brightness source appeared to be less distracting. LaGiusa et al. (1973, 1974) explored implications for pupils' attention to instructional material by using accent lighting on the teacher's instructional surface. This highlighting seemingly improved the amount of time pupils spent attending to (as judged by an independent observer) and their performance on a vocabulary task. The effect was replicated with a within-subjects design over a year's exposure to the new lighting set-up. A third study, by Taylor et al. (1975), looked at whether task lighting (meaning highlighting the task area) in an office space enables the observers to focus better on that task, and herewith improve their task performance. The study reports that of the three lighting scenarios studied, the scenario referred to as comfortable, non-uniform office illumination improved task performance best in comparison to the uniform and extreme non-uniform illumination scenarios. However, they also stated it is not clear whether the attention or other mechanisms such as preferences caused the difference in performance. Overall, the three studies suggest that high-illuminance areas attract the observers’ attention, but it is not yet clear whether this can elicit any desirable behaviours purposely. Research exploring implications of the light pattern for occupants is still scare, but those available indicate that it influences one’s visual impression of a space, and that certain patterns appear preferred over others. These impressions and preferences also appear to be shared experiences. Findings also suggest that a light pattern may incite certain mood responses, that can affect the observer’s behaviour and performance. A mechanism that may explain the workings hereof is the ability of a light pattern to direct the observer’s attention, particularly towards higher brightnessareas. This mechanism may improve one’s attention to a task area when accentuated relative to its surroundings. Though the evidence for such mechanism is still limited, and further research necessary.

Artificial Light and Pupil Behaviour

Veitch (2001) reports on another behavioural implication by the light pattern, namely towards the observers’ attention. The underlying theory applied by Veitch is that certain behavioural outcomes can be increased in likelihood by directing the observer’s attention to particular elements in the environment. Direction of attention may be achieved by making a target surface or object stand out by contrast against its background or surroundings. For example, such technique is often used in performing arts to highlight a character or area on stage by means of a spotlight.

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Attention Implications

3.3.5

The Artificial Light Characteristic of Interest

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This research explores how the artificial lighting in the learning environment could act as a tool for teachers to reduce class disturbances caused by pupils and improve their concentration on a learning task, and herewith improve the learning performance. For artificial lighting to act as such a tool, it requires that the teacher is able to change its expression via some form of (manual or digital) manipulation. The literature review revealed three characteristics of (artificial) light that are currently known able to bring about a mood or behavioural effect in pupils by changing expression. These are the light’s intensity, colour and pattern.

Artificial Light and Pupil Behaviour

Intensity and colour (temperature) are considered intrinsic light characteristics as their expressions are embedded within the light source itself. Light intensity can be directed towards a more intense (brighter) or less intense (dimmer) expression. The light’s colour temperature can be directed towards a warmer or cooler expression. Light intensity and colour can also be adjusted jointly. In most built environments, artificial light’s intensity and colour settings are controlled by the lighting system installed. On the other hand, the light pattern, in essence the composition of different brightness and colour areas in a space, is considered an extraneous characteristic of light because its expression is co-dependent on its interaction with environmental features such as form, materials and finishes of the space. These features are typically defined by the architects. Similar to artificial light’s intensity and colour settings, the composition of artificial light pattern is also controlled by the lighting system in place. Foreseeing how the light will interact with the environment it is placed in, is typically the responsibility and expertise of the architect. As this research is embedded in architectural practice, it appears fitting to explore how the artificial light pattern in the learning space could be manipulated to bring about the desired behavioural change: to discourage (disruptive) behaviours and to improve pupil’s concentration on their learning. Findings from the literature related to implications of the light pattern for occupants provide some indication what kind of light pattern could be capable of inciting the changes wished for. Most notably, findings by Flynn et al. (1973) suggest that a light pattern featuring relatively bright and focussed task lighting within a dimmer lit environment draws the observers’ attention towards the task area. He refers to this as clarity of the visual scene; how well respondents can distinguish spatial hierarchy in the room and herewith interpret its purpose. This notion is supported by findings from studies by Hopkinson & Longmore (1959), LaGuisa et al. (1973, 1974) and Taylor et al. (1975) who also suggests that highilluminance areas seem to attract the observers’ attention over lowilluminance areas. These studies also found that our response to a light pattern, to some extent, is a shared experience, and thus predictable once a causal link is established.

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Based on these findings, it can be hypothesized that a learning environment with a light pattern comprising relatively bright task area(s) set in dimmer surroundings may encourage pupils to focus more on their task instead of engaging with their surroundings. This may help pupils to attain and retain in a state of concentration, and reduce the impulse to express disruptive behaviours, and ultimately improve their learning performance. This provides for incentive to further explore the implications of said “bright task, dimmer environment” light pattern.

Challenges

(1) Realistic context. Our impression of the artificial light pattern is inherently linked with the architectural context it is placed in; including geometry, form and material finishes of the space. Light pattern studies should therefore be positioned in fullscale, real-life environments in order to arrive at realistic findings, particularly when these studies’ interests are the psychological effects of light. Finding access to such locations may be challenging. (2) Documenting issues. Artificial light patterns are difficult to document or measure as its difficult to distinguish its own characteristics from other features such as material properties and finishes of the environment itself, and importantly, natural light if present. (3) Technical implications. In order to investigate the impact of the light pattern on occupant (behaviour), two or more patterns are to be studied and compared between. To find or create significantly different light patterns may bring about severe technical complications as it may involve changing or replacing some of the lighting system components. In comparison, changing the artificial light’s intensity or colour temperature can often be achieved relatively easily through the control system built into an existing installation. (4) Practical implications. It may require some time before behavioural or mood changes incited by a change in the light pattern will manifest. Finding building owners and occupants willing to participate for a prolonged amount of time may be challenging. These reasons make it apparent that investigating potential implications of the artificial light pattern for building occupants may be relatively challenging. Nevertheless, this research sat out to do so, while being aware of the challenges to be addressed.

Artificial Light and Pupil Behaviour

However, the studies that investigated implications of the artificial light pattern, described this to be a complex undertaking. Boyce (2014) outlines four reasons or challenges why:

3.4

Summary

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The underlying aim of this study is to explore if artificial lighting, one of the features of the indoor learning environment, could act as a tool for teachers to manage (disruptive) pupil behaviour to improve quiet during class, and ultimately better pupils’ learning performance. Elements of three theoretical frameworks, namely by Veitch (2001), Boyce (2014) and Higgins et al. (2005), informed the theoretical underpinning for this research, which in essence outlines that light in the learning environment is able to incite a mood change in pupils via the perceptual pathway, and that such mood change is informed by pupil’s visual interpretation of their learning environment. The implications are amongst others changes in pupil’s engagement with their learning, and general attainment.

Artificial Light and Pupil Behaviour

A review of associated literature revealed how and in what ways artificial light in the learning environment has been found to influence pupils to date. These effects were found to be linked to three characteristics of artificial light that are typically researched: intensity, colour and pattern. While light intensity and colour are considered intrinsic characteristics of light, pattern is considered an extraneous characteristic of light because its expression is codependent on the interaction between the light and the environment it is placed in. As this research is embedded in architectural practice, the potency of the artificial light pattern in a learning space to incite the behavioural change in pupils this research aims for, is further explored. The limited research available about this potential relationship suggests that the light pattern in a space influences one’s visual impression thereof, and that certain patterns appear preferred over others. These also appear to be shared experiences. Findings also suggest that a light pattern may incite certain mood responses, and herewith to affect the observers’ behaviour and performance. A mechanism that may explain the workings hereof is the ability to direct the observer’s attention, particularly towards high brightness-areas. This mechanism may improve one’s attention to a task when it’s accentuated relative to its surroundings. Though the evidence for this mechanism is still very limited, and further research therefore encouraged, which this study looks to contribute towards. The next chapter details further what is understood as the artificial light pattern in architectural space, how it (technically) comes into being, and how its expression is found to affect occupants. The chapter also discusses what artificial light pattern is typically present in today’s Folkeskole learning spaces, and explores what alternative light pattern could possibly support attaining a quieter learning environment by discouraging disruptive pupil behaviours and improve pupils’ attention to their learning – ultimately to better their learning performance.

Artificial Light and Pupil Behaviour

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Artificial Lighting Design for Learning Spaces

ARTIFICIAL LIGHTING DESIGN FOR p. 85

LEARNING SPACES This chapter brings a design-practice perspective into the research. It outlines the scope of artificial lighting design and how it shapes our visual impression of a space. Some practical aspects of lighting design are introduced that informed the research approach, and the design freedom of the lighting designer is sketched to reside in the light pattern—an assemblage of lighting qualities such as intensity, colour, and spread. The pros and cons of the artificial light pattern that is typically present in Folkeskole learning spaces are discussed, and the missed opportunity of adaptability thereof is addressed. An alternative artificial light pattern is then proposed, that may discourage disruptive behaviours and improve pupils’ concentration as advocated by the 2014 Folkeskole Reform. Figure 4.1 illustrates the three key topics discussed in this chapter. Namely, the role of artificial lighting within indoor environments in general, and how deliberate application thereof in the Folkeskole learning environment may help manage disruptive pupil behaviours.

FFiigguurree 44..11 Schematic Schematic overview overview of of the the research’s research’s theoretical theoretical framework. framework.

Section 4.1 discusses the practice of artificial lighting design, how it is technically realized, and in what way the artificial light pattern affects one’s visual impression of a space. Section 4.2 reveals findings from a field study done to investigate the current state of artificial lighting in typical Folkeskole learning spaces, which exposed a bright and uniform pattern to be the norm. Section 4.3 introduces the concept of pools-of-light as an alternative pattern to address pupil behaviour, while section 4.4 summarizes the chapter.

Artificial Lighting Design for Learning Spaces

4.1

Designing Artificial Lighting for Indoor Environments

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Light is the medium that enables us to visually perceive the world around us and to perform our activities therein. As discussed in the previous chapter, besides enabling sight, light may also bring about a wider range of psychological and physiological responses. For example, it has been found to influence our mood, motivation, (social) behaviour, health and well-being (e.g. Boyce, 2014). Poor lighting especially has evident consequences as it causes agitation and reduced performance. Providing the right lighting conditions is thus essential to optimize occupant well-being and functioning.

4.1.1

Architectural Lighting Design

Artificial Lighting Design for Learning Spaces

From an architectural point of view, light influences our perception of indoor space, and of the objects therein. Our visual impression of such space is a function of the contrast between brightness and shadow areas. Variations in contrast can make a dramatic difference to how a space is perceived (Mangum, 1998). The composition of brightness and shadows, i.e. the light pattern, is informed by the interaction of light with the form, materials and finishes of the lit environment (Boyce, 2014), see also section 3.2.4. Architects are in charge of defining these environmental characteristics as well as the expression of the light pattern therein. Herewith architects are responsible for creating an appropriate visual indoor environment fittingly with the functional and aesthetics goals relevant for that space (IESNA, 2o11). To help architects realise appropriately lit indoor spaces, local lighting regulations and guidelines have been created. Building professionals in Europe for example consult their local adaptation of the European Standard EN 12464-1 (2011) which addresses indoor workplaces and associated areas, including learning environments. These standards have been informed by knowledge derived from lighting-related research. In line with the research developments as outlined in Chapter 3, these standards initially prescribed quantitative recommendations in support of occupants’ visibility and comfort needs. But when researchers shifted their focus to a broader perspective how light affects people, these standards followed suit and now also refer to qualities of light. Boyce (2014) defines lighting quality by the extent that a lighting design meets a broad range of objectives – for example visual comfort, but also to create specific impressions of a space (also referred to as atmosphere) and generating desired patterns of occupant behaviour – and constraints – such as budget and resources, timelines, pre-determined design visions. Both these objectives and constraints are set by the client and the designer.

The lighting conditions in regularly occupied spaces, such as learning environments, are typically a combination of natural light and artificial light. Although natural light optimisation gained prominence on the design agenda of architects, the role of artificial light as a design parameter thus far has been fairly limited (see section 4.2.3 for further discussion). Typically, artificial lighting is mainly considered to supplement when natural light is lacking. This research seeks to challenge this design stance by exploring how the artificial lighting may become something more than solely making things visible. For example, whether it could support teachers in their task to manage pupil behaviours considered disturbing to the learning situation at hand. In order to explore the potency of artificial lighting to act as such an aid, it is relevant to first clarify how artificial light manifests in indoor spaces, and how its expression can be manipulated by the occupant. The next two sections outline technical and architectural considerations hereto.

4.1.2

*/** The definition of the electrical lighting system and its five key components are defined by this thesis author based on her preceding professional experience.

The Electrical Lighting System

Artificial light is produced by an electrical lighting system. The definition of an electrical lighting system as adhered to in this thesis concerns the entire collection of components emitting artificial light to illuminate that environment *. This system is often designed and specified by the architect typically in dialogue with an electrical engineer, or occasionally, by an architectural lighting designer. The assortment of system components and their characteristics is vast – endless combinations and varieties are possible. Yet each electrical lighting system can be defined by five key components **: •

Light source. All systems contain at least one electrical light source that emits artificial light. These sources come in various shapes, sizes and typologies, but can each be described according to intrinsic characteristics such as intensity, colour temperature, and spectral power distribution.

•

Luminaire type. A light source is commonly embedded within a housing which, besides providing for electrical, mechanical and thermal management of the source(s). It also defines the distribution of the light emitted by means of reflectors, diffusers and/or lenses. There are many different luminaires available on the market.

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He also recognised that the success of a lighting design depends on the occupant’s expectations and attitudes to and past experiences with lighting. There are for example individual differences for what is considered comfortable lighting, and cultural differences between different regions about for instance lighting aesthetics (Boyce, 2014). There is therefore no typical lighting design that suits all situations. Understanding each space’s light and lighting needs is therefore key.

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•

Placement. Each luminaire’s placement relative to the architectural context and objects therein, as well as the direction of the emitted light defines where light and matter interact, and where not (or less).

•

Number. An electrical lighting system comprises one or (many) more luminaires. If multiple, these may be all the same type, or various luminaire types can be mixed. These may be arranged in a regular grid or following a custom arrangement.

•

Control. The regulation of each luminaire takes typically place via a central control system. This system allows the user to (de)activate, dim or change colour, either per individual luminaires or clustered as groups.

These are the key components of a lighting system the architectural team controls, besides the characteristics of the environment itself. Artificial Lighting Design for Learning Spaces

4.1.3

Design Aspirations for Artificial Lighting

The decisions about the selection of these components are typically informed by the applicable building regulations, various environmental goals, and any aesthetic aspirations (IESNA, 2011). •

For Danish learning environments lighting standard DS/EN 12464-1 (2011) is applicable, which, amongst others, prescribes the horizontal working plane (at desk height) in regularly occupied learning spaces is to be illuminated to a maintained illuminance level of 300 lux with a uniformity ratio of 0.6. This is considered to ensure the average pupil may (visually) perform their activities undisturbed and comfortably.

•

Typical environmental goals are often prescribed by the sustainability certification the projects committed too. For the artificial lighting, this may for example require strive for low energy consumption and long-lamp life durability.

•

Aesthetic aspirations typically refer to the ideal that integration of the lighting system is to be well synchronized structurally, mechanically, and aesthetically with the architectural context. Here aesthetics concerns both the physical look or style of the luminaires and other system components, as well as the way these are integrated into the architectural fabric. But aesthetics also deals with the visual impression of the space that is formed by the observer when the artificial lighting is in use. Thus, the overall appearance of the lit environment as a whole.

The last aspect, that of aesthetics dealing with the visual impression of the space, is of particular importance for this study and is further addressed in the next section.

Our Visual Impression of a Space

Light not only enables us to discern the physical environment and objects therein and to perform our tasks and activities well and safely, it also influences the way we filter meaningful information from our environment. Cuttle (2015) argues this allows us to build an overall visual impression of our surroundings (see section 3.2.2 for further details). Depending on the visual image formed, the environment may for example be interpreted as calm, lively or intimate. The fact that light influences our visual impression of a space was also recognised by Danish architect Steen E. Rasmussen:

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4.1.4

Although Rasmussen is referring to making a change to the way that natural light is entering the space, the principle is equally valid for artificial light emitted by a lighting system. Making changes to (one of) the lighting system components, for example repositioning a luminaire or changing light intensity, affects the expression of the subsequent light pattern, which prompts the observer to redefine our visual impression of that space. Variations in light patterns have been found capable to influence the observer’s mood and behaviour (see section 3.3.4 for further details).

Layering with Light The light pattern is characterised by how light intensities and colour areas are placed in a space (Boyce, 2014). The concept of illumination hierarchy entails the (deliberate) structuring of different light-and/or-colour areas relative to each other. Cuttle (2015) describes this as layering the distribution of illuminances (and colour) in a space. He distinguishes two types of illuminations, or light layers *, that can be structured by the designer and occupant: (1) ambient or background illumination, and (2) local concentrations of illuminations. (1) Ambient or background illumination refers to a layer of light that provides for general illumination of a space. This layer allows the observer to recognize the space and objects therein, and to orient and move around safely. Our perception of the ambient layer concerns for instance whether a space appears to be brightly lit, dimly lit or something in between, and informs our basic visual impression of the space. * This applies specifically to artificial lighting. However, it is important to notify that these artificial light layers may or may not be supplemented with a natural light layer if unobstructed windows or other façade openings are present in a space.

Artificial Lighting Design for Learning Spaces

Light is of decisive importance in experiencing architecture. The same room can be made to give very different spatial impressions by the simple expedient of changing the size and location of its openings. Moving a window from the middle of a wall to a corner will utterly transform the entire character of the room. (Rasmussen, 1959, p. 187).

p. 90

(2) Local concentrations of illuminations refers to a layer(s) of light that directs the observer’s attention, gives emphasis to an area or feature, or identifies objects that are considered visually significant. Most forms of life are attracted towards light, and humans are no exception. Phototropism is the process by which attention is drawn towards the brightest part of the field of view (Cuttle, 2015). It is a powerful tool for lighting designers, enabling to direct the observers’ attention towards certain areas, and away from others. This layer may include task lighting, which refers to illumination of task or activity areas in the space such as desks or wall mounted white boards. It may also include accent or mood lighting, which is used to highlight a valuable object or area and draw attention towards it, for example an artwork or wall decoration, or to reveal or enhance certain architectural features, for example a level change or a nook. This type of lighting augments our basic impression of the space defined by the ambient illumination.

Artificial Lighting Design for Learning Spaces

Illumination Hierarchy Ordered distributions of these illumination layers leads to the concept of illumination hierarchy, whereby illumination distributions are structured as the principle means by which the architect may express their design intentions (Cuttle, 2015). Some spaces may feature one layer only, typically ambient illumination, while other spaces may feature multiple layers. The latter often concerns spaces that host a varied palette of activities and/or are used by different occupant types with varying needs. A layered lighting design allows to direct the observers’ attention by creating visual hierarchy in the space. It may also allow for variability if the control component of electrical lighting system permits adjusting the settings of the different layers independently. In that case, the occupant may choose to (de)activate or modify certain light layers to deliberately change the expression of the light pattern in the space, herewith affecting the observer’s visual impression of the space. The capacity to change lighting layers is an important competence the electrical lighting system offers to this study, which seeks to encourage behavioural change in pupil’s by making changes to the artificial light pattern in the learning space. The following section outlines what changes the electrical light system permits in order to change the expression of the light pattern.

4.1.5

The Artificial Light Pattern

A key element defining our visual impression of a space is contrast. Contrast is the difference in brightness and/or colour areas that makes an object or surface more or less distinguishable to the observer. High contrast means a relatively large difference is present in the field of view; vice versa for low contrast (Boyce, 2014).

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In architectural context there may be multiple different brightnessand colour areas present in a space. The expression and placement of each area is defined by the components of the lighting system. The arrangement, or overall composition, of these brightness- and colour areas is generally referred to as the light pattern. There are three key parameters that define the appearance of the artificial light pattern: intensity, colour and spread * (Boyce, 2014; Cuttle, 2015). Changing (one of) these parameters inherently impacts the expression of the light pattern. This is demonstrated best with help of exemplary visuals. These are artist impressions and by no means accurate representations of reality. For the purpose of demonstration, natural light has been excluded and the room surfaces share the same white finish and reflectivity values.

Light intensity is the amount of visible light emitted by a luminaire (unit: lumen). The amount thereof falling onto a surface is expressed as illuminance (unit: lux), while luminance is the amount of light passing through or reflected from a surface entering our eyes (unit: cd/m2). Brightness is our perceptual response to luminance. One or more light intensities in a space may be either in- or decreased; the subsequent differences between these may strengthen or weaken the appearance of the light pattern in the space (Figures 4.2 – 4.4).

Figure 4.2 Low light intensity (dim)

Figure 4.3 Default light intensity

Figure 4.4 High light intensity (bright)

Figure 4.5 Warm white light

Figure 4.6 Neutral white light

Figure 4.7 Cool white light

* The label spread is used as no other labels were found in the literature that convey a similar meaning as intended here. In this research light spread refers not solely to light distribution form of light exiting the luminaire, but also refers to the placement of the luminaire relative in space, and the direction of the light beam if relevant.

Artificial Lighting Design for Learning Spaces

Light Intensity

Light Colour

p. 92

The colour temperature of white light * emitted by a luminaire may range between yellowish warm white to bluish cool white light. Varying the colour of one or more light sources strengthens or weakens the appearance of the light pattern in the space (see Figures 4.5 – 4.7).

Light Spread Light spread, in this thesis, refers to the placement, direction and distribution of the emitted artificial light relative to the space and objects therein. Spread particularly defines the character of the light pattern in a space – the arrangement of light(er) and dark(er) areas. Where changes in brightness and colour strengthen or weaken the expression of a light pattern, changes to (any of the three) light spread parameters inherently changes the expression of the light pattern itself. Typical variations applied in architecture for each of the three ‘spread’ parameters are illustrated in Figure 4.8. Artificial Lighting Design for Learning Spaces

placement

ceiling

suspended

wall mounted

down/direct

up/indirect

bi-directional

focussed

semi-diffused

diffused

direction sideways

distribution

Figure 4.8 Common examples of the three light spread parameters

To exemplify how changing each of the three spread parameters affects the expression of the artificial light pattern, six different lighting designs are presented in Figures 4.9 – 4-14. In all six examples light intensity and colour temperature kept the same. The first three examples are typical lighting designs that can be found in learning spaces (these would comply with lighting standard DS/EN 12464-1:2011) and each feature one ambient layer of light. * Colour may also refer to primary colours or mixes thereof. However, these are commonly not applied in standard working, living and learning environments, beyond possibly some decorative function.

Figure 4.9 Direct lighting (design 1)

•

Design 2 (Figure 4.10) shows three suspended luminaires. The light emitted is directed upwards to project light onto the ceiling. This design relies on reflected light hereof to fall onto the working plane. This type of design may be referred to as an indirect, ambient illumination scenario as the wall surfaces and working plane receive only indirect light reflected off the ceiling. The ceiling surface appears brightest.

•

Design 3 (Figure 4.11) shows the same three suspended luminaires, only now the light is directed both upwards to the ceiling and downwards to the working plane. This type of design may be referred to a bi-directional, ambient illumination scenario. The brightest surface will depend on the ratio between direct/indirect component of the applied luminaires, but in principle will be either the working and/or ceiling plane. The vertical wall surfaces will receive some direct but mostly indirect light reflected off the ceiling, work surfaces and floor.

Figure 4.10 Indirect lighting (design 2)

Figure 4.12 Direct + Wall wash (design 4) Figure 4.13 Pendant lighting (design 5)

Figure 4.11 Bi-direct lighting (design 3)

Figure 4.14 Direct + Pendant (design 6)

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Design 1 (Figure 4.9) shows six ceiling-based luminaires placed in a (regular) arrangement. The light exiting the luminaires is directed downward so that the majority of the artificial light is projected directly onto the working (task) plane below. This type of design may be referred to as direct, ambient illumination scenario because it prioritizes illuminating the horizontal plane across the room. The vertical wall surfaces receive some direct though mostly indirect light reflected off the working surfaces or ground floor. In this scenario the working (task) surfaces will appear brightest, the walls and ceiling appear relatively dim.

Artificial Lighting Design for Learning Spaces

•

p. 94

The following three examples are three non-typical typical lighting designs which may not necessarily comply with DS/EN 124641:2011. These designs may still allow for appropriate task visibility, albeit at the same time result in significantly different visual impressions of the room. Design 4 and 6 are multi-layered designs.

Artificial Lighting Design for Learning Spaces

•

Design 4 (Figure 4.12) combines two types of luminaires. The first type are six ceiling-based luminaires placed in a (regular) arrangement as per design 1. These provide for ambient illumination of the room, and the working plane in particular. The second type are ceiling based wall-washers projecting their light onto the backwall (whiteboard) area. This layer of light may be considered task lighting, attracting the observer’s attention to the wall. This type of design may be referred to a layered ambient/task illumination scenario.

•

Design 5 (Figure 4.13) shows four ceiling-suspended pendants directing their light directly below onto the desk surfaces. Contrary to the beforementioned luminaire types which project semi-diffused light (meaning the light has direction but is not strictly bundled), the pendants emit a focussed light beam that creates for local brightness areas. This type of design would be considered a directional, local illumination scenario. With no additional ambient lighting present, only a little reflected light of the desk surfaces may reach other surfaces such as the walls in the room. This design displays bright areas of light set within relatively dark surroundings. This results in relatively stark contrasts, or a high contrast ratio, within the room.

•

Design 6 (Figure 4.14) combines design 1 and 5 and shows both the six ceiling-based luminaires providing for ambient illumination, and the suspended focussed pendants creating concentrated pools of light. This type of design would be considered a local and ambient illumination scenario. It features the same local highlights as per design 5, but these are now surrounded by ambient illumination of the room itself.

These six designs exemplified the different artificial light patterns that may manifest in the same (learning) space. Each pattern, in essence a distinctive composition of different brightness areas, creates for a unique visual impression of that space. Different impressions have been found to provoke different (emotional and physiological) responses in occupants which may affect their mood and behaviour (see section 3.3.4). The next section discusses findings from a field study that was undertaken to investigate what type of artificial light pattern(s) typically is present in the Folkeskole learning environment today. This is relevant knowledge because in order to encourage behavioural change in pupil by modifying the artificial light pattern, the default light pattern must be understood in order to explore effective manipulations thereof.

4.2

Artificial Light in the Folkeskole

Figure 4.15 Sophieskolen (2016) in Nykøbing Falster, designed

Figure 4.16 Ørestad skole (2012) in Ørestad (Copenhagen),

by TNT Arkitekter and Creo Arkitekter. The school hosts circa

eight hundred pupils*.

hundred pupils*.

Figure 4.17 Herstedlund Skole in Albertslund (Copenhagen).

Figure 4.18 Trongårdsskolen in Lyngby (Copenhagen),

The school hosts circa six hundred pupils*. Built 1930,

updated 2011. Partly updated lighting in 2018/19.

seven hundred pupils*. Partly updated lighting in 2016.

* https://uddannelsesstatistik.dk, visited February 2020

The field studies took place during Spring 2016 and included in person visits to three or four learning spaces per school. During these visits the lighting system and appearance of the light pattern was assessed, and light level measurements (lux) taken at desk height. In addition, six non-structured interviews were held with teachers practicing in the Folkeskole, and four non-structured interviews with experienced school designers at Henning Larsen.

Artificial Lighting Design for Learning Spaces

To identify the status of the artificial lighting conditions in learning spaces today, how teachers and pupils experienced these, and why it is (designed) this way, fields studies were undertaken in four representative Folkeskole. Two of these are new built facilities, Sophiaskolen (Figure 4.15) and Ørestad skole (Figure 4.16). Both schools are fitted out with new electrical lighting systems. The two other schools, Herstedlund skole (Figure 4.17) and Trongårdsskolen (Figure 4.18) date back to the 1960s. The learning spaces here still feature the original lighting designs, though the luminaires have been refitted or replaced with newer lighting technology.

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Learning Environment

4.2.1

Artificial Lighting in the Learning Spaces

p. 96

Although the learning spaces visited (see Figures 4.19 – 4.25 for impressions thereof) have their own unique design features both architecturally as well as contextually, the artificial light conditions in these rooms were found to share three characteristics:

Artificial Lighting Design for Learning Spaces

•

Uniform light pattern. All learning spaces featured ceiling-based lighting systems that produce one, ambient light layer only. Luminaires are either recessed in, attached to or suspended from the ceiling, and evenly placed relative to the room. They typically emit semi-diffused light downwards. Most of this emitted light falls onto horizontal surfaces (floor or desks) and is distributed fairly evenly throughout the room (confirmed by the measurements). The walls receive some direct light, but mostly rely on reflected light of the horizontal surfaces (as does the ceiling). Overall, the resulting artificial light pattern in these learning space can be described as uniform as it shows little variations in brightness, alias is lacking contrast.

•

Bright appearance. The learning spaces appeared relatively bright when the artificial lighting is activated. The lux levels measured at desk height during daytime (with natural light present) confirmed that impression; measurements ranged between 300 and 500 lux, with lower and higher values recorded in corners or nearby window areas. These are slightly higher levels then the recommended 300 lux (see section 4.1.3). It was also found that luminaires are grouped per space and controlled via manual wall switches. These typically allowed occupants to (de)activate or dim the artificial lighting according to their needs. Sophie-skolen and Ørestad skole also featured automatic daylight-controlled dimming of the luminaires.

•

The artificial light pattern rules. During daytime (non-shielded) windows allow natural light to enter the learning spaces in all four schools. This has a significant impact on the overall lit appearance of these spaces. Without artificial lighting present, the subsequent natural light pattern in the room is a gradient with declining brightness away from the windows. But it never a static appearance as natural light changes depending on the time of day, season and weather conditions. However, when the artificial lighting is activated, this light pattern was found to overrule over the natural light pattern. The window wall now appears more a luminous wall rather than a light source itself.

These findings suggest that learning spaces in the Folkeskole visited typically feature one ambient layer of light produced by evenly distributed, ceiling-based luminaires projecting semidiffused light downward. The subsequent artificial light pattern is considered to be relatively bright and uniform (lacking contrast) in appearance and to dominate any present natural light.

p. 97 Figure 4.20 Sophieskolen – learning space w artificial light

Figure 4.21 Ørestad Skole – learning space w natural light

Figure 4.22 Ørestad Skole – learning space w artificial light

Figure 4.23 Herstedlund Skole – learning space w artificial light

Figure 4.24 Trongårdsskolen – learning space w natural light Figure 4.25 Trongårdsskolen – learning space w artificial light

Artificial Lighting Design for Learning Spaces

Figure 4.19 Sophieskolen – learning space w natural light

4.2.2

Teacher’s Experience with Artificial Lighting

p. 98

During the field studies four non-structured interviews were held with teachers working in the Folkeskole visited; one in each school. Two extra interviews took place with two teachers in a fifth Folkeskole, Frederiksbjerg school*. These in total six teachers were questioned about their views on and experience with the artificial lighting conditions** in their respective learning spaces, how they use the electrical lighting system installed, and if they make changes and for what reasons. Their responses revealed five aspects of the the artificial lighting conditions that are either well or poorly received. It also provided indications what the lighting condition currently may be lacking or missing. This knowledge helped to discern what artificial light pattern could be viable to better pupil’s concentration and discourage disruptive behaviour as per the ambition of this research. The pattern eventually selected is further elaborated on in section 4.3.

Artificial Lighting Design for Learning Spaces

The teachers’ responses have been categorized into three pros and two cons. The three aspects of the artificial lighting condition that were appraised relatively well (pros) are: •

Adequate visibility. All four teachers stated that the artificial lighting condition in their respective learning spaces was meeting their pupil’s and their own visual needs adequately. The relative bright and uniform light pattern (as described in the previous section) allows everyone in the space to discern their environment and objects therein well and comfortably, and to recognize each other and read facial expressions well. Most curricular activities are well supported by the lighting.

•

Visual comfort. None of the teachers expressed concern that the artificial lighting was causing for significant(glare) discomfort. It was generally considered bright, but not in a harmful way. Glare issues caused by direct sunlight was more often cited a concern, but typically managed by lowering window shading.

•

Ease of control. All learning spaces are fitted out with one or more wall mounted manual light switches that allows the teacher (and pupils) to (de)activate the lighting on demand. All teachers found this to be easy and efficient. Sophieskolen and Ørestad Skole also featured automatic control via occupancy sensors, which was considered a positive attribute. They wouldn’t have to remember to switch off the lighting after class.

* Frederiksbjerg School is the school this study’s field experiment took place. ** Occasionally the teachers referenced to the natural light conditions in their learning environments. These comments are not addressed here, only if relevant in conjunction with the artificial lighting. It is well understood that natural and artificial light generally operate in the learning space during daytime, when the learning spaces are in use, and herewith both inform the occupant’s visual experience of their space.

* instead of visual impression, often words like atmosphere, ambience or ‘feeling’ of the space were used to discuss the teachers’ experience with the lighting in their respective rooms.

Uninspiring visual scenery. The teachers described their visual impressions of the artificial lighting conditions * in their respective spaces with words as: uninspiring, bland, monotone, boring, and industrial. And particularly so during winter, when day- and sunlight doesn’t have a strong presence to enrich the artificial condition. This is an interesting finding that relates to Flynn’s study discussed in section 3.2.4. He found that light patterns with the least contrast (alias uniform) were considered rather dull and uninspiring. The teacher’s opinions correspond herewith. The artificial light condition was also appraised as child-unfriendly; it was viewed to better suit an office rather than a school. These opinions were voiced particularly strong by the teachers of the newly built schools (Sophieskolen, Ørestad Skole and Frederiksbjerg Skole). Though their views may have been accentuated by the relatively clean architectural context of their learning spaces. Typically, teachers with access to dimming controls said they try to lower the artificial light intensity to reduce its presence, while safeguarding their own and pupil’s ability to see well and move around safely.

•

Lack of variability. Although the visual appearance of the learning space illuminated by artificial lighting was not highly praised, it was generally considered to support most curricular activities adequately, particularly those activities requiring collaboration and interaction between pupil’s and/or teacher such as group tutoring and teamwork activities. However, the teachers described three situations that they considered to benefit from another artificial lighting condition: (1) Improve pupil concentration. Activities that typically require a pupil’s individual attention, for example mathematical, reading or language exercises, were believed to benefit from a different artificial lighting condition, namely one radiating a message of quietness, intimacy, safety and focus. Three teachers described how they tried to manipulate the standard lighting condition in their spaces. Their methods include deliberately decreasing the brightness in the room by lowering the window blinds or (de)activating or dimming the artificial lighting significantly. But they also spoke about introducing their own luminaires, for example table lamps, desk lights and even candle lights. These light sources distribute their light in direct vicinity (see Figures 4.26 – 4.28). In comparison to the standard uniform light pattern by the ceiling luminaires, these new luminaires create strong local brightness areas, and herewith a contrast-rich, or non-uniform, light pattern. A table or desk light would typically be handed out to small group of pupils with the intention to encourage soft talk and discourage engagement with other groups. The candles were handed to each pupil during reading

Artificial Lighting Design for Learning Spaces

•

p. 99

Two aspects of the artificial lighting condition in the learning spaces were considered to be lacking or missing (cons):

sessions to demarcate personal space with light. To strengthen this pattern, teachers would typically deactivate or dim the ambient room lighting. The subsequent new light pattern is associated with words as: intimate, sheltered and focussed. p. 100

Regardless of the approach, these three teachers believed the modified, local light condition in the learning space would help pupils to concentrate better on themselves and be less engaged and distractive to others.

Artificial Lighting Design for Learning Spaces

Figure 4.26 – 4.28 References of self-introduced luminaires by teachers in the learning environment (from fields studies)

(2) Revitalize sleepy pupils. The teachers also voiced an apparent need to revitalize or re-engage pupils with their learning (task) when their attention had faded. This typically would occur after lunch, or late afternoon, when pupils would be sleepier, loose interest quicker, wander around more and get agitated more easily. In these situations, teachers did quite the opposite and boosted the brightness in their learning spaces. For instance, by opening the blinds fully, or increasing the artificial light intensity (when the electrical lighting system permits). Their aim herewith is to replenish pupil’s mood and to encourage them to re-join the activity again. (3) Gradual wake-up. One teacher believed that during the early mornings of winter period the transition pupils would go through between arriving at school with their eyes adapted to the relative darkness outside to entering the learning space with fully activated lighting, was too harsh. He found that pupils would complain about eye strain and headaches, while others showed signs of agitation quicker. This teacher would dim the artificial lighting significantly at the start of the school, allowing pupils a gentle transition between the relative darkness outside and relative brightness indoors, and slowly built up. Herewith the teacher attempted to prevent an unproductive mood state, such as agitation, to be elicited. To summarize, the six teachers interviewed consider the standard artificial lighting conditions in their learning spaces to be relatively bright, dull and uninspiring, but to adequately support their own

p. 101

and pupils’ visual needs during collaborative teamwork activities. However, they point out three situations where they actively make modifications to the standard artificial lighting condition: (1) to encourage a state of concentration in pupils during attentionrequiring activities by creating local brightness areas; (2) to reengage pupils with their learning when their attention drifted by boosting the brightness in the learning space, or (3) prevent unproductive mood state as agitation or discomfort issues by gradual brightness adjustment. The first reason deals with making a deliberate change to the standard lighting condition in response to particular curricular activities. The second and third reasons deal with on-demand changes trigged by pupil’s mood state.

4.2.3

The Architects Approach

Following these field studies and interviews with teachers in these representative Folkeskole, four architects, all experienced with designing educational buildings, were consulted too. The reason hereto was to provide context to why the bright and uniform light artificial light pattern appears to be the conventional solution for learning environments. The interviews provided four insights: •

Artificial lighting is complementary, not leading. Light in general is considered by the architects a vital ingredient to their work – without light the built environment can simply not be seen. But their interest in light appears to go out mostly to natural light, and to bring indoors as much as possible. Main reasons are to exploit the health and wellbeing benefits of natural light, and to limit the building’s energy consumption in order to meet sustainability goals. Artificial lighting is not considered a key design parameter, and more considered a necessity to complement when natural light is lacking or not available. It is hereto addressed relatively late in the design process, allowing only little room to manoeuvre. This seems to limit architects to explore otherwise viable lighting design considerations.

•

Regulation and technical realization. Most often it is not the architect who specifies the lighting system components, but the (electrical) engineer who typically seeks to comply with the recommendations in DS/EN 12464-1:2011. These are mostly aimed at securing adequate visual functioning of the pupil’s visual system, and do not necessarily provoke to think beyond.

•

Visual appearance. From an aesthetical point of view, the architect appeared mostly concerned with the looks and placement of the lighting system components that are to be

Artificial Lighting Design for Learning Spaces

Regardless the motivation, it appears the teachers’ shared critique towards the standard electrical lighting system is that it doesn’t allow them to orchestrate different lighting conditions in their learning spaces to stimulate a certain mood or behaviour in pupils.

p. 102

integrated into the building and coordinated with other electrical and mechanical services. Very little attention is paid towards the appearance of the subsequent light pattern the occupant will ultimately experience, beyond meeting the recommendations targets for visibility and visual comfort. •

Limited knowledge about the impact of (artificial) light on occupant behaviour. Although research uncovered a broad range of influences and effects, the architects predominantly considered it to serve the needs of our visual system to perform our activities well, to move around easily and safely, and to allow 24/7 use of buildings. Only minor concern was shown for behavioural implications of the light, beyond wayfinding help.

Artificial Lighting Design for Learning Spaces

These findings indicate that architects generally prioritize designing with natural light and that artificial light is considered complementary to satisfy the building regulations and allow for 24/7 building use. The looks of the lighting system components and the architectural integration thereof are other key concerns of architects. These views architects have about (artificial) lighting may have prevented to explore opportunities beyond conventional solutions. This research looks to make such step, while respecting the basic requirements for sight, safety, and technical integration.

4.2.4

A Local Brightness Pattern

The field studies in four Folkekole learning spaces and interviews with teachers and architects revealed a discrepancy between what users of these learning environments want from the artificial lighting, and what a typical electrical lighting system therein offers. It particularly revealed a missed opportunity to change the expression of the artificial light condition in the learning space, most notably to support learning activities that benefit from quietness during class and pupil’s attention to their learning task. The teachers interviewed already professed to self-modify the lighting situation in their respective learning spaces, most notably by adding their own portable sources. They believe the subsequent local brightness areas in the learning space encourage soft talk and intimate focus within small groups of pupils, discourages pupils to engage with peers outside their inner circle, and supports pupils to focus on their own task at hand (see section 4.2.2). If these assumptions are found to be true, the behavioural change brought about by these localized brightness areas would result in reduced disturbances during class, improved overall quietness and better pupil concentration as advocated by the 2014 Folkeskole reform. The next section outlines findings from two other sources, namely associated literature and architectural practice, that were consulted to further detail what type of artificial light pattern could encourage the desired behavioural change.

4.3

The Artificial Light Pattern to

Although the teachers’ intuitive use of a local brightness areas to encourage pupils to concentrate on their task seems a plausible concept, two other sources were consulted to further substantiate the validity of this hypothesis: (1) the associated research literature, and (2) practice informants (alias architects).

Suggestions from Research Literature

The literature review discussed in Chapter 3 revealed that artificial lighting has the potential to create stimulating visual environments that affect pupils’ mood and other behavioural outcomes. Besides its intensity and colour, particularly the way the artificial light is placed, directed, and distributed (also referred to as: spread) in the space that informs the expression of the subsequent light pattern observed. Variations in the light pattern, most profoundly by altering the relative placement of and difference between the brighter and dimmer areas in the space, have been found to bring about different emotional and physiological responses. The literature review revealed that a non-uniform pattern, also referred to as contract-rich, that features one or more different brightness areas in a space, could be capable of encouraging the mood or behavioural change in pupils as desired for this study. Flynn et al. (1973) and Loe et al. (1994) found that occupants of indoor workspaces such as an office or conference room typically prefer lit conditions that made the space appear bright (which correlates with a well-lit periphery) and interesting (which relates to a degree of non-uniformity of light pattern). Govén et al. (2011) found that exposure to a relatively non-uniform light pattern in the classroom improved pupils’ mood and performance. Veitch (2001) points towards the capacity of a non-uniform light pattern to direct the observer’s attention to particular elements in the environment. This was documented to affect an observer’s behaviour and performance. Hopkinson & Longmore (1959) reported their observers’ attention on a vertical visual task was best when the task was locally illuminated, then when lit from general ceiling illumination alone. LaGiusa et al. (1973, 1974) found that applying accent lighting on the teacher's instructional surface improved the amount of time pupils spent attending to and their performance on a vocabulary task. Taylor et al. (1975) found that task lighting in an office space enables observers to focus better on that task, and improved task performance. And, Flynn et al. (1973) found that observers are attracted by brighter surfaces and prefer to face towards them.

Artificial Lighting Design for Learning Spaces

4.3.1

p. 103

Improve Quietness

p. 104

These findings suggest that a learning space with a relatively nonuniform, or contrast-rich, light pattern may encourage a positive mood state. And when also featuring relatively brighter (task) areas set in dimmer surroundings, these may draw the occupants’ attention towards these brighter areas. These behavioural implications may affect occupants’ (task) performance positively.

4.3.2

Ideas from Architectural Practice

Informal conversations between the author of this thesis and four architects at Henning Larsen allowed to speculate how artificial lighting could be applied to create local light areas and support pupil concentration, from a designer’s perspective. This enquiry relied on our joint professional experience with architectural design and light, and specifically our interpretations of how light interacts with spatial form, geometry and materials, and people.

Artificial Lighting Design for Learning Spaces

A tactic most frequently discussed was to look for ways to encourage pupils to focus on oneself instead of others or their surroundings. One way suggested to achieve this was by creating spaces-withinspace – or smaller spaces within the bigger learning space for pupils to withdraw into. Reference was made to the hospitality sector where local (candle) light often is used to create a private microsetting for a (group of) customers within a larger restaurant setting. The same principle could be applied to the learning space. The premise being that when a pupil is seated within an area of relative brightness, set within dimmer surroundings, would stimulate the pupil to focus on oneself. Inside such brightness area, referred to as pool-of-light, a pupil would become part of a smaller, more intimate light space set within the bigger learning environment. Within each local lightspace, those pupils inside would possibly also feel more encouraged to interact with peers within their micro-space, than with those outside their micro-space. It is hypnotised this would cause less hinderance and disturbances. This ideal would align with the emphasises of the 2014 Reform to decrease disruptions and unrest during class. Pupils that are more self-aware and focused on their own task may be less inclined to display disruptive behaviour. It was also though that relative bright pools-of-light set in dimmer surroundings would attract pupils towards them, particularly when aligned with the seating furniture. Reference was for example made to a campfire setting, which draws people intuitively towards it. A campfire radiates light and warmth and attracts people to come nearby and gather around (see Figure 4.29). Another common reference was made to the dining table setting in their own homes. Commonly illuminated in Denmark by a pendant projecting its light onto the table surface. The relatively bright table was believed to attract family members towards it (see Figure 4.30).

Figure 4.29 – 4.31 Reference images for pools of light

4.3.3

The Alternative Light Pattern: Pools of Light

Findings from these sources – teachers, literature and architects, informed the formulation of an alternative light pattern that is hypothesized to encourage the desired change in pupil behaviour: •

the intuitive tactics of teachers to use local light sources to attract and keep pupil’s attention inwards, and less orientated towards other pupils in the learning space.

•

the findings from the literature indicating that brighter areas set in darker surroundings attract one’s attention.

•

the proposed ideas from architectural practice that bright areas attract pupils towards them, and pupils residing in these areas experience these as intimate micro-spaces within the bigger learning space – discouraging interaction with outer peers.

Based on these findings it is deemed plausible to explore the implications of a non-uniform, contrast-rich artificial light pattern featuring relatively bright areas situated within a relatively dimmer surrounding on pupils’ behaviour. This pattern, which is referred to in thesis as: pools-of-light is significantly different from the standard, uniform artificial light pattern typically found in today’s Folkeskole learning environments. This makes it possible to study the impact of a light pattern change based on comparison studies.

p. 105 Artificial Lighting Design for Learning Spaces

Renowned architect Richard Kelly (Kelly, 1952) described a similar belief when he discussed his concept of light as a focal point. To him, light has the capacity to draw the observer’s attention to the area or object it highlights because of its relative brightness set against a darker background (see Figure 4.31). He was referring to deliberately accentuating for instance architectural features or art object to guide the observer’s eyes. But the same principle may apply here too; pools-of-light in a learning space may attract pupils towards them, to sit within and focus their attention locally.

4.4

Summary

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The underlying aim for this study is to investigate whether the artificial light pattern, which is one of the features of the physical learning environment, could assist in discouraging disruptive pupil behaviours and wherewith improve quietness during class, ultimately to better pupils’ learning performance. If found capable thereof, the artificial lighting in the learning space could become a tool at the disposal of teachers to assist managing pupil behaviour.

Artificial Lighting Design for Learning Spaces

A light pattern is the overall arrangement of brightness- and colour areas in a space. The key parameters defining the expression of an artificial light pattern are intensity, colour and spread. Changing (one of) these parameters inherently impacts the expression of said light pattern. Where the first two variables, intensity and colour, merely concern a direct relationship between the light emitted and the observer receiving it, the third variable, spread, concerns experiencing the interaction between the emitted light and the (physical) features of that environment. Spread is defined by the placement, direction and degree of distribution of light relative to the space and its objects. Each pattern, in essence thus a distinctive composition of different brightness areas, creates for a unique visual impression of that space. Variations herein have been found to impact pupil’s mood and behaviour. A review of current status of and user experience with the artificial lighting conditions in four representative Folkeskole learning spaces, revealed a typical light pattern that is relatively bright and uniform featuring little apparent contrasts, that dominates over the natural light. This pattern is generally considered as uninspiring and bland, but does support pupils and teachers’ visual needs well. The artificial lighting system lacks opportunity to be adapted by the teacher to support different activities or mood states. This may particularly be evident post-reform, now that curricular settings are more diversified, and pupil engagement increasingly varied. The lighting appears particularly lacking to support curricular activities that require more individual focus, quietness and concentration. Based on the suggestions derived from research literature, field study interviews with teachers and experienced architects, it appears promising to investigate whether an alternative light pattern referred to as pools-of-light may elicit the desired behavioural change in pupils to result in more quietness during class, and ultimately better their learning performance. The question is research thus looks to answer can be formulated as: Does exposure to the pools-of-light pattern in the Folkeskole learning environment discourage disturbing pupil behaviours and herewith improve quietness during class? And if so, does this change significantly affect pupil’s learning performance?

p. 107 Artificial Lighting Design for Learning Spaces

The method chosen to investigate if the pools-of-light pattern is indeed inciting the desired behavioural change pupils, is that of the experimental field study. The following three chapters will further detail the field experiment as performed. Chapters five outlines the various research variables considered significant, and the methods used to study these during the field experiment. Chapter six describes the contextual setup, details the experimental lighting installation, and outlines the research design developed to collect viable data for comparison. Chapter seven discusses the analysis of this data, and the results derived.

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The Field Experiment Variables

This chapter introduces the field experiment that was performed in a real-life Folkeskole, namely Frederiksbjerg School in Aarhus to investigate if the artificial light pattern can influence pupils’ behaviour in a way it improves quietness during class. During the experiment pupils were alternately exposed to two types of artificial light patterns (treatment variable), while data was collected about their behaviour and performance (outcome variables). In addition, fourteen potentially intervening variables were monitored as well so that data contamination could be limited. Figure 5.1 illustrates all these variables that have been assessed during the field experiment.

Folkeskole Learning Environment

(A) uniform light

Outcome Variables

(I) noise

(II) behaviour

(III) performance

(B) pools of light

Intervening Variables

(1) architecture

(5) activity

Figure 5.1 Diagram of the variables reviewed during in the field experiment

(2) interior

(3) climate

(4) pupils

The Field Experiment Variables

Central to this research is the quest for a better Folkeskole learning environment that supports the changes introduced by the 2014 reform and herewith better pupils learning performance. This study particularly answers to the reform’s call to improve quietness during class so that pupils can concentrate better on their learning, and ultimately perform better. It does this by exploring how the artificial lighting, and the artificial light pattern in particular, can assist teachers in managing pupil behaviours that disrupt their own or others concentration. Based on suggestions derived from associated research literature, Folkeskole field studies, and interviews with teachers and experienced architects it appeared promising to investigate whether a non-uniform artificial light pattern referred to as pools-of-light could reduce undesired pupil behaviour and herewith improve quietness during class.

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THE FIELD EXPERIMENT VARIABLES

Treatment Variable

p. 110

This chapter details these treatment, outcome and potentially intervening variables that have been assessed during the field experiment. Though Section 5.1 first outlines the rationale for using the field experiment as the main method of investigation, and discusses two considerations related to the validity of the experiment’s that informed the design of this field experiment. Section 5.2 than discusses the field experiment’s treatment variable, alias the artificial lighting pattern, and the two typologies thereof that pupils have been exposed to during the experiment: (A) the standard uniform artificial light pattern created by ceiling-based luminaire tiles, and (B) the experimental non-uniform pools-oflight pattern created by temporarily installed pendants. It also describes how the expressions of both patterns were assessed. Section 5.3 describes the three outcome variables that were used to reveal whether any significant change in pupil’s behaviour and performance occurred that can be related to exposure to the two types of artificial light patterns: (I) noise during class, (II) disruptive behaviours, and (III) cognitive performance. The methods used to collect the necessary data per variable are provided.

The Field Experiment Variables

Section 5.4 lists the fourteen potentially intervening variables that were identified to potentially contaminate the study. These variables are clustered into five categories: (1) architectural variables, (2) indoor climate variables, (3) interior variables, (4) subject variables, and (5) activity variables. To account for each of these variables either a mitigating approach has been applied that allowed to exclude some variables as potential contaminators. When not feasible the method used to collect relevant data is described. Section 5.5 than summarizes the chapter.

5.1

An Experimental Field Study

5.1.1

Motivations for Experimenting in the Field

There are three motivations for choosing the field experiment as the main method of investigation. Firstly, this method is advocated in the literature (see Chapter 3.1.2). Most notably by Boyce (2014) who argues that researchers exploring behavioural effects of light should position their studies in real environments because light and the physical disposition of the environment are intrinsically connected. Our visual experience of light in architectural context is difficult to replicate in a lab setting. Boyce further argues that in order to document any realistic behavioural change, respondents need to be exposed to the (experimental) lighting condition long enough to consider this their ‘new normal’. Limited exposure, which is often the case in lab settings, might risk that respondents will ignore a change in the lighting condition temporarily. Thus, researching the implications of lighting conditions on occupant behaviour in “the field” offers several advantages.

Thirdly, this research was conducted as an industrial partnership with architectural practice Henning Larsen with the underlying aim to improve learning environments. The organisational setting and context of this research therefore encouraged a situated approach; meaning for the study to be placed in a real environment so that not only academics but also architects and design practitioners could relate to the findings. This naturally led towards the method of field experimentation, as it allows to design and introduce light variations in real-life spaces in a controlled way, and study potential effects thereof on pupils while they continue their normal routines.

5.1.2

Considerations for the Research Design

The aim of field experimentation is to establish a relationship between a treatment variable and (an) outcome variable(s). The treatment variable in this research is the artificial light pattern in learning spaces used by primary school-age children. The outcome variables are (change in) disruptive pupil behaviour and their learning performance. Creswell (2009) describes several threats that may compromise the validity of a field experiment. These threats need to be addressed prior to commencing the experiment to avert false outcomes. Two threats have particularly informed the research design of this field experiment. The first is the potential threat of data contamination by other variables than the those of interest in this study. The second threat is the inability to assign respondents randomly to a group, which could introduce systematic differences and complicate the interpretation of results.

Data Contamination The risk of data contamination in a field experiment is real, because in real-life environments there will be other variables present than the treatment variable (the artificial light pattern) that could affect the outcome variable of interest (pupil behaviour and concentration) but cannot be controlled for. These can possibly contaminate the data. It is therefore key to identify those potentially intervening variables prior to commencing the experiment.

p. 111 The Field Experiment Variables

Secondly, the intended research approach to investigate whether the pools-of-light pattern would encourage the desired behavioural change in pupils was to perform a comparison study between two or more Folkeskole learning spaces with significantly different artificial lighting conditions. However, the field studies undertaken in the four Folkeskole during the preliminary studies (see Chapter 4.2) revealed that Folkeskole learning spaces typically feature the same relatively bright and uniform artificial lighting pattern. This has been attributed to the wide-spread application of ceiling-based luminaires. This made a comparison study no longer possible, as the learning spaces would feature too similar lighting conditions.

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Fourteen of such potentially intervening variables have been identified for this field experiment (see section 5.4). The next step is to decide on the research tactics to either neutralize, or if not feasible, monitor these variables. To neutralize the potentially intervening variables, for example the weather conditions outside and time of day, a crossover research design was applied (Creswell, 2009). A crossover research design requires that both versions of the treatment variable of interest, in this study the two artificial light patterns, are tested concurrently. This requires hosting the field experiment in at least two comparable learning spaces during the same time period. Other identified intervening variables, dealing with architectural implications such as window design and furniture arrangements, could be neutralized by careful selection of these host learning spaces. The dealing with these intervening variables is further detailed in section 5.4.

Assignment of Respondents

The Field Experiment Variables

The pupils partaking in the field experiment cannot be assigned randomly to a group due to practical and ethical reasons. The experiment had to work with pre-existing pupil groups, that could have different demographic compositions. In order to neutralize differences between pupil groups a within-subjects research design (Gifford, 2015) was applied. This means that each group was exposed to both artificial light patterns, so that data could be compared within the same pupil group. Both the decision to apply a crossover research design as well as a within-subject research design informed the overall design of the field experiment’s research protocol, which is further addressed in section 6.3.

5.2

Treatment Variable: The Artificial Light Pattern

Treatment Variable

The treatment variable of this field experiment, the artificial light pattern, allowed for two type of expressions: (A) uniform light

(B) pools of light

•

Standard uniform light pattern which results in a relatively monotone appearance of the learning space, featuring very few variations between brighter and darker areas (see artistic impression sketch, Figure 5.2).

•

Experimental non-uniform pools-of-light pattern which results in a relatively contrast-rich appearance of the learning space, showing significant variations between the relatively brighter pools-of-light situated in relatively darker surrounding environment (see artistic impression sketch, Figure 5.3).

p. 113 Figure 5.2 Uniform light pattern

5.2.1

Figure 5.3 Non-uniform pools-of-light

The Standard Uniform Light Pattern

The uniform light pattern may be considered a lighting condition that serves the average occupant’s visual needs. No distinction or hierarchy is applied between different areas in the space, allowing pupils to be seated anywhere and see well in all directions – for example their nearby task area as well as a teacher’s smart board positioned across the space. The resulting visual narrative of the space may be described as one of equality, openness and functionality. But it has also been referred to as monotone, dull and uninspiring (see section 4.2.2). This implies a contradiction; on one side the lighting is appreciated because it serves pupils visual needs, and on the other side the lit appearance does not necessarily seem to be comfortable or inspiring the learning. In the experimental field study, the uniform light pattern has been technically realized by utilizing the ceiling-based lighting tiles already installed in the learning spaces hosting the study.

5.2.2

The Non-Uniform Pools-of-Light Pattern

The pools-of-light pattern is a specific type of a non-uniform distribution of light in space. As opposed to the uniform pattern, the pools-of-light pattern is not typically present in the Danish Folkeskole learning spaces. The reasons for selecting this particular type of light pattern for further study are discussed in section 4.3.In the experimental field study, pendants were used to create the pools-of-light pattern. A pendant is in essence a light source placed within a housing that is suspended a certain distance from the ceiling. Provided the housing is opaque, it will project the emitted light downwards to form a pool of light on the surface it falls onto.

The Field Experiment Variables

A uniform light pattern shows relatively little variation between lighter and darker areas in the learning space. The light is fairly evenly distributed across the horizontal plane of the space, with the vertical surfaces illuminated correspondingly. This typology was found typically present in the Danish Folkeskole learning spaces, and therefore represents the standard lighting condition pupils are most often exposed to today (see section 4.2.1).

There were three reasons for opting for pendants to create the pools-of-light pattern: Flexible. The position of a pendant within the space, and the suspension height of its housing can be chosen relatively freely. This allows for a synchronization between the location and size of the pool of light and the working desks of pupils. In normal conditions, desks can be moved around in learning spaces. It would therefore be important for the experiment to agree with teachers a position for the furniture and keep that in place throughout the experiment.

•

Implementable. The pendants are relatively easy to install and wire into an existing electrical circuiting. They do not require extensive changes to the ceiling and only need a single point of attachment to the ceiling. Following regulations however, the installation should be performed by a certified contractor

•

Recognisable. The pendant is a familiar luminaire type in Denmark, and the lighting object was expected to blend in the interior design and not to exercise a particular visual attraction—and become a distraction. Nevertheless, the research allowed for time between the installation of the new lighting and the actual start of data collecting, so that pupils would have time to become familiar with the experimental lighting installation.

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•

The Field Experiment Variables

5.2.3

Assessment Methods

A prerequisite for establishing if a relationship between the chosen treatment and outcome variables exists, is that the expression of the treatment variable can be significantly varied to be able to incite a (potential) change in the outcome variables. Therefore, the expressions of both the standard uniform pattern and of the experimental pools-of-light pattern were assessed and compared amongst with help of two light mapping methods: •

The first method required mapping horizontal illuminance levels across the working plane of the learning spaces hosting the experimental study for both light pattern scenarios. The ratios derived from this mapping techniques were assessed according Christopher Cuttle (2015) prescriptions of perceived differences of illuminance.

•

The second method included taking high dynamic range images (HDRI) of both light patterns in all learning spaces hosting the field experiment to evaluate the appearance of the entire space and the brightness variations therein as a whole.

Section 6.2.5 provides for further details about both these methods and discusses the subsequent findings thereof.

5.3

Outcome Variables: Pupils’

(I)

Noise Levels – as pupils are the primary cause of noise during class, it can by hypnotized that a change in noise levels relates to a change in pupils’ behaviour. This variable is a quantitative measure.

(II)

Disruptive Behaviours – these concerns three types of externalized and observable behaviours that interrupt a pupil’s own and/or others concentration towards the learning task. This variable is a qualitative measure.

To investigate whether change, if found, in pupils’ behaviour would impact their ability to concentrate and herewith pupils’ learning performance, a third variable was studied: (III)

Cognitive Performance – assessed by means of specialized tests. This variable is a quantitative measure.

Research Methods Each variable been treated as an individual data collection study I, II and III. Figure 5.4 shows a diagram of the three outcome variables and the research methods used to collect data on each variable. The next paragraphs describe each variable and the related methods. Study (I) – Noise Levels. Noise is found to be a prevalent disruptor in school classes. A significant source of noise is found to be the pupils themselves, who generate noise vocally or through physical activity (section 2.3.1). Noise acts as an inverse variable, the premise being that a reduction in noise from pupils suggests an increased state of concentration in pupils. Less noise also equals better aural conditions, or a better learning environment, as set out in the goals of the school reform. The noise data has been collected with

The Field Experiment Variables

This experimental field study explores if pupils’ behaviour and learning performance are affected by the artificial light pattern. Specific interest goes out towards pupil behaviours that typically result in audible, visual, or physical forms of disruptions that interrupt pupils’ concentration on a learning task (section 2.3). Or in other words, observable disruptive behaviours. Concentration refers to the ones ability to attain and maintain attention on the learning task (section 2.1.2). When pupils’ concentration is compromised by disruptions, this was found to negatively affect their learning performance (section 2.x). Because behaviour is a very broad concept to study, this variable has been made operational by employing two related variables that have been proven measurable or observable for change by preceding researchers (section 3.2):

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Behaviour and Performance

Research method sound recording video recording

observations (II)

behaviour

interviews focus groups

(III)

performance

cognitive tests

Autumn 2017

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Outcome Variables

noise

Spring 2017

(I)

Figure 5.4 Diagram of the three outcome variables and methods used to collect data

The Field Experiment Variables

specialized sound recording equipment during appropriate learning activities, and rather than a statistical reduction in noise, the research would look for perceptibly significant differences. In order to link sound records to appropriate activities, the learning sessions were also videoed. Study (II) – Disruptive Behaviours. This study looked for behavioural changes that can be (outwardly) noticeable to teachers and pupils, and are typically experienced as disruptive. Three types of disruptive behaviours were identified in the literature (section 2.3.2). These can be classified as: (a) expressive behaviours, (b) social behaviours, and (c) physical behaviours. The occurance of these behaviours during the field experiment was studied with help of a number of qualitative research methods: (1) observational studies during class, followed up by (2) interviews with the respective teachers of those classes, and a few intermittent (3) focus groups with pupils. The premise for this study is that when fewer occurrences of disruptive behaviours are observed, would suggest pupils concentrate better on their learning (task). Less disruptions also contributes to attain a better learning environment in general as prescribed by the 2014 Folkeskole reform. Study (III) – Cognitive Performance. This study measures pupils’ cognitive performance by means of specialized (1) math and (2) creativity tests administered in the experimental learning spaces. The premise is that improved cognitive performance, expressed in the test results, would imply an increased state of concentration and thus less distracted pupils. Such change would relate to changes found in the noise level and/or display of distractive behaviours in the learning environment, which are explored in study (I) and (II). Due to the nature of analysing the test results, this study looks for statistically significant differences.

Studies (I) and (II) in noise and behaviour would be performed during learning activities that require a concentrated state of mind. Noise and behaviour are less likely to disturb pupils when they for example engage in collaborative-learning that require the pupils to discuss and interact, or play activities that allow for physical and social exercise. Focused-learning activities such as reading, writing and mathematics, on the other hand, require undisturbed attention and benefit from increased pupil concentration. Focused-learning activities are undertaken individually or in small groups.

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Focussed-Learning Activities

To control for this, the learning sessions would also be video recorded, so that the actual focussed-learning activities could be identified afterwards. Studies (I) and (II) concurred simultaneously during Spring 2017. The cognitive performance tests of study (III) were administered at the end of a normal curricular focussedlearning session and would by default be considered a focussedlearning activity. This study took place during Autumn 2017.

Consent Parental consent for pupils to be subjected to study (I) and (II) was acquired via the school’s intranet via a notification. For study (III) parents of the pupils to be subjected to the exercises were consulted in and asked to confirm in writing.

5.3.1

Study I: Noise During Class

This study measures noise, or sound levels, during focussedlearning activities, while the pupils are exposed to either of the two artificial light pattern typologies. The study looks for perceptibly significant differences in sound level between the two situations.

Data Collection Method Sound recording. To investigate if a change in noise would manifest under different lighting situations, sound levels were recorded during curricular sessions in the four learning spaces. Video recording. At the same time, videos were recorded in these learning spaces, documenting the positions and number of pupils present and the activities ongoing. These recordings allowed to revisit the curricular sessions in order to interpret the recorded sound data.

The Field Experiment Variables

The collection of noise and behavioural data would therefore take place during focussed-learning activities. Although the weekly curricular schedule of the learning spaces would suggest indicatively what kind of learning activity was scheduled, the actual activity could still be changed by teachers as they would see fit.

Technical details of the sound and video recording equipment and setup in the learning spaces are fully described in section 7.1.1. For further details on the recorded sessions, see section 6.3.1. p. 118

Data Interpretation The sound levels recorded are the accumulation of background sounds (external sounds, sound-producing installations, and equipment in the learning space) and activity sounds (physical and vocal sounds produced by pupils and teachers). Interpretation of the sound data is done based on three informed assumptions:

The Field Experiment Variables

A change in the sound level recorded is the result of a change in activity sounds. Background sounds in learning spaces keep relatively constant during normal circumstances (see section 2.3.1). If variations are present in the averaged sound data, these can therefore be attributed to a change in vocal and physical activity of pupils or teachers – unless observed otherwise. A lower measured sound level implies that pupils were either talking less, less loudly, would move less, or would move less objects around, any of which would indicate that the pupils’ attention was on the learning instead. A higher sound level suggests the opposite; more distraction from or less attention to the learning. In order to meet this premise, effort was made to keep the background noise consistent during the experiment in three ways: (1) by keeping the sound-producing installations and equipment in place; (2) by regularly inspecting the direct surroundings of the school for significant changes that could change the background noise. For example, a significant change in traffic flow due to road works or start of renovations work to a neighbouring property. (3) by recording significant and unexpected sound interruptions during class on an observations template. To gain insight to whether the background noise in the four learning spaces is similar and its quantity, sound levels were also recorded for two 15-minute timeslots: once around 7am, about an hour before the school would start, and once around 10pm when the school would close. Very few to little human activity took place during these timeslots. The recorded levels therefore were considered to be representative of the background sound from apparatus and building installations as well as external sounds from the surroundings. All activity sounds are considered unwanted noise during the focussed learning activates. Subjectively such interpretation will differ between pupils; each of us have different thresholds and interpretations to what type of sound and at what level it is experienced as noise, and what is not. However, for this research, the total measured sound level is equated to be experienced as noise. Or in other words, during focussed-learning activities all sounds are considered distractive noise. A lower measured total sound level is considered a less noisy learning space, which provides for better environmental condition for pupils to

5.3.2

Study II: Disruptive Pupil Behaviour

This study looks for noticeable, or observable, changes in three types of disruptive pupil behaviours during focussed-learning activities while they are exposed to either of the two artificial light pattern typologies: 1. Non-learning related expressive behaviours – these are externalized expressions not specifically directed at someone nor relevant to the learning. These behaviours are signs that a pupil is not engaged with or focussed on the learning task at hand. Some of these may also be experienced as an annoyance to others. The three type of expressive behaviours specifically looked at in this study are (section 2.3.2 for references): •

talking out loud but not at or with someone, noise making such as grinning, groaning or sighing.

•

displays of fidgetiness or restlessness such as wobbling on a chair, playing with objects.

•

displays of daydreaming, sleepiness, resting down on a table surface. These are not necessarily disruptive to others, but suggestive of disengagement with one’s own learning.

The premise is that when pupils display less externalized expressive behaviours, they are more engaged with their learning – and less disturbing to themselves and others.

The Field Experiment Variables

The interpretation of the sound data was also informed by an important characteristic of sound intensity: it is a logarithmic measure in decibels dB(A). The dB(A), or A-weighted decibel unit, is based on powers of 10 to provide for a manageable range of numbers to encompass the wide range of human hearing. Generally, sound intensities in the built environment range from 25 dB inside a quiet house to 100 dB for loud crowd noise. What is important is that, due to this logarithmic scale, a change in sound intensity of 1 dB(A) is considered a little more than the perceptive threshold, indicated as the just noticeable difference (JND). A difference of 5 dB(A) is perceived generally as twice as loud or quiet and is considered a significant change. The normal conversation range in learning environments is between 50 and 70 dB(A) (Sala & Rantala, 2016). A room with highly concentrated pupils working on their own would be close to 50 dB(A), while general classroom chatter would near 70 dB(A). For this research it was anticipated to find relatively small changes in sound level (if any) between just noticeable and significant difference, or between 1 and 5 dB(A).

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concentrate with less aural distractions. A higher sound level suggests the opposite; less supportive conditions for pupils to concentrate on their learning.

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2. Non-learning related social behaviours – are externalized interactions that take place between pupils, or a pupil and teacher, that are not relevant or beneficial to the learning. The three types of these disruptive social behaviours looked at in this study are (section 2.3.2 for references): •

shouting out or waving arms to attract a teacher’s attention instead of quietly raising a hand.

•

seeking contact or interacting with peers nearby, for example seated at the same table, in a way that has no relevance to the task at hand such as for instance chatting, joking, elbowing.

•

seeking contact with peers further away, for example seated at another table, that has no relevance to the task at hand. Or even with peers outside the classroom, for instance by signing behind or knocking on a window.

The Field Experiment Variables

The premise is that when less irrelevant social interactions take place; lesser disruptions occur to one’s own or others concentration. This will be especially evident when less unnecessary interactions take place between pupils seated far apart instead of between directly neighbouring pupils. Local interaction has less potential for disruptive loud talk or shouting than when needing to travel across the learning space; 3. Physical (or out of seat) behaviours – refers to any movement of a pupil up and away from their place that is unnecessary for the learning task at hand. The three physical behaviours looked at in this study are (see section 2.3.2 for the literature references): •

needlessly wandering around.

•

needlessly changing seats or location in the room.

•

repositioning (their own or others) seats and/or desks.

The premise is that if pupils stay seated and move around less, the more they are engaged with their learning, and are less disturbing to themselves or others. This may positively affect pupil’s concentration. It should be highlighted this excludes all necessary or normal physical activities such as getting up to visit the toilet, approaching the teacher or a peer to discuss the learning task at hand, or a need to take a tool or stationery from a cupboard. These forms of physical movements are considered necessary regardless of the educational circumstances (toilet visit), or are simply indispensable to the learning (using the right learning tools or equipment). The occurrence of these type of movement activities are unlikely to change due to a different lighting scenario.

Data Collection Methods

Semi-structured individual interviews. Interview research is essentially a way of collecting qualitative information by questioning a person or small group of persons (Wertz et al., 2013). In semi-structured interviews the interviewer does not strictly follow a formalized list of questions, but will ask more preprepared open-ended questions, allowing for a discussion with the interviewee rather than a straightforward question and answer format. These interviews took place with the respective teachers in charge of each sessions observed afterwards. To allow to revisit these interviews while analysing the notes, each interview was also voice recorded (with permission).. Focus groups. These are in essence interviews conducted by the researcher with a group of participants who are asked about their opinions or perceptions about a particular topic. Generally, the environment is interactive, and the participants are free to discuss with each other. The interviewee acts more as a moderator. However, to guide the focus group sessions, a set of questions was prepared to discuss. The focus groups in this experiment took place twice with a small group of pupils, and twice with all six teachers involved. Notes were taken during each session, and each was voice recorded.

Guiding Templates Each of these studies (observations, interviews and focus groups) were guided by pre-defined templates that directed the attention of the researcher / interviewee towards the three types of disruptive behaviour. The design of the templates was done as suggested by Creswell (2009). The three templates were informed by the three types of externalized behaviours described in the previous section. Further details on these templates see sub-section 7.2.

The Field Experiment Variables

Non-participant observations during class. Observational research is a way of collecting data by observing naturally occurring events, situations, settings, behaviours, and other social phenomena as they occur, and taking notes of these (Wertz et al., 2013). When also observing and describing the context in which the subject of interest (in this research pupils’ behaviour) takes place, it provides for the possibility to look at the relationship between context and that subject. In non-participant observations one watches the subject(s) of interest, but without taking an active part in the situation under scrutiny. These observations took place during twelve pre-selected focussed learning sessions, distributed equally per learning space. To allow to revisit these sessions while analysing the observational notes, each session was also video recorded.

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To collect data on these three types of disruptive pupil behaviours, three qualitative research methods were used:

Data Interpretation

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The data collected through observations and interviews was processed following the method of thematic analysis as described by (Braun & Clarke, 2006): “… a method for identifying, analysing, and reporting patterns (themes) within a data set”. These themes need to be associated with the specific research question(s) and translated into categories for analysis. They also describe thematic analysis to be an analytical method in its own right, but to share similarities with others. One comparison is made with grounded theory but suggest that it’s a rather “light” version thereof. The reason for choosing this method to analyse the data set is firstly that it does not require detailed theoretical understanding and technological knowledge as most other methods require. The secondly reason is that thematic analysis can be used without the commitment to theory development such as the grounded theory approach, nor is it bound to one particular theoretical framework. The process of interpreting the collected data following the thematic analysis method is discussed in section 7.2.

5.3.3

Study III: Cognitive Performance

The Field Experiment Variables

This study looks for a direct change in pupils cognitive performance by means of two specialized tests, administered while the pupils are exposed to either of the two artificial light patterns.

Data Collection Method Performance tests. Pupils were subjected multiple times to two specialised performance tests. Their test results were compared and related to the lighting conditions under which these took place. These were always within-subject comparisons in order to eliminate any bias due to individual diﬀerences in the ability to perform schoolwork. The premise is that pupils would score better on these tests whilst being exposed to the pools-of-light conditions, if this would reduce distractive behaviour and lessen noise. The tests are: •

A standard addition test—the pupils had to add two three-digit numbers, as many as possible within a set timeframe.

•

A figural creative thinking test—the pupils had to drew as many objects or pictures as they could imagine using the lines and circles provided within a set timeframe.

The first test is considered a quantitative exercise, while the second test has a rather qualitative nature. Both tests were designed by Aarhus University to assess pupil’s cognitive performance in terms of ability to concentrate while doing mathematical addition exercises and conducting a creative task. The setup of study (III) was modelled on earlier work where the tests were used to relate indoor climate factors and cognitive performance (Petersen et al, 2016).

The tests were administered during normal curricular hours, but during another time interval than study (I) and (II). There are three reasons why studies (I), (II) and (III) did not run simultaneously:

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Timing

1. Attaining written approval of all parents for their children to partake in this test-based study proved to be more time consuming than anticipated. 2. The teachers considered study (III) to have a greater impact on the pupil’s than study (I) and (II) as it intervenes with their normal study program by adding an extra task to do. It was therefore requested by the school to not run the three studies during the same period.

In consultation with the school, it was hereto decided to perform study (I) and (II) first and run study (III) in a follow-up period. An incidental advantage of this setup was that some of the learnings from study (I) and (II) could be used to inform the design of study (III), for example which intervening variables to study concurrently. This led to simplification of the research design.

5.3.4

Data Collaborations

To ensure appropriate quality of data collected and analysis thereof was done correctly for each of these three studies, three types of external “experts” were consulted

* https://ufm.dk/forskning-og-innovation/ forsk2025/indkomne-indspil/netvaerk/ innovationsnetvaerket-dansk-lyd

•

Acoustic experts from the department of Architectural Acoustics at the Technical University of Denmark (DTU) were consulted on the sound measurement and data analysis thereof. A successful joint application to Dansk Lyd * (Danish Sound) provided funding for a research assistant and for the use of four professional sound meters to record the sound levels in the four learning spaces during the experiment. The assistant helped with appropriate setup of the equipment, and the analysis of the raw data collected by translating it into an operational format. Further details on the data collection protocol and analysis thereof are discussed in section 7.1. The collaboration resulted in the publication of a paper and a presentation at EuroNoise 2018 (Mil, 2018).

•

To gain experience with observing pupils in classroom settings and interviewing teachers before conducting the actual field experiment, collaboration was sought with two Master students from the program: Applied Cultural Analysis of Copenhagen

The Field Experiment Variables

3. The school preferred to exclude the younger pupils at first level from the testing study as the school’s pedagogy does not support such testing activities yet at this age.

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University. These students had been trained in ethnographic research methods in real work, study and healthcare environments. Together a research project was developed, titled: Light & Learning Environments: a cultural analytical exploration of light in learning environments as a social phenomenon (Barney & Sørensen, 2016) This project included jointly conducted interviews and observations in two schools in Copenhagen (Ørestad Skole and Frederiksberg Gymnasium). This collaboration provided for valuable insights in how to act as an (non-intrusive) observer in a learning setting, and how to design and use a template to direct the act of observing. As well as how to conduct a semi-structed interviews with teachers, who are not necessarily familiar with discussing the topic of light and extract relevant information. •

To support the cognitive testing, collaboration was also sought with the Indoor Climate and Energy research group of Aarhus University, who had prior experience with these tests. Further details on the design of the study and tests are presented in section 6.3.2.

The Field Experiment Variables

5.4

Intervening Variables

The field experiment takes place in a real-life school environment, where many other variables than the treatment variable of interest (artificial light pattern) could influence pupil behaviour and performance too. Their interference could complicate the interpretation of the collected data and herewith the validity of the research. Fourteen variables were identified as potentially intervening in this field experiment. These variables surfaced during a literature review of associated field experimental studies (Chapter 2). These variables have been categorized into five groups: •

Group 1: Architectural variables: spatial geometry (1), floor layout (2), and window design (3).

•

Group 2: Interior variables: furniture (4) and decorations (5).

•

Group 3: Indoor climate variables: light (6), sound (7), temperature (8), and air quality (9).

•

Group 4: Subject variables: pupils (10) and teachers (11).

•

Group 5: Activity variables: curricular task (12), timeslot (13), and unexpected interruptions (14).

In order to exclude the influence of these fourteen potentially intervening variables, these had to be either neutralized in the setup of the experiment, controlled for or measured during the experiment. Different research methods have been used to collect

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data on these variables, resulting in a mixed method design that included both quantitative and qualitative methods. Figure 5.5 provides an overview of the methods used per variable group. The following five sub-sections describe the potential risk of each intervening variable and the respective research method applied.

(1)

architecture

(2)

observations (site visits)

observations

daylight, temp, air recording (3)

climate

digital simulation online tracking observations Spring 2017

(4)

subjects

interviews observations

(5)

activity

observations video recording time registration

Figure 5.5 Diagram of the intervening variables groups and respective research methods

5.4.1

Architectural Variables

Three architectural characteristics of a learning space were identified to impact pupil behaviour (see section 2.4.3).: spatial geometry (1), floor layout (2) and window design (3). To neutralize potential interference from significant architectural differences for these characteristics between spaces, it was key to find comparable learning spaces that would be physically similar. The assessment of comparable learning spaces took place in two stages: (1) Review of architectural documentation, and (2) Observational site visits.

* https://www.radiance-online.org/

Review of architectural documentation. This was done together with one of the architects who co-designed the building. This allowed to review architectural comparability in terms of general layout, geometry, and materials of all learning spaces in the host school (Frederiksbjerg Skole). In addition, computer simulations with Radiance * were performed to predict the natural lighting conditions in the various areas of the school. These studies allowed to arrive at a pre-selection of ten potential host spaces.

The Field Experiment Variables

interfering variables

interior

architectural documentation

Autumn 2016

Research method

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Observational site visits. These ten preselected spaces were further examined during site visits in November and December 2016. These allowed to assess and compare the architectural appearance of the spaces in person, and to assess two of their interior characteristics that could not be read from the architectural documentation: the applied (wall) colours and finishes. These visits also gave the opportunity to be informed about the use of each space and included talks with the school’s head and respective teachers to gather information about who was occupying the respective space, what kind of activities were taking place, and what (curricular) schedule was adhered to. These learnings also informed the appointment of the experiment’s spaces. See section 6.1 for details. Another important aspect of the site visits was also to probe for and cultivate willingness amongst the teachers to participate in the experiment.

The Field Experiment Variables

The outcome of these assessments was the appointment of four learning spaces with comparable architectural features. Hereto this group of variables could be excluded as intervening. It was also ensured the spaces selected were used by similar pupil groups and hosted comparable curricular activities; see for details respectively section 5.4.4 and 5.4.5. The learning spaces selected are further described in section 6.1.

5.4.2

Interior Variables

There are several interior design characteristics that have been found to affect pupil behaviour (see section 2.4.3). Two of these were identified as potentially intervening in this experiment. The first interior characteristic is the furniture (4). This includes all the seating and working desks that are used by pupils, particularly during focused-learning activities. Significant changes to the furniture type and their arrangement, for example placed closer or further apart or in bigger or smaller groups, could alter pupils’ social and physical behaviour especially. The second characteristic concerns decorations (5). These are non-fixed objects or elements such as posters, paintings or artworks as well as loose objects (other than furniture) such as cabinets, shelving, and cupboards. In contrast to the beforementioned architectural characteristics, both these characteristics could be changed or rearranged by the users of the spaces during the experiment and therefore had to be monitored for change during the experiment. Observations before class. To exclude potential interference of these two interior variables it was chosen to firstly pre change by making pre-experiment agreements with the teachers on the interior setup of their respective learning space, and to keep these in place for the duration of the experiment. But as these agreements could not be enforced, changes to the furniture layout and décor could still occur. Hereto, both variables have been monitored by reviewing these in person at regular time intervals during the experiment,

5.4.3

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alias by the method of observing. These timings coincided with the observational studies on the pupils. The observation template, which was used to structure these pupil observations, therefor also included a specific box to note observed changes to the decorations and furniture. Photos were also taken in each learning space from three predefined positions to be able to compare the status of the interiors throughout the experiment.

Indoor Climate Variables

Natural light Light in learning spaces is generally the combination of natural (during daytime) and artificial light (if activated). Together these two components define the lit appearance of a space, for example whether it appears bright or dim, contrastful or plain, uplifting or bleak. The interest of this research goes out to explore potential impact of a deliberate change to the artificial light component. In order to study its effect, it is critical that the natural light component remains steady (unchanged). But natural light is dynamic by nature, and its expression inherently varies over time of day and season. It is also affected by the weather; an overcast sky compared to a sunny sky will bring about a different natural light appearance indoors. The manifestation of natural light is also dependant on the window blind settings. Closed blinds reduce the presence of natural light indoors significantly. These three characteristics may cause for diverse manifestations of the natural light in the four learning spaces and were therefore studied and monitored. Prior to the experiment, a digital simulation study allowed to gain some fundamental insight into what may be expected as the average amount, reach and variation of natural light, including daylight and sunlight, into the learning spaces. These simulations are predictive studies of natural light. The actual, real-time behaviour of the natural light during the experiment was also monitored. This was done by three methods: real-time light level measuring, weather condition monitoring, and observing the blind settings.

The Field Experiment Variables

Research related to the field of environmental psychology evidenced that each of the indoor climate variables – (6) light, (7) sound, (8) temperature and (9) air quality – may affect pupil wellbeing, behaviour or general functioning (see section 2.4.3). These variables could potentially thus interfere with and complicate interpretation of the data. These variables can however not be controlled as these in part are naturally occurring phenomena. Hence monitoring their (quantitative) levels during the experiment was considered important. The methods used to collect this data are described in the next three sub-sections.

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Digital simulation. Three types of simulations were done based on a CIE overcast sky or local weather data: daylight factor (DF), useful daylight illuminance (UDI), and sunlight penetration. These studies allowed to gain insight into the relative weight of natural light in the overall lit appearance that may be expected for the four learning spaces (which is the accumulation of natural and artificial light). Their results were mainly used to appoint which learning spaces would be suitable and comparable amongst each other to host the experiment (see section 6.1.4).

The Field Experiment Variables

Real-time light level recording. The light intensity inside the four learning spaces was recorded real-time with two light recorders per space. Each recorder measured light intensity in their respective field of view per 10 second time intervals throughout the entire duration of the experiment. Recorder 1 was placed in an east-facing windowsill located circa halfway up the wall. Its sensor was positioned horizontally so that it was looking up to the sky. This sensor registered predominantly the intensity of daylight (and potentially sunlight) entering the learning space. Recorder 2 was suspended from the ceiling at about the centre of each learning space. Its sensor was facing towards the window façade. This sensor registered both the accumulated light intensity in its field of view; in this location both the artificial and natural light would coincide. For details on the light sensor technology and exact positioning of the sensors per learning space, refer to Section 6.3. Weather monitoring. Tracking the local weather or sky conditions provides for insight how the natural light behaved over time. If the weather varied significantly, the natural light expression did too. In this case, it may act as an intervening variable. Local weather conditions were tracked for the duration of the experiment, from 22 February until 5 April 2017 for Central Aarhus per 6-hour timeslots. Data was collected from: www.dmi.dk (Denmark’s national weather institute). The weather conditions provided would range between three different types: cloudy, semi-cloudy, or clear sky conditions. In addition, an extra light intensity recorder had been placed on the rooftop of the experiment’s school building, with the sensor looking up to an unobstructed sky. This sensor registered the outdoor real-time light intensity. Together with the weather data from DMI, the behaviour of natural light during the experiment could be mapped and analysed for significant variations. Observing the blinds. The blind settings during class were monitored firstly, by the observational researcher each 15-minute time interval in the learning space the o. Descriptions thereof were noted down on the observational templates, and a time stamp noted down when the blinds would drop or rise. To document an impression of the conditions a photo was taken from one of the learning space’s windows directly before and after an observational session. As only few sessions could be attended to in person, the video records of the non-observed sessions were consulted.

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Changes to the blind settings were time stamped. The collected data from these blind setting observations (both in real-time and from video records) together with the data from the real-time light level recordings and monitored weather conditions provided for insight how the natural light had behaved during the experiment. The premise being that if this behaviour appeared to have been relatively stable, it would not be considered an intervening variable.

Sound level measuring. Sound, or noise, has been appointed an outcome variable for pupil behaviour and concentration and is monitored with specific sound measuring equipment. See section 5.3.1 for technical details. The collected sound data is primarily used to analyse whether significant differences occur, while pupils are exposed to two different artificial light patterns. However, in support of the appointment of comparable learning spaces to host the experiment, some of the sound data was also utilized to assess whether background sound levels were similar between these spaces. Hereto, early morning and late evening sound measurements were done when very little human activity was taking place in the school and the averaged sound levels.

Temperature and Air quality Temperature, CO2 and humidity recording. Various researchers uncovered that a rise above or fall below the respective comfortable thresholds for room temperature and air quality negatively impacts a pupil’s mood, behaviour, and performance (see chapter 2). To rule out that these variables were influencing pupil behaviour during the experiment, both have been monitored for each learning space with two temperature sensors and sensors for carbon dioxide and humidity. For details on the sensor technologies and their placement, see Section 7.1.

5.4.4

Subject Variables

In total ten groups of about 25 pupils each, and six teachers were included in the field experiment. The composition of each group, including the teacher, was to remain unchanged during the experiment. Therefore, the group composition was monitored during the experiment.

Pupils Because each group was exposed to the experimental and the standard conditions of the experiment; within-group comparisons were well possible if the group didn’t significantly change. To be able to also make between-groups comparisons, the composition of the groups had to comparable. Hereto each group was assessed to comply with three demographic requirements: (1) a relatively

The Field Experiment Variables

Sound

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similar number of pupils per group; (2) a fairly equal distribution of sex; and (3) an age between 6 and 12 years old. Prior to the experiment this data had been provided by the administration for the ten groups. The ten groups included were all assessed to meet these three criteria. Interviews. In addition, short sit downs with each teacher prior to the experiment commended provided for insight if any of the groups included pupils with significant learning disabilities or abnormal behavioural issues that impacted the general behaviour of a group significantly. This may render the group incomparable to other groups. None of the groups were described to fall into this category and were therefore considered normal functioning groups. To ensure the demographic stats also upheld during the experiment, changes to the group composition were monitored. Before each observational session a short talk with the teacher was used to be informed about any absentees or new pupil(s), or other significant changes in the group that could distort the recorded noise and observed behavioural data.

The Field Experiment Variables

Teachers The six teachers partaking in the experiment were adhering to the same curricular program. But naturally each teacher would have their own personal approach to teaching, classroom management strategies and threshold for disruptions. The same pupil group could therefore display different behaviour depending on the teacher conducting their teaching. Comparison of data collected for the same group and teacher would allow for association. However, comparing data collected between different teachers could be more complicated. This required to assess whether the ‘teacher’ as a variable could be neutralized. Interviews. Each teacher was interviewed about his/her approach to their teaching prior to the experiment. This allowed to gain some objective insight into their personal approach and strategies. These findings were further detailed with help of observations. Observations during class. Prior to the experiment two pilot-study days took place during February 2017 (see section 6.3.1). These allowed to attend a class of each teacher and observe their approach in action without collecting yet data. The data collected with both methods indicated that although differences between the teachers were evident, for example their ways of communicating with pupils and strategies for addressing disruptive behaviour, all expressed and adhered to similar key values: to keep order, to pay attention to each individual pupil, and to address disruptive behaviour quickly. They also appeared to structure their class similarly: starting with a brief introduction to

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the task for that class, time for pupil to perform the task, and to wrap up with a summary. Hereto is was decided the individual teacher would not be considered a significant intervening variable. Noise, behavioural and performance data could be compared regardless of the teacher present during the collection. In addition, it was considered important that the six teachers remained in place during the experiment and were not substituted by a different teacher. This to avoid such change affecting pupil’s behaviour. To monitor their presence in each session, the name of the teacher was noted down for each attended observation session on the respective template. The remaining sessions, those not observed in person were reviewed from their respective video records.

Activity Variables

As described in section 5.2.3 the intent for the field experiment is to study pupil behaviour related to concentration specifically during focused-learning activities. These are considered activities that rely on pupils undisturbed attention for the task at hand such as reading, writing, language and mathematic exercises. These curricular activities may take place individually or in small groups, and generally thrive in relatively quiet and undistracted environments. The predefined schedules for each learning space provided for insight into which curricular topic would be addressed during what timeslot, and to filter out those fitting the description beforementioned. Although this seemed a plausible way to select comparable activity timeslots in theory, this may differ in in practice. During the site visits in November and December 2016, and pilot studies in February 2017 it namely became clear that the actual activities and pupil’s engagement herewith could differ slightly, for example per activity type and time of day. Hereto possible deviations from the schedules had to be taken into account, both in terms of type of activity as well as the timing thereof.

Variation in Activities Although the schedule would indicate pupils would engage in a certain curricular activity, the actual task at hand in that timeslot could vary to a degree. In some session’s pupils would collaborate often together, while others required more individual practice. Some would require pupils to work on paper-based materials, while others mostly on digital equipment. Such differences could prevent certain sessions, and for the data collecting during, to be compared.

The Field Experiment Variables

5.4.5

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Observations during class and video recording. As these differences were not possible to predict beforehand, it was decided to observe and record videos of the appointed observational sessions. For details about the sessions appointed, see Section 6.3.1. By revisiting these observational notes and videos, it was possible to define of which sessions the activities were deemed focussed-learning activities and sufficiently comparable. This allowed to exclude certain sessions from further analysis, which were those sessions that included exercises with relatively heavy collaborative interactions and consultation amongst pupils.

Timing of Activities

The Field Experiment Variables

The focused-learning activities could take place during the early morning, late morning or early afternoon timeslots, and on any school day of the week (see section 3.2.3). During pre-experiment talks in November and December 2016 with the six teachers, some addressed they observed that pupil’s general mood could change depending on the time of day or weekday. During early morning sessions pupils would generally be relatively exited and energetic, while after lunch often rather sleepy. On Mondays they would be more enthusiastic while on Fridays their willingness to cooperate diminished. Herewith saying that when studying pupil behaviour, such variations would be likely to occur. Observations during class and time keeping. In an attempt to limit these impacts, observational visits during class would be limited to two consistent weekdays that were found most stable and predictable, and of which the curricular schedule would feature relatively good opportunity to encounter focused-learning activities. These days were: Wednesday and Thursday. In addition, the observational template included a box to note down a general impression of the pupils’ mood, which was at the end of a session verified with the respective teacher.

Unexpected Interruptions Besides changes to the group of pupils, teacher, activity, or mood, other unexpected interruptions could manifest. For instance, abnormal loud noises from outside, malfunctioning of a building system or teaching equipment, external visitors invading the learning space, pupils being expelled during class, extra assistant teacher to be present, maintenance work during class, etc. Observations during class and video recordings. All of the unexpected or abnormal interruptions were noted down on the observational template during those sessions attended by the researcher. Or identified when reviewing the video recordings of all sessions.

1. Architectural Variables

Chapter 6 Prior to experiment 1. Spatial Geometry 2. Floor Layout 3. Window Design

2. Interior Variables

3. Indoor Climate Variables

4. Furniture

Similarity of overall dimensions and proportions. [Architectural plans, visual assessment.] Similarity of learning space areas, central working area. [Architectural plans, visual assessment.] Similarity of orientation and arrangement. [Architectural plans, visual assessment.] Similarity of desks and storage units. [Visual assessment.]

5. Decorations

Similarity of color schemes and finishes. [Visual assessment.]

6. Natural Light

Similarity of DF, UDI, Sunlight Penetration. [Computer simulations.] Similarity of visual appearance. [Visual assessement, interviews with teachers.]

7. Ambient Sound

8. Temperature

9. Air Quality

4. Subject Variables

5. Activity Variables

10. Pupils

Similarity or negligibility of ambient sound. [Visual and aural assessment of acoustic properties.]

Chapter 7 During experiment Format agreed with teachers for continuity. Visual inspection once every field day and test day in four spaces. Format agreed with teachers for continuity. Visual inspection once every field day and test day in four spaces. Manual lux-mapping of light scenarios during day and night in four spaces during each field-day pair. Lux-level measured for continuity and similarity in window and middle of four spaces. Recorded at 10 sec intervals throughout the experiment with HOBO sensors in four spaces and for callibration with one pair of more advanced LI-COR sensors in one space only. Sky conditions for continuity and similarity between field days. Assessment of DMI weather records and visual assessment during observations study II. Blind position for continuity. Assessment of time-lapse recordings in four spaces. Sound level measured during pilot in four spaces to confirm assessment. Values comparable and negligible compared to classroom noise.

Small changes were corrected prior to field days. No effect. Small changes were corrected prior to field days. No effect.

See comment below.

The sky conditions and corresponding indoor lighting led to the exclusion of one session for two spaces. Blinds were continually open. No effect.

Temperature measured for continuity and agreement with comfort criteria. Values remained within bounds. No Recorded at 5 min intervals effect. throughout field experiment in four spaces. Air quality measured for continuity and agreement with comfort criteria. Recorded at 2 min (CO₂) and 5 min For field days, values remained (RH) intervals throughout field within bounds. No effect. experiment in four spaces. A CO₂ peak was recorded outside the field days. Similarity of pupil age. [Age groups are Group size observed for continuity. Number of people in central area constant for each floor. School-aged Confirmed through follow-up interviews varied and was counted for each children are on first and second floor.] with teachers. session.

11. Teachers

Similarity of teachers. [Interviews with teachers.]

Teacher observed for continuity. A check took place on field days whether Teachers stayed with their groups. No regular teacher was present. effect.

12. Curricular Task

Similarity of task. [Focused-learning activities only.]

Selection of timeslots with specific focussed-learning activities.

13. Timeslot 14. Interruptions

Preference for comparisons between timeslots with the same task type. Preference for comparisons between learning sessions at same time of day.

Interruptions monitored during observations study II.

Figure 5.6 Overview of the role each intervening variable played in the field experiment

Analysis

No significant external or classroom interruptions occurred. No effect.

The Field Experiment Variables

Chapter 5

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The role that each of the fourteen variables played in the setup of the experiment (discussed in chapter 6), or during the collection and analysis of the data (discussed in chapter 7) is summarized in Figure 5.6.

5.5

Summary

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This chapter discussed the methodological foundation of the experimental field study that was performed in a real-life Folkeskole (Frederiksbjerg School) in Denmark to establish if the artificial light pattern – the treatment variable – influences pupils’ behaviour and performance – the outcome variables of the experiment. To avoid data contamination, fourteen potentially intervening variables were identified, and either neutralized in the setup of the experiment, or monitored for significant change during the experiment. Treatment variable – During the experiment pupils were alternately exposed to two types of light patterns in their learning spaces: (A) standard situation that is characterised by a uniform artificial light pattern, and (B) an experimental situation that is characterised by a non-uniform pools-of-light pattern.

The Field Experiment Variables

Outcome variables – While the pupils were exposed to either of the two patterns, data was collected about their behaviour and performance by means of three data collection studies labelled: (I) noise during class, (II) disruptive pupil behaviour, and (III) cognitive performance. Studies (I) and (II) are aimed at finding perceptible differences in pupil behaviours that directly affect quietness in the learning environment, while study (III) looks for statistical learning improvements suggesting effects in pupils’ concentration. Intervening variables – Five groups of potentially intervening variables were identified and described: (1) architectural variables, (2) interior variables, (3) indoor climate variables, (4) subject variables, and (5) activity variables. The architectural variables were neutralized by finding comparable learning spaces to host the experiment. These did not require further observation during the experiment. The other variables were to be monitored for (significant) change during the experiment. Some of these variables also informed the analysis of the collected data. The following will further detail how the various research methods were brought together into a comprehensive research design.

The Field Experiment Variables

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The Experimental Context, Setup and Design

This chapter discusses the implementation of the various data collection methods discussed in chapter 5 into a comprehensive research design. Hereto it describes the practical context of the field experiment, and the process of securing four representative learning spaces to host the experiment. The experimental lighting installation used to expose pupils to both the standard, uniform light pattern and the experimental pools-of-light pattern is detailed, as well as the considerations and various analyses that were performed in order to arrive at a research protocol that allowed to collect all necessary data consistently during the experiment.

Section 6.1 describes the research context that hosted the field experiment, namely four learning spaces of the newly built Frederiksbjerg Skole in Aarhus (DK). The process of selecting the four learning spaces is elaborated on, which was important as the aim for the selection was to pinpoint comparable spaces that would neutralize a number of the intervening variables described in section 5.4. Comparability would reduce the number of remaining variables that had to be monitored during the experiment and accounted for in the analysis. Section 6.2 describes the experimental lighting system that was designed for and temporary installed in the four learning spaces, that allowed to expose pupils to the two different artificial light patterns: (A) the standard uniform pattern, and (B) the experimental pools-of-light pattern (B). The experimental lighting system ensured teachers could teach under normal conditions, but also allowed to activate the experimental light pattern, pools-of-light, when wished for. A description of the luminaries, controls, and the installation process is provided. To confirm the validity of the original design assumptions for both light patterns, a detailed analysis of the different pattern expressions is provided. Section 6.3 provides a detailed protocol to execute the three studies related to the three outcome variables: (I) noise levels during class, (II) observable disruptive behaviours, and (III) including the monitoring of intervening variables. Due to the ongoing teaching in the school, planning the experiment has been a critical aspect of its implementation. Studies I and II were performed in the spring semester, and study III in the autumn semester of 2017. Section 6.4 provides for a summary of the chapter.

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THE EXPERIMENTAL CONTEXT, SETUP AND DESIGN

The Experimental Context, Setup and Design

6.1

The Experiment’s Learning Spaces

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The field experiment was undertaken in Frederiksbjerg Skole in Aarhus (Figure 6.1). Frederiksbjerg Skole featured a fitting pedagogical context and architectural setting to host the experiment. This school has been visited during the site visits and is described in chapter 2. Henning Larsen Architects’ involvement gave an opportunity to understand the building from a designer’s point of view and see the building in use. Thereby, the school management had expressed its willingness to cooperate with the experiment early in the process.

The Experimental Context, Setup and Design

The school adheres to the folkeskole pedagogy and is one of the first to have been built following the 2014 reform as described in chapter 2. The architectural vision for this building was to provide pupils and staff with an environment that would allow the new reform ideals to unfold well. From personal discussions with staff and following the various nominations and awards the building has received, the building is well received by staff, pupils, local community and the professional community.

Figure 6.1 Frederiksbjerg Skole, view of the west and north-facing facades (photo credits: Henning Larsen)

The experiment took place in two pairs of Frederiksbjerg Skole’s learning spaces while they were used as normal. One pair is located on the first floor and one pair is located on the second floor. Both pairs are located in the north-east corner of the building and positioned directly above each other: •

Rooms L1.01 and L1.02 are located on the first floor and each room is occupied by one group of pupils aged 7 to 9 (Figure 6.2). The groups spend most of their curricular hours in their space while undertaking a broad palette of curricular activities.

•

Rooms L2.03 and L2.04 are located directly above on the second floor (Figure 6.3) and host 90-minute mathematics sessions that are attended by ten different pupil groups aged 10 to 12. The groups rotate these spaces according to a weekly schedule.

p. 139 Room L1.02

Figure 6.2 First floor: Room L1.01 and Room L1.02

Room L2.03

Room L2.04

Figure 6.3 Second floor: Room L2.03 and Room L2.04

These four spaces were selected because they were assessed to be comparable with regards to a number of the intervening variables described in section 5.4. As described in that section, each of the in total fourteen identified intervening variables were assessed if they could be neutralized in the setup of the experiment. If not, these controlled for and measured during the experiment. The three architectural variables, spatial geometry (1), floor layout (2), and window design (3) were successfully neutralized by selecting learning spaces that could be considered to have a “similar expression” with regards to those respective variables. These similarities neutralized potential interference from the architectural variables, and it helped keeping some of the interior (group 2)), subject (group 4) and activity (group 5) variables constant as well. However, because this experiment did not take place in a fully controlled laboratory setting, inherently there would still be differences between spaces and between the conditions under which the experiments were conducted. Some of the intervening variables are also interrelated. For example, pupils use certain learning spaces in the building based on their age. Therefore, this chapter section is organised following a practical interpretation of the variables classification presented in section 5.4 and explains the selection and comparability of the two pairs of spaces based on six characteristics: pupil age (6.1.1), spatial organisation (6.1.2), interior design (6.1.3), acoustic properties (6.1.4), lighting conditions (6.1.5), and curricular schedule (6.1.6).

The Experimental Context, Setup and Design

Room L1.01

6.1.1

Pupil Age Groups

The age range of pupils attending Frederiksbjerg Skole ranges from 3 to 16. Pupils are grouped according to their year of age. p. 140 The Experimental Context, Setup and Design

•

The ground floor hosts children between 3 and 6 years old. These are pre-schoolers and attend a day care facility. This facility is not yet considered part of the school curriculum and functions independently. The ground floor also hosts administrative and technical spaces, as well as several open spaces such as a large atrium, play zones and a lunch area.

•

The first floor hosts pupils aged between 6 and 9 years old. Each group contains about 22 to 26 pupils of mixed ages and occupies one designated learning space. In these spaces a broad palette of curricular activities take place, some of which may benefit especially from (an improved) capacity to concentrate. Commonly, an activity lasts between 45 and 90 minutes. In between are scheduled breaks during which the groups leave their designated space and attend other indoor and outdoor communal spaces and play facilities. The composition of each group is fairly consistent throughout the school year, and their weekly curricular schedules are comparable to one another.

•

The second floor hosts pupils aged between 9 and 12 years old, who are grouped according their year of age. Each group contains about 22 to 26 pupils of circa 9–10, 10–11 or 11–12 years old. The composition of each group remains fairly consistent during the school year. On this floor the formal learning spaces are clustered into four sections, each dedicated to one of four curricular topics: languages, sciences, mathematics, and history and geography. Groups here spend commonly 90-minute sessions in one learning space, and rotate spaces and sections according to a weekly schedule. Some sections, and their respective curricular activities, may benefit particularly from an improved capacity to concentrate.

•

The third floor hosts pupils between 13 and 16 years old, who are loosely grouped according to their year of age. Similar to the second floor, learning spaces on the third floor are clustered per sections, and each space hosts 90-minute curricular sessions. A difference is that pupils here are not bound to one group. They have some autonomy to elect certain subjects to focus on, and therefore these pupils follow rather individualized curricular programs. As a consequence, there is significant variation in which pupils attend what classes, and where. Tracking steady pupil groups appears rather complex.

•

The age of pupils taught on the first and second floor falls within the same child-development category of: childhood (Guerra et al., 2012). This category generally refers to children aged between 6 and 12 years old. Sitting in the same developmental category implies pupils exhibit comparable social, emotional, and cognitive developmental steps. Guerra et al., (2012) states this allows for some general comparison of behaviour. This is in contrast to pupils on the ground floor, who belong to the category: pre-schoolers (3 –6 years old) and pupils on the third floor, who belong to the category: adolescents (12 – 18 years old). Comparisons between different categories is considered more problematic according to Guerra et al. (2012). It should be noted that within the childhood category a distinction is made between those younger (aged 6 – 9) and those older (aged 9 – 12). For both sub-categories Guerra et al. (2012) recognize certain behavioural differences. It is therefore suggested that the behavioural data collected is primarily analysed and interpreted separately per floor.

•

The review of research literature indicated that most studies have focussed on pupils of this age range, presumably because this corresponds with the primary-school age in many countries. Studying pupils of the same age range would give relatable findings.

•

Ground-floor pupils do not yet adhere to a curricular schedule that includes focused-learning activities.

•

Third-floor pupils are more difficult to track due to their personalized schedules.

Pairing of Learning Spaces Besides the two age categories (6 – 9 versus 9 – 12 years old), there are two other significant differences between the first and second floor in how the learning spaces are used during the day. •

A learning space on the first floor is used by one dedicated group of pupils during the curricular hours of 08:00 and 14:00, whereas pupil groups on the second floor rotate between sectional learning spaces, occupying each respective learning space for circa 90-minute per session. As a consequence, the time pupils are exposed to a certain environment differs significantly. This may cause different sensitivities and

The Experimental Context, Setup and Design

The way pupils are distributed across the four building levels and the usage and organization of the respective learning spaces informed the decision to host the experiment only in learning spaces located on the first and second floor. The reasons are:

p. 141

First and Second Floor Learning Spaces

responses to environmental changes, potentially complicating comparisons of behavioural data between the two levels. • p. 142

The type of curricular activities the learning spaces are hosting also differs. First-floor spaces host a range of curricular activities, whereas each second-floor spaces only host a specific curricular activity. Because the objective of this experiment is to study potential effect on pupils’ disruptive behaviours to improve quietness during class, it was considered imperative to study pupils while partaking in activities that benefit thereof. On both floors, suitable activities and corresponding teaching sessions had to be found. However, the nature of these activities per floor could differ, complicating comparisons of behavioural data collected between the two floors.

The Experimental Context, Setup and Design

Because of these differences, it was decided to pair up learning spaces, one pair on the first and one pair on the second floor. The next step then was to select which two learning spaces on the first floor, and which on the second floor could be paired. In consultation with Frederiksbjerg School, it was decided to select a pair in the mathematics section on the second floor, because the curricular activities taking place in this section were considered to benefit from improved quietness during class as anticipated with this study. In addition, the curricular schedules of the learning spaces in this section are predictable and reliable. The selection of the two mathematics learning spaces then informed the selection of the pair of learning spaces on the first floor. As all experimental host spaces were to feature certain comparable environmental characteristics, it appeared sensible to select spaces nearby each other, and similarly orientated to feature comparable natural light conditions. The next section outlines the selection of the exact two pairs of learning spaces on both floors.

6.1.2

Spatial Organisation

A general review of the building’s architectural documentation showed that the learning spaces on the first and second floor are integrated in so called learning clusters. Each cluster typically comprises three space typologies (see Figure 6.4): •

A central community area: designed to host educational activities that focus on learning through movement and play, and social activities. The decoration and furniture in each community area are aligned with the particular age group ability, levels of understanding and motion.

•

Learning spaces (also referred to as classrooms): designed to host most of the formal teaching and learning activities, including group instructions, individual activities and collaborative assignments.

Study rooms: designed as quiet rooms for individual and group study. These can be used by all pupils inhabiting the cluster that are able to work well without much supervision. The teachers generally decide which pupils may sit here for works. central community area

p. 143

•

learning spaces

Figure 6.4 Typical cluster layout of three space typologies: first floor, north-east corner of building (highlighted red area, see Figure 6.5)

Two site visits, in November and December 2016, gave the opportunity to assess these first and second floor clusters in greater detail. This revealed that most of the formal curricular activities are taking place in the learning spaces. This was confirmed by four teachers active on these floors, who were interviewed during these visits on how they commonly use the three space typologies. This understanding led to centre the experiment on the learning spaces.

Learning Spaces The geometry of most of the learning spaces on the first and second floor is comparable. Most spaces feature a floor to ceiling height of circa 3 meters, room depth of circa 9 meters from the facade to the back wall, and a width that ranges between 5 and 6 meters. The documentation also indicated that the internal layout of a learning space typically consists of three areas (see Figure 6.5 – Figure 6.8). The interviewed teachers revealed that each area is used for a certain curricular setting: •

The group room is commonly used to temporarily isolate pupils that require additional attention or help, or that cause too much disruption to other pupils. Often this area is separated from the other two areas by a glass wall with a glass door that is left open or closed depending on the activity.

The Experimental Context, Setup and Design

study rooms

The central working area is generally used for focussed or collaborative task activities. It is commonly fitted with flexible desks and seating which may be quickly rearranged, for example for pupils to study in groups or individually. This area also includes substantial windowsills that were found to function as break-out niches where one or a few pupils would withdraw to work on their tasks.

•

The podium area is generally used for group presentations or instructions by the teacher and fitted out with seating benches and a smartboard or projector.

p. 144

•

learning spaces

group room

central working area

group room

The Experimental Context, Setup and Design

podium area

central working area podium area

Figure 6.5 Typical learning space layout with three zones: first floor, north-east corner of building (highlighted red area, see Figure 6.4)

Figure 6.6 Room L1.01: Group room

Figure 6.7 Room L1.01: Central area

Figure 6.8 Room: L1.01 Podium

During the site visits it was observed that the learning activities of interest for this study (those that especially benefit from quietness and concentration) commonly take place in the central working areas of the learning spaces. This was confirmed by the teachers during the interviews. It was therefore decided the experiment would focus predominantly on the central working area, but the entire learning space would be taken into consideration. The central working areas are highlighted in Figure 6.9 and Figure 6.10.

p. 145 Room RL1o.o0m 1 L1.01

Room RL2o.o0m 3 L2.03

Room RL1o.o0m 2 L1.02

6.1.3

Figure 6.10 Second floor: Room L2.03 and Room L2.04 highlighted central working areas

Interior Design

As pupil behaviour has been found to be affected by features such as wall colour, furniture and other decorations (see section 3.1), the interior design of the first and second floor learning spaces was assessed for comparability. If these were found to differ significantly between spaces, this could interfere with the results. However, the site visits revealed most learning spaces feature similar interiors. The used materials and applied colours were found to be similar in most learning spaces (including the four spaces ultimately selected), featuring medium blue linoleum floor finishes, white acoustic ceiling panels (sized 0.6 m × 0.6 m or 1.2 m × 0.6 m) and white walls with yellow (acoustic) panel sections. The type of furniture also appeared comparable, commonly consisting of wooden shelving along the walls perpendicular to the façade and back wall, movable medium grey tables (0.8 m × 1.2 m) with black stools and chairs, some additional soft furniture in the form of couches to provide for comfortable seating, and shielded table stations for individual focus. Although orientation and organization of furniture could slightly differ per learning space, the interior design of the learning spaces at the first and second floor was generally assessed to be consistent and did therefore not exclude any rooms from being selected. See Figure 6.11 – Figure 6.14 for impressions of the respective interiors from the four selected learning spaces.

The Experimental Context, Setup and Design

Figure 6.9 First floor: Room L1.01 and Room L1.02 highlighted central working areas

Room RL2o.o0m 4 L2.04

p. 146 The Experimental Context, Setup and Design

Figure 6.11 Room L1.01 Interior Design

Figure 6.12 Room L1.02 Interior Design

Figure 6.13 Room L2.03 Interior Design

Figure 6.14 Room L2.04 Interior Design

6.1.4

Acoustic Properties

As described in section 2.1.3, sound in the learning space is an accumulation of pupil activity sounds and background sounds. An important feature that defines the occupant’s experience of this sound is the acoustic quality of the environment. For learning spaces, where spoken language is important, speech intelligibility is an important aspect characterising the acoustic quality of the room. An indicator for speech intelligibility is reverberation time, which measures the time for sound to decay in a given space. Longer reverberation times tend to worsen speech intelligibility. Reverberation time of a room can be shortened by eliminating hard surfaces, for example by application of sound-absorbing materials. As described in the previous sections, room geometry, spatial organisation and finishes of the four learning spaces was assessed to be comparable. Notably, sound-absorbing ceiling tiles, wall absorbers, and soft furniture are present in all four learning spaces. As these particularly contribute to the acoustic quality of a space, this suggests that these spaces feature a comparable acoustic environment with good opportunities for speech intelligibility. This was later confirmed by measurements performed with help of the sound recorders provided by DTU Acoustics during the pilot

p. 147

studies. Early morning (07:00-07:30) and late evening (21:30-22:00) sound measurements were performed in the four learning spaces when very little human activity was taking place in the school. The average sound level of these recorded timeslots all fell between 31 to 35 dB(A) for all spaces. These are typical background sound levels of city center school buildings and suggests that the four spaces have relatively comparable background sound levels. Furthermore, when comparing these background levels against the total measured sound levels during the experiment itself (which ranged between 55 and 70 dB(A), see Table 7.1), it also appears these background sounds are negligible considering the logarithmic scale of decibels. This suggests none of the four rooms present significant fundamental noise issues (e.g. noisy building systems or traffic noise).

Lighting Conditions

With light being a key variable of interest for this experiment, specific attention was given to assess the lit appearance of the first and second-floor learning spaces. In general, the lighting condition present in the learning spaces during curricular hours is a combination of natural and artificial light. In order to select learning spaces with comparable light conditions, it was required that: (1) the artificial lighting and (2) natural light conditions would be comparable between spaces; and (3) the artificial light component would have a significant visual impact relative to the natural light component.

(1) Artificial Lighting The artificial lighting in all learning spaces was assessed to be comparable, because the applied lighting system and the control characteristics are equal in all spaces. For an impression of the resulting visual scenery, see Figure 6.11 – Figure 6.14. The artificial lighting system, designed to comply with the recommendations of the Danish Standard BS70 / European Lighting Standard EN12464-1, consists of ceiling-based light-tile luminaires, fitted with dimmable LED technology (described in section 6.2.1 for details). These are placed spread across the ceiling ensuring a relatively uniform distribution of light across the horizontal plane of a room, with well-lit vertical surfaces. This form of distribution allows for appropriate sight onto the working surface at any seating location within the space. It also results in a relatively monotone visual scenery with little contrast. The light tiles are clustered in one control group in each space. The group is automatically switched by occupancy sensors, or manually by means of wall-switches. At 22:00, when the building closes, a timer in the building management system deactivates all lighting.

The Experimental Context, Setup and Design

6.1.5

p. 148

The output of the light tiles is also constantly adapted by the control system, informed by a light sensor placed in the centre of the ceiling, to maintain a steady illuminance of 300 lux on the working plane. This setup ensures the recommended 300 lux is maintained across the working surface of the learning spaces, while unnecessary energy consumption is avoided. The intensity of the light tiles may also be manually adjusted by pressing the wall switch for more than three seconds. In order to optimize the lighting, additional control settings have been pre-programmed into the light tiles. The tiles closest to the windows would be pre-set at 90% output, those in the middle at 100% output, and those furthest away from the window at 110% output. This setup compensates for the gradual decline in natural light penetration. See Appendix B for the reflected ceiling plans of the four spaces, indicating the placement of light tiles.

(2) Natural Light Conditions The Experimental Context, Setup and Design

The requirement is to select spaces that showcase similar natural light conditions. Natural light includes indirect and direct sunlight, which enters the learning spaces in Frederiksbjerg school through varied placed windows. The manifestation of thereof in each space is characterised to a great extent by the respective window orientation relative to the sun path, window arrangement in the façade, application of blinds, and external obstructions such as adjacent buildings. Window Orientation To validate the comparability of the natural light conditions in the selected four learning spaces, first a decision was to be made for window orientation. To allow for relatively similar natural light conditions to manifest the windows of these spaces were to face the same direction. The already appointed mathematics cluster featured one learning space facing west, and two learning spaces facing east (see Figure 6.10). As a comparable pair was required, the choice fell upon the two east-facing learning spaces. To allow for a similar window orientation for the first level pair, it was required to equally select east-facing window spaces. The architectural documentation indicated the two learning spaces located directly beneath the mathematics section were fulfilling this requirement. No other spaces fulfilled this requirement. The assessment of the window orientation thus ultimately resulted in the selection of the four learning spaces as presented in Figure 6.9 and Figure 6.10. These are further referred in the thesis as: L1.01 and L1.02 for the first level spaces, and L2.03 and L2.04 for the second level spaces. To further assess the respective natural light conditions and comparability amongst, a window arrangement study was done.

Figure 6.15 Room L1.01 Central area window arrangement

Figure 6.16 Room L1.02 Central area window arrangement

Figure 6.17 Room L2.03 Central area window arrangement

Figure 6.18 Room L2.04 Central area window arrangement

Predictive Simulations With help of the digital model of the school building and the direct surrounding buildings, three simulations were performed for the four learning spaces with lighting software Radiance (Radiance, 2019) for daylight factor (DF), useful daylight illuminance (UDI), and sunlight penetration. These studies allowed to estimate the natural light conditions that may be expected for the four learning spaces. these studies and their results are briefly discussed in the following sub-sections. Detailed output of the simulations and measurements are in Appendix C.

The Experimental Context, Setup and Design

The arrangement of windows—their size and placement—codefines how much and how far natural light enters the space. The four east-facing learning spaces all feature two window sizes: smaller (1.2 m × 1.2 m) and larger window sizes (2.4 m × 2.4 m). From the architectural documentation it appeared their arrangement differs per room, though a common strategy has been to allow for a similar distribution glazed area along the facade wall: (top : middle : floor) with ratio: (3 : 2 : 1). The higher placed windows (top) allow for deep reach of natural light into the space, while the lower ones (middle, floor) also allow for a visual connection with the environment. The central areas of the four learning spaces feature different window arrangements as shown in Figures 6.15 – 6.18, seen from inside the building. These differences may be further amplified by the opposite building blocks obstructing some of the light intake at lower levels of the school building.

p. 149

Window Arrangement

Daylight Factor

p. 150

The daylight factor (DF) is the ratio of the daylight level inside versus a standardized daylight level outside. The Danish Building Regulations * state that a room with an average DF lower than 2% is considered underexposed and requires artificial lighting. A DF between 2% and 5% indicates a fairly well daylit space, that can be complemented with artificial lighting when the occupants require. A DF above 5% indicates there is no need for artificial lighting.

The Experimental Context, Setup and Design

The simulations for the four learning spaces suggest that a DF larger than 5% only occurs near the windows. A DF between 2% and 5% is achieved for the areas up to 3.5 meters away from the windows. The remaining depth of the spaces, up to 6.5 meters, is predicted to be underexposed with a DF lower than 2%. These results suggest that the natural lighting conditions are relatively comparable for the four spaces, and that according to the recommendations in the Danish Standard BS70 / European Lighting Standard EN12464-1, artificial illumination is required to supplement a significant part of the learning spaces. See Appendix C for further details about the DF analysis results. Useful Daylight Illuminance A characteristic of natural light that is relevant to this research is its dynamic nature. Over the course of a day the intensity, colour and direction of daylight changes while the sun moves along its path. This affects the visual appearance of the learning space for example between morning and afternoon sessions. Variability is also brought about by changing weather conditions. The colour and intensity of natural light indoors varies greatly between cloudy days and blue-sky conditions. A consequence of this variability is that daylight may change on the days during the experiment takes place. Both time and weather driven changes however are similar in each of the four learning spaces. It therefore does not compromise their comparability. But because it may vary throughout the timeline of the study, natural light is considered an intervening variable and monitored throughout the experiment. Further details are in section 5.4. The useful daylight illuminance (UDI) is a daylight metric that indicates how much of the occupied time daylight levels in a space fall within a range of illuminances. The simulations used a range of 100 – 2000 lux and found that at least 40% – 50% of the occupied time, all four learning spaces required artificial lighting. See Appendix C for further details about the UDI analysis results. * Bygningsreglementet 2015, BR18

From a simulation, sunlight penetration into the central working areas of the four spaces was predicted for hourly intervals between 08:00 and 14:00 for three days: once near the start of the anticipated timeline of the experiment (22 February), once near the middle (13 March), and once near the end (3 April). These studies indicated that direct sunlight can only enter the learning spaces from the middle of March between 08:00 and 09:00 on the second floor, and between 09:00 and 10:00 on the first floor. The resulting patches would mostly fall on the floor and were assessed to cause little interference with the spatial artificial light pattern (for further details on the simulations see Appendix C) Real-time Measurements The simulations indicate that relatively comparable natural light conditions may be present in the four learning spaces. But as these are only predictive results, real-time lux measurements in the four learning spaces were also performed during the experiment (see section 6.2.5 and Appendix D). This allowed to endorse (or not) the comparability of these conditions. The studies together confirmed that relatively similar daylight conditions exist in the four learning spaces. The studies also indicate that artificial lighting is required to ensure the entire learning space is sufficiently illuminated during all hours of use.

(3) Visual Impact of Artificial Lighting Because the interest for this experiment goes out to the potential impact of artificial light in a learning space, it seems important that a change of the artificial light condition should notably impact the visual appearance of that learning space. The site visits in November and December 2016 gave an opportunity to observe both the daylight only and the combined daylight and artificial-lighting conditions in the learning spaces on the first and second floor. Figure 6.19 – Figure 6.26 show the four learning spaces in the two conditions side-by-side.

The Experimental Context, Setup and Design

During the morning hours, sunlight might enter the four learning spaces through their east-facing windows, unless clouds, other buildings, or blinds block the light. This sunlight then results in bright patches of light, which will impact the pupils’ experience of the overall light pattern in the space. Direct sunlight can also cause glare and overheating, and to prevent this, the school building has been fitted out with external solar blinds along the east and southfacing windows. The blinds deploy automatically as a group when external light sensors detect direct sunlight, but they can be manually operated for each space by means of wall switches. It may therefore occur that the blinds are manually raised, and direct sunlight enters the learning space.

p. 151

Sunlight Penetration

p. 152 The Experimental Context, Setup and Design

Figure 6.19 Room L1.01: Daylight only

Figure 6.20 Room L1.01: Daylight and 100% ceiling tiles

Figure 6.21 Room L1.02: Daylight only

Figure 6.22 Room L1.02: Daylight and 100% ceiling tiles

Figure 6.23 Room L2.03: Daylight only

Figure 6.24 Room L2.03: Daylight and 100% ceiling tiles

Figure 6.25 Room L2.04: Daylight and 10% ceiling tiles

Figure 6.26 Room L2.04: Daylight and 100% ceiling tiles

The site visits also revealed that the artificial lighting is commonly activated when the learning spaces are in use. The teachers interviewed during these visits described their respective learning space to appear rather dim, dull and insufficiently lit without the artificial lighting activated, in particular during overcast days. In rare occasions, on sunny days, and only if the curricular activity at hand would permit it, they occasionally chose to not activate the lighting. The teachers described their motives to activate the artificial lighting during learning sessions firstly, to ensure for appropriate visibility for all pupils throughout the learning space. Secondly, to boost the brightness of the space; making it more inspiring or to help pupils feel energized. And thirdly, out of habit. Teachers considered activating the artificial lighting when they enter a learning space a marker of starting the curricular session. Another finding during the site visits was that, when the artificial lighting is activated, it dictates the occupants’ visual experience of that space. When asked, the teachers described their experience of the activated lighting as: clean, dull, plain, hospital-like, harsh, and not-very-child-friendly. In this condition it appears the natural light only plays a minor role in the overall visual experience of the lit space, which suggests that the visual experience of a learning space is dominated by the artificial lighting if it is activated.

6.1.6

Curricular Schedule

The curricular sessions in all Frederiksbjerg School’s learning spaces are scheduled between 08:00 and 14:00. During this timeframe, the occupancy pattern of most learning spaces follows the same structure. There are three curricular blocks of 90 minutes (or occasionally 2 × 45 minutes). These are separated by 30 to 60minute breaks for physical activity and lunch, often outside these learning spaces. A typical school day in a learning spaces is thus divided in three curricular sessions and two breaks as per Table 6.1. Table 6.1 Occupancy schedule of learning spaces on typical school day. Early morning – session 1

Late morning – session 2

Afternoon – session 3

08:00 – 08:45

session 1A

10:00 – 10:45

session 2A

12:30 – 13:15

session 3A

08:45 – 09:30

session 1B

10:45 – 11:30

session 2B

13:15 – 14:00

session 3B

09:30 – 10:00

break 1

11.30 – 12:30

break 2 /lunch

p. 153 The Experimental Context, Setup and Design

What became clear during the site-visits and what is clear from the photos is that the visual appearance of the spaces is significantly altered by the artificial lighting. This also gave credence to the presumption underlying the research approach that changes in the artificial light pattern would be noticeable.

p. 154

In general, this schedule applies to most of the learning spaces on the first and second floor, making comparable in terms of scheduling. However, the types of activities taking place during these sessions were found to differ significantly per learning space and cluster. Because of the specific interest in focused-learning activities, the section of mathematics was selected (see section 6.1.1). This co-informed the selection of the two spaces on the first floor, which was ultimately decided on based on window orientation. Nevertheless, each space’s curricular schedule was also analysed to ensure scheduling of suitable sessions for data collection was feasible. See section 6.3.1 for further details on these sessions. Additional deviations from this schedule may occur during the experiment (see section 5.4.5). The actual curricular activities were therefore considered a variable and were monitored.

The Experimental Context, Setup and Design

This section described the two pairs of learning spaces that hosted the experiment and argued why these were considered comparable in order to eliminate certain intervening variables. The following section outlines the artificial lighting installation that was installed in these four learning spaces and how it was used to expose the respective pupil groups to the two different artificial light patterns (see section 5.2) during their regular curricular activities.

6.2

The Experiment’s Lighting Installation

The experiment requires that each learning space can display the uniform and the non-uniform pools-of-light patterns. In order to achieve this an experimental lighting system has been installed in the central areas of the four selected learning spaces. This lighting system included two types of luminaires: light tiles and pendants.

Figure 6.27 Light tile

Figure 6.28 Pendant

•

The light tiles (Error! Reference source not found.) are ceilingrecessed luminaires fitted out with a diffuser, producing diffused light. This element scatters the light, producing a relatively uniform pattern of artificial light in a space.

•

The pendants (Figure 6.28) are ceiling-suspended luminaires fitted out with a shield around the light source that bundles and focusses the emitted light. A pendant can be directed it onto an area of interest and results in a relatively non-uniform distribution of artificial light in a space.

The light tiles used in the experiment were already present in the four learning spaces, as part of the standard fitout of the school building. The pendants have been purposely added. In each learning space the light tiles were circuited as one control group, and the pendants were grouped as a second control group. Both groups were automatically switched by occupancy sensors located in each learning space, or by the building’s time clock in the building management system (BMS).

6.2.1

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Light Tiles

Specification The lighting tile is a 600 × 600 mm ceiling-recessed luminaire branded LedUsed III and produced by Solar Lighting. The luminaire is equipped with LED light sources placed behind a semitransparent diffuser. At full output the lighting tile consumes 45 Watt and produces a light output of circa 4300 lumens with a color temperature of 4000 Kelvin and CRI of 80+. The lighting tile is classified with a unified glare rating index (UGR) of <19. See Appendix G for a full product specification.

Placement The placement of these luminaries in the space defines how the artificial light is distributed. Each learning space has six light tiles placed above the central area, with the exception of learning space L2.03 that has four. Figure 6.30 – Figure 6.33 show the reflected ceiling plans of the learning spaces, with the positions of the tiles. The arrangement of tiles had been guided by lighting standards EN12464-1 and DS700, which recommend maintaining 300 lux at the working plane with a uniformity ratio of 0.6. Hereto, the tiles were spread out across the ceiling, though their exact placement was also coordinated with the other technical equipment in the ceiling such as ventilation grills, sprinklers and WIFI equipment. The resulting distributions are relatively uniform. Figure 6.31 – Figure 6.37 show the ceiling tiles at night-time, for clarity.

Control During daytime hours the learning spaces take in natural light through the windows. The total amount of light in the rooms—the accumulation of artificial and natural light—varies depending on time of day, season, weather conditions, and deployment of the external blinds. The tiles are dimmed automatically to provide the recommended 300 lux at desk level and to avoid over-illumination. For this purpose, a light sensor is installed centrally in the ceiling. Two occupancy sensors, one on the wall next to the entrance and one on the wall in the podium area, turn the light on upon detecting motion, and off after 15 minutes of inactivity. The BMS turns off all light at 22:00. Wall switches can be used to manually override the automatic control, allowing the occupant the ultimate decision.

The Experimental Context, Setup and Design

Figure 6.29 Control Switch

Both groups could also be manually controlled by the occupants themselves with help of a double wall switch as shown in Figure 6.29. The left button (de)activated the group of ceiling tiles and the right button the group of pendants. There were two wall switches per learning space: one positioned on the wall next to the entrance door, and another positioned on the wall next the podium.

11 5

2 A3

C1 A4

10 4

A3,a

a,b

9 3

A3,b

N1 D2

8 2

NOTE:

7 1

I fælles adgangsveje fordeles forsyning skiftevis på hvert 2. armatur. Hvor intet andet er anført, forsynes installationer fra den pågældende etagetavle. N10 Trappe T1 forsynes fra ET 0.1-13.5, 13.7, 13.8 Trappe T2 forsynes fra ET 0.2-13.5, A3 13.7, 13.8 F 01.1.06 Trappe T3 forsynes fra ET 0.3.1-13.5, 13.7, 13.8 Grupperum 22.9 m² fra ET 0.4-13.5, 13.7, 13.8 Trappe T4 forsynes Trappe UT1 forsynes fra ET 1.1-13.5, 13.7, 12.8 5Trappe UT2 forsynes fra ET 1.2-13.5, 4 13.7, 12.8 3 A3 Trappe UT3 forsynes fra ET 1.3.2-13.5, 13.7, 12.8

HENVISNING:

01.1.05 Stamlokale 70.9 m²

Trykafbryder med 2 sluttefunktioner

A3 Tryk med indikeringslampe

Elinstallationer Armaturfortegnelse 6.73X0 Princip for PIR og UG6 i fælles adgangsveje 6.73X1

2 4

4 a,b

1 polet afbryder 1 polet afbryder med indikeringslampe A3 Korrespondanceafbryder

Vægudtag A3

Lampeudtag på loft D3

Trappe T2 forsynes fra ET 0.2-13.5, 13.7, 13.8 Trappe T3 forsynes fra ET 0.3.1-13.5, 13.7, 13.8 Trappe T4 forsynes fra ET 0.4-13.5, 13.7, 13.8 Trappe UT1 forsynes fra ET 1.1-13.5, 13.7, 12.8 Trappe UT2 forsynes fra ET 1.2-13.5, 13.7, 12.8 Trappe UT3 forsynes fra ET 1.3.2-13.5, 13.7, 12.8

Alle 5 DALI-spoler i belysningsarmaturer 4 skal afbrydes af PIR-melder (eller 3 relæ) placeret i samme rum. PIR-melderes L' benyttes til dette. For fælles adgangsveje, se dog 6.73X1.

Tryk med indikeringslampe

Elinstallationer Armaturfortegnelse 6.73X0 Princip for PIR og UG6 i fælles adgangsveje 6.73X1

HENVISNING:

63.5

A4,a

A3 D A3

01.1.15 Trappe T1 21.0 m²

C1,a D D S1.1 Teknikskakt 6.9 m²

01.2.03 Grupperum 20.2 m²

63.5

114.4 m²

01.2.07 Depot

A3,g

Grupperum 14.5 m² Luxomat RC-plus next N20 A2 10.2 m² Påbygning. B.E.G. 280 grå, 130°, 8 m., bevægelsesføler. B1 S2,g A2 D1 D1 A3 B.E.G. PD4-M-TRIO-3P, tænd/sluk til fælles adgangsveje tilstedeværelse 24/8m A3,g A3,g A3,g 01.2.14 B B1 Hc. toilet m² B.E.G. PD2-S-I, slave, 10/4 m., bevægelses/tilstedeværelse. 5.3 Indbygning. A3,a A3,a 05.2.01 a Pædagogisk køkken C1Indbygning. A4 B.E.G. 24/8 m., bevægelses/tilstedeværelse. A3 PD2-S-I, slave,01.2.05 63.0 m² Fællesrum/projektflade S2,g S2,g A3,g A4

A,a 1.1 S2/a,b A3,a A3,a

A3,g Luxmåler DALI, A3,a 1A3,a - 2000 lux

ET b1.4 63.6 Henvisningsarmatur flugtvejsbelysning, lodret pil ned 05.S.01 A3,a A3,a A4 A4 Fælles/Gang OS 51.6 m² 63.6 Henvisningsarmatur flugtvejsbelysning, dobbeltsidet, højre/venstre pilC1 A4 a,b,c A3,g A3,g 12.1 m² Henvisningsarmatur flugtvejsbelysning, A4,cenkeltsidet, højre/venstre pil A3,g A3 Panikarmatur flugtvejsbelysning i trapper. Monteres på gavlvæg på hovedrepos A4

01.2.09 Grupperum

63.6 C1 63.6

Panikarmatur flugtvejsbelysning, projektør 01.2.15

63.6

B1A3

63.6 Panikarmatur flugtvejsbelysning indbygget i loft A3 A3 B N20 The Experimental Context, Setup and Design A4,c EX 2.1 A3,g

01.2.11 Garderobe 36.8 m²

S2 A4,a

A4C1 N2

N3 N10 A4

N30

N20

01.2.04

Garderobe 30.3 m²

A302.2.08Grupperum 19.7 m² B

05.1.04 Garderobe 33.1 m² 02.2.10 Grupperum 12.1 m²

Trykafbryder med 2 sluttefunktioner Trykafbryder med 4 sluttefunktioner

B.E.G. PD2-M-DALI/DSI-1C-I, DALI, dagslys, 1 on/off (tryk eller auto) 10/4m., D2 bevægelse/ tilstedeværelse. Indbygning.

A3 *10 B2,g 05.2.02 Fælles/Gang 59.5 m²

A3,g

a,c

A3,a

N20 A3,g

A3,a

01.2.06 Stamlokale 60.7 m²

A3,a

S1.2 Teknikskakt 6.9 m²

A3,a

NOTE:

I fælles adgangsveje fordeles forsyning skiftevis på hvert 2. arm Hvor intet andet er anført, forsynes installationer fra den pågæ

Trappe T1 forsynes fra ET 0.1-13.5, 13.7, 13.8 Trappe T2 forsynes fra ET 0.2-13.5, 13.7, 13.8 Trappe T3 forsynes fra ET 0.3.1-13.5, 13.7, 13.8 Trappe T4 forsynes fra ET 0.4-13.5, 13.7, 13.8 T2.12 UT1 forsynes fra ET 1.1-13.5, 13.7, 12.8 Trappe TAGTERRASSE Trappe 16.6 m² UT2 forsynes fra ET 1.2-13.5, 13.7, 12.8 Trappe UT3 forsynes fra ET 1.3.2-13.5, 13.7, 12.8

Alle DALI-spoler i belysningsarmaturer skal afbrydes af PIR-m placeret i samme rum. PIR-melderes L' benyttes til dette. For fælles adgangsveje, se dog 6.73X1.

Belysningsarmatur, indbygget i loft,

Vægudtag

Lampeudtag på loft

Korrespondanceafbryder

1 polet afbryder med indikeringslam

1 polet afbryder

Trykafbryder med 4 sluttefunktioner lampeudtag for særbelysning (b), p

Trykafbryder med 4 sluttefunktioner

Trykafbryder med 2 sluttefunktioner

Tryk med indikeringslampe

Elinstallationer Armaturfortegnelse 6.73X0 A3 for PIR og UG6 i fælles adgangsveje 6.73X1 Princip

HENVISNING:

4 a,b

omitted

63.5

63.6

B.E.G. PD2-M-DALI/DSI-1C-I, DAL bevægelse/ tilstedeværelse. Indbyg

B.E.G. PD4-M-Trio-2R-1D-i, DALI, bevægelse/tilstedeværelse. Indbyg

Belysningsarmatur, vægmonteret, h

D B

B.E.G. PD4-M-DALI/DSI-1C-I, DAL bevægelse/ tilstedeværelse. Indbyg

01.2.08 Grupperum 20.2 m²

A3 A

63.5

B.E.G. PD2-M-1C-I, on/off, 10 m., t

63.6

SIGNATURFORKLARING: A3

63.5

D2 A3

63.5

B.E.G. PD4N-1C-I, on/off, 24 m., be

B.E.G. PD3-1C-P,on/off,10 m., bev

B.E.G. PD3-1C-I, on/off, 10 m., bev

B.E.G. PD2-M-1C-P,on/off,10 m., ti

B.E.G. Luxomat RC-plus next 280 g

B.E.G. Luxomat RC-plus next 230 g

B.E.G. PD4N-1C-P, on/off, 24 m., b

63.5

B.E.G. PD4-M-TRIO-3P, tænd/sluk

B.E.G. PD2-S-I, slave, 24/8 m., bev

B.E.G. PD2-S-I, slave, 10/4 m., bev

E2 A3

S2 C1

63.5

01.2.10 Stamlokale 60.3 m²

Luxmåler DALI, 1 - 2000 lux

Henvisningsarmatur flugtvejsbelysn

63.5

63.6

Panikarmatur flugtvejsbelysning i tr

Henvisningsarmatur flugtvejsbelysn

63.6

Panikarmatur flugtvejsbelysning ind

Henvisningsarmatur flugtvejsbelysn

63.6

Panikarmatur flugtvejsbelysning, pr

63.6

Panikarmatur flugtvejsbelysning, pr

N2 S2 N3 A3,a

N10

63.6

6.1331 N1

A3,a

N20

63.6

N30

05.2.05 Depot 14.2 m²

01.2.16 Trappe T1 21.0 m²

05.2.04 PLC 24.7 m²

D D N1fra 1 stk. 2P gruppe Strømskinne med DALI-bus forsynet fra den anførte etage. B1 D1

01.2.08 Grupperum 20.2 m²

B A3,g A3

Trykafbryder med 4 sluttefunktioner, til overstyring af aut. lysregulering (a) samt tænd/sluk af lampeudtag for særbelysning (b), placeres i 1,8 m o.f.g. 1 polet afbryder

1 polet afbryder med indikeringslampe Korrespondanceafbryder Lampeudtag på loft

63.6

B.E.G. PD4-M-Trio-2R-1D-i, DALI, dagslys, 1 on/off tryk eller auto) 24/8m., bevægelse/tilstedeværelse. Indbygning.

Belysningsarmatur, vægmonteret, her type D.

D3 Belysningsarmatur, indbygget i loft, her type B.

Vægudtag B

63.6

1 63.5 B

B.E.G. PD2-M-1C-P,on/off,10 m., tilstedeværelse. Påbygning.

B.E.G. PD4N-1C-I, on/off, 24 m., bevægelsesføler. Indbygning.

A3,a

B.E.G. Luxomat RC-plus next A/a,b 280 grå, 130°, 8 m., bevægelsesføler. Påbygning. A3,a *10 R01.2.07 B.E.G. PD4-M-TRIO-3P, tænd/sluk tilA3,a fælles adgangsveje tilstedeværelse 24/8m Depot N20 A2 10.2 m² T2.12 B.E.G. PD2-S-I, slave, 10/4 m., bevægelses/tilstedeværelse. Indbygning. TAGTERRASSE 16.6 m² A2 D1 B.E.G. PD2-S-I, slave, 24/8 m., bevægelses/tilstedeværelse. Indbygning.

A3,a A3,a B.E.G. PD4N-1C-P, on/off, 24 m., bevægelsesføler. Påbygning. b B.E.G. Luxomat RC-plus next 230 grå, 130°, 8 m., bevægelsesføler. Påbygning. A3

B.E.G. PD4-M-DALI/DSI-1C-I,T2.02 DALI, dagslys, 1 on/off (tryk eller auto) 24/8m., Overdækket areal bevægelse/ tilstedeværelse. Indbygning. J J 21.9 m² 63.5 A3 B.E.G. PD2-M-1C-I, on/off, 10 m., tilstedeværelse. Indbygning.

63.5 B

B.E.G. PD3-1C-I, on/off, 10 m., bevægelsesføler. Indbygning.

63.5

B.E.G. PD3-1C-P,on/off,10 m., bevægelsesføler. Påbygning.

63.5

01.2.02 Grupperum 12.3 m²

63.5

G H S1 D2

S D1

T2.01 TAGTERRASSE 68.0 m²

4 a,b

SIGNATURFORKLARING:

A3 F

01.2.03 Grupperum 20.2 m²

01.2.01 E1 A3 63.5 Trykafbryder med 4 sluttefunktioner Stamlokale 60.0 m² A3 P E2 tænd/sluk af Trykafbryder med 4 sluttefunktioner, til overstyring af aut. lysregulering (a) samt lampeudtag for særbelysning (b), placeres i 1,8 m o.f.g. F

SIGNATURFORKLARING: A3

B UT Alle 1 DALI-spoler i belysningsarmaturer skal afbrydes af PIR-melder (eller relæ) placeret i samme rum. PIR-melderes L' benyttes til dette. For fælles adgangsveje, se dog A3 6.73X1.

01.1.07 Grupperum 14.9 m²

B C1 A4 63.6 Belysningsarmatur, indbygget i loft, her type B. 01.2.05 T2.03 T2.01 63.5 Luxmåler DALI, 1 - 2000Fællesrum/projektflade lux Overdækket areal 114.4 m² 01.1.09 TAGTERRASSE A4 14.8 m² Krydsfelt D 68.0 m² ET1.1 63.6 Belysningsarmatur, vægmonteret, her type D. 4.6 m² 01.2.04 63.6 Henvisningsarmatur flugtvejsbelysning, lodret pil ned N1 S2/a,b D3 J Grupperum A3 D2m² A2 19.7 63.5 B.E.G. PD4-M-Trio-2R-1D-i, DALI, dagslys, 1 on/off tryk eller auto) 24/8m., A G4 A3 A3,a A3,a A3 A3 63.6 Henvisningsarmatur flugtvejsbelysning, dobbeltsidet, højre/venstre pil bevægelse/tilstedeværelse. Indbygning. N2 01.1.08 EX 1.1 Q Depot b T2.02 8.9 m² B 63.5 B.E.G. PD2-M-DALI/DSI-1C-I, DALI,areal dagslys, 1 on/off (tryk eller auto) 10/4m., B Overdækket 63.6 Henvisningsarmatur flugtvejsbelysning, enkeltsidet, højre/venstre pil A4 N3 A4 J J m² OS bevægelse/ tilstedeværelse. 21.9 Indbygning. A3 A3 a,b,c C1 63.6 Panikarmatur flugtvejsbelysning i trapper. Monteres på gavlvæg på hovedrepos 01.2.09 A3 N10 Q 63.5 B.E.G. PD4-M-DALI/DSI-1C-I, DALI, dagslys, 1 on/off (tryk eller auto) 24/8m., B2 Grupperum 01.2.02 12.1 m² bevægelse/ tilstedeværelse. Indbygning. Grupperum A4,c i loft S2 63.6 Panikarmatur flugtvejsbelysning indbygget N20 12.3 m² C1 01.2.11 63.5 B.E.G. PD2-M-1C-I, on/off, 10 m., tilstedeværelse. Indbygning. N 01.2.06 C1 S2 A3 A3 A3 J Garderobe A4 36.8 m² 63.6 Panikarmatur A4 flugtvejsbelysning, projektør Stamlokale N30 60.7 m² 63.5 B.E.G. PD2-M-1C-P,on/off,10 m., tilstedeværelse. Påbygning. C2 01.1.10 Stamlokale 63.6 A3 Panikarmatur på 3 m galvaniseret mast ET 1.1 N30 A4,c A3 69.7 m² EX 2.1 flugtvejsbelysning, projektør A3 63.5 B.E.G. PD3-1C-I, on/off, 10 m., bevægelsesføler. Indbygning. D1 A3 01.2.01 01.2.15 B1 A3 A A3 A3 A3 Stamlokale g,h,i Tænding gangareal Krydsfelt B1 60.0 m² N20 3.3 m² 01.2.12 63.5 B.E.G. PD3-1C-P,on/off,10 m., bevægelsesføler. Påbygning. D2 P Forrum + toilet J A3,a A3,a A D1 8.2 m² C1 t Tænding G4 med terrænbelysning A D2 ET 2.1 b B1 omitted E1A3 63.5 B.E.G. PD4N-1C-I, on/off, 24 m., bevægelsesføler. Indbygning. A4 B1 A3 A3 I områder, som A3 *10 A3A3 ET er 2.1fællesadgangsveje, skal der ved siden af PIR-melder A A3A3 D1 A3 ET 2.2 monteres en UG6 eller lign. Se i øvrigt princip 6.73X1. P E2 B.E.G. PD4N-1C-P, on/off, 24 m., bevægelsesføler. Påbygning. 01.2.13 A/a,b Forrum + toilet *11 Hvor B1 der (udendørs) benyttes to eller flere 2PIR-meldere (type F), kobles disse 8.4 m² A4,c B.E.G. LuxomatA3,a RC-plus*10 next 230 grå, 130°, 8 m., bevægelsesføler. Påbygning. A4,c parallelt jf. brugsanvisning. B1 A3,a M D1 01.1.11 D2

J D

A3 A3

02.2.04 Stamlokale 60.0 m²

A3 A2,f A3

A2,f f

N3 0

T1.01 TAGTERRASSE 115.2 m²

A,a,b

A3,a

T1.02 Overdækket areal 35.1 m²

*10

S2,a

01.1.04 Pædagogisk køkken/fællesrum/SFO base 126.6 m²

A3,b

A2,f

C1,f A3

T2.03 Overdækket areal 14.8 m²

N10

12 6

N3 0

A4 01.1.03 Grupperum 18.9 m²

01.1.06 Grupperum 22.9 m²

A3,b

01.1.12 Garderobe 31.7 m²

B2,g *10 D1

02.2.05 Gang 8.3 m²

N10 A3 F

A,b

B1 D1 A3 B1 D1

02.2.03 Grupperum 18.6 m²

B1 A3 B D1 B1 D1

A2,f

02.2.06 Forrum + toilet 8.2 m²

D1 A3,g B1

9 A3

01.1.01 Stamlokale 70.5 m²

01.1.02 Stamlokale 72.0 m²

UT 1 A3,bA3

A3 D1 B1 D1 B1

N10

A3 A3 A Forrum +Toilet

B1 01.1.14

A3 24.3 m² B1

B1 D1

B1 02.2.07 Forrum + toilet 8.2 m²

02.2.09 Grupperum 12.1 m²

N30

J S2

A3,b

02.2.01 Stamlokale 60.0 m²

A3,b A3

B1 A3

01.1.05 Stamlokale 70.9 m²

A3,g A3,b

D1 B1

N20 D1 B1 A3,g a,b,c

J ET 1.1 C1A4

Figure 6.37 Room L2.04 Night-time ceiling tiles ON

Figure 6.36 Room L2.04 Light Tiles – Ceiling Plan

Figure 6.33 Room L1.02 Night-time ceiling tiles ON Figure 6.32 Room L1.02 Light Tiles – Ceiling Plan

N1 05.1.05 Fagdepot billedkunst

A3 D3

N3 0

A3 A3

*10 A4 A,b S2,g A3,b

ET1.1

D1 A3 B1

A3,a 05.1.01

Fælles/Gang N20 250.7 m²

T1.01 TAGTERRASSE 115.2 m²

T1.02 Overdækket areal 35.1 m²

D2 T1.03 Overdækket areal 22.5 m²

jt S. elthø OBD3 bb Do A3,a

A3,g

N20

01.1.07 Grupperum 14.9 m²

01.1.09 Krydsfelt 4.6 m²

A3,b

02.2.02 Fællesrum/projektflade

G4m² 81.8 EX 1.1 A3,b

A,a,b A3,a

A3,a 05.1.01 Fælles/Gang 250.7 m²

A4 J

A2 01.1.08 Depot 8.9 m²

c S2,b

p. 156 N1 A3

N10

*10 b

A3,g S2,g

A3,a A3,g

A3,gJ

T2.05 Overdækket areal 17.8 m²

Figure 6.31 Room L1.01 Night-time ceiling tiles ON Figure 6.30 Room L1.01 Light Tiles – Ceiling Plan

N30

S2,a

gisk køkken/fællesrum/SFO base

A3,g OS

a,b

A3,b

N10

Figure 6.35 Room L2.03 Night-time ceiling tiles ON

Figure 6.34 Room L2.03 Light Tiles – Ceiling Plan

6.2.2

The Pendants

The choice for this particular pendant was informed by discussions during a pre-intervention workshop on 14 December 2016, which included the six teachers and two of the building’s maintenance staff. This meeting was held specifically to discuss their needs and wishes, and the technical requirements for the pendants. A key concern staff and teachers expressed was that pendants could be prone to vandalism, and when damaged could give rise to possibly unsafe situations, such as exposed electrical wiring. They therefore preferred the selected pendant would neither attract pupil’s attention, thus be modest in size and aesthetical expression, and could withstand some force. In discussion with Fagerhult, who sponsored these pendants, the Dino Classic was selected to suit the needs as outlined. The Dino Classic is a relatively small-sized pendant that has a simple, opaque design with no delicate details or accessories that can easily damage. The hood, which is the most visible element of the pendant, has a clean, white finish that blends well against the white surrounding wall surfaces and is made of deep drawn aluminium that can withstand some force when touched or hit. The light source itself is embedded in the protective hood. It may be referred to as a light engine, as the actual LED light sources are covered by translucent safety glass and an aluminium fan to ensure for sufficient heat dissipation. This light engine cannot be unscrewed—it is fixed inside the hood. Each pendant includes a 10mm thick suspension cable with metal core, fixed to the concrete suspension beams above the suspended ceiling to withstand a reasonable pulling force. To allow it to penetrate the suspended ceiling, the respective ceiling tiles were removed and temporarily replaced by carton board set-ins (see section X.X)

Placement Each learning space was fitted out with six pendants. The furniture arrangement in essence defined the positioning thereof, with each pendant placed directly above the pupils’ prime task areas. All four learning spaces featured about four prominent working desks,

The Experimental Context, Setup and Design

The pendants have been specifically added to the four learning spaces for the duration of the experiment. The pendant used is a non-dimmable, white enamelled Dino Classic by Fagerhult. The luminaire is fitted out with a cluster of LED light sources that reside inside the pendant hood that directs the radiated light downward. The beam angle is approximately 40 degrees. At 16 Watt, the luminaire produces 1325 lumens, with a color temperature of 4000 Kelvin and a CRI of 80+. See Appendix G for a full product specification.

p. 157

Specification

ET 1.2

ET 1.1

02.2.04 Stamlokale 60.0 m²

j S. elthø OB A3 bb Do

T1.03 Overdækket areal 22.5 m²

01.1.02 Stamlokale 72.0 m²

A3,b

A4 01.1.03 Grupperum 18.9 m²

A3,b

ET 2.1

A,b

B1 D1

A3,a

a,b

*10 b

A,a,b

S2,a

T2.03 Overdækket areal 14.8 m²

A3,a

A3,b

A2,f

A2,f f

A3 A3

Stamlokale 60.0 m²

B1 D D1 5.3 m²

01.2.14 B1 Hc. toilet

D S2,g

A3,g

01.2.03 Grupperum 20.2 m²

A3 A4

01.1.05 Stamlokale 70.9 m²

ET1.1

F A3

B1 D1

A3,a

*10

T2.01 TAGTERRASSE 68.0 m²

*10

A/a,b N20

S2/a,b

A3,a

T2.02 Overdækket areal 21.9 m²

A3,g

04.2.02 Studie/Øverum 3 10.6 m²

D 2

A3,a

A3,a A6 C1

A3,a

04.2.03 Studie/Teknikrum 10.7 m²

A/a,b

N20

A4,c

N20

A4,c

A4,c N1

a,c

A3,g

N20

ET 1.4

ET 1.1

A3,g

01.2.05 Fællesrum/projektflade 114.4 m²

OS a,b,c

01.2.15 Krydsfelt 3.3 m²

A4,c

ET 2.11

01.1.11 Grupperum 14.5 m²

A3 B2,g

A3 A3

05.1.06 Kreativt værksted (våd) 24.5 m²

05.2.02 Fælles/Gang 59.5 m²

*10

EX 2.1

A4 4 A3

B1 D1 A3 B1 D1 B1 D1

J A3

A3,a

A3J A3,g A3,a

A4,c

N3 S2/a,b

04.2.04 Studie/Øverum 1 01.2.05 10.7 m² Fællesrum/projektflade 114.4 m²

a,b,c

B1,g A3,g A3,a

*10

EX 2.1

T1.08 Overdækket areal 26.2 m²

Lydisoleret Koldt værksted 22.5 m²

A4 J T1.09

A a,b

A3,g

ET1.1

01.1.05 Stamlokale 70.9 m²

A4,a

a,b

01.1.06 Grupperum 22.9 m²

A3,g

01.1.10 Stamlokale 69.7 m²

G4 EX 1.1

01.2.11 Garderobe 36.8 m²

B1 A3

A3 A

A4,a A3

01.2.13 Forrum + toilet 8.4 m²

01.2.12 Forrum + toilet 8.2 m²

A4 A3

01.1.08 Depot 8.9 m²

01.2.04 01.1.09 Grupperum Krydsfelt 19.7 m² 4.6 m²

01.1.07 Grupperum 14.9 m²

Trappe T1 21.0 m²

01.1.15 A3,g

D D

N10 F

A3,a

01.2.02 Grupperum 12.3 m²

UT 1

05.1.04 Garderobe 33.1 m²

S1.1 Teknikskakt 6.9 m²

A3,g

NS2 30

05.1.05 Fagdepot billedkunst 16.5 m²

T1.01 TAGTERRASSE 115.2 m²

A3,a

B2,gA3,g

C1,f

ET 1.1

01.1.04 Pædagogisk køkken/fællesrum/SFO base 126.6 m²

A3,b

A2,f

*10 A,a

01.1.12 Garderobe 31.7 m²

A2,f S2,g

A3,g

N20

A3,a

A3,g

05.2.01 Pædagogisk køkken 63.0 m²

A3,a

A3,g

05.1.01 Fælles/Gang 250.7 m²

J T1.02

35.1 m²

S2,g Overdækket areal A3,g

a,b

A3,a

J F belyser atriegulv "a"

16.3 m²

A3,a

A3 A 05.2.08 05.1.07 01.2.01 PLC A5,a Kreativt værksted (tør) A5,a Stamlokale A3 A3audiolokale

A4,a b

05.2.07 a Pædagogisk Læringscenter PLC, (Multimedieområde) 19.3 m²

A5,aA3

A3,g

G4 EX 1.1

A3 01.1.09 Krydsfelt 4.6 m²

01.2.03 Grupperum 20.2 m²

19.7 m²

01.1.08 Depot 8.9 m²

01.1.07 01.2.04 Grupperum 14.9 m² Grupperum

A3,g A4

B2,a

Afskærmes

A3,g

*10A3,a AA5,a A3

57.4 m²m² 60.0

A3,g

B1 01.1.14 Forrum +Toilet A3,b 5ET 24.3 m² 2.2

S2,g S2,g A3,g

A3,g

05.S.01 Fælles/Gang 51.6 m²

A3,g

N20

A3,aA3

A5,a A3,a

A3,g

B2,g

*10 N1

A3,g

A3 N20 A3,g A3,a

A3,a

B2,a A,a,b

A5,aA3 *10 b

C1,a

N20

A4,a

N10

02.2.08 Garderobe 30.3 m²

A3,g

S2,g a

A3,a

A5,a

A3 A3,a B2,g

A3,a

A3,g 05.1.01 Fælles/Gang 250.7 m²

S2,g A4,a A3,g

02.2.10 Grupperum 12.1 m²

N3 0

A3,a

01.1.01 Stamlokale 70.5 m²

02.2.17 Trappe T2 19.8 m²

A3,g C1 A3,a A4

05.1.03 Fælles fagtorv 61.9 m²

A3,g *10

T2.03 Overdækket areal 14.8 m²

S2,a A3,b 3

7A3

02.2.05 Gang 8.3 m²

"a" belyser atriegulv D

01.1.03

S2,g

B2,a *10 A4

A3,a A3,g

A3,a

OS a,b

01.1.04 Pædagogisk køkken/fællesrum/SFO base 126.6 m²

A3,b

02.2.03 Grupperum 18.6 m²

BA3 A3

02.2.06 Forrum + toilet

f8.2 m²

N20 A3,g

Grupperum 12.1 m²

02.2.09 A3,g

A3,a

ET 2.2

A3,a

01.2.11 Garderobe 36.8 m²

N10

A3 S2

D1 B1

D1 A4,f B1

*10 B2,g

A3,g

a,b,c

02.2.07 Forrum D3+ toilet 8.2 m²

UT 7B1

A3,a

N20

A3,a C1,a

02.2.16 Depot 9.7 m²

A3,b

The Experimental Context, Setup and Design 5 ET61.1 A3 A3 4

02.2.01 Stamlokale 60.0 m²

A3 A3

Garderobe 61.7 m²

02.1.12 A3,b

D1 B1

C1,f D1 B1

A4,f

A3,a

02.2.14 Gang 12.5 m²

S2,g A3,g A2

Grupperum N2018.9 m²

A3,g

A3,g A3,g

A3,g

A,b

N10

A,b A4,f c

A3,b N1

C1 A6

N20

02.2.12 Grupperum 19.7 m² 02.2.13 Grupperum 20.1 m²

S2.2 Teknikskakt 16.7 m²

72.0 m²

A 05.1.02 S2,g 01.1.02 A3,g N20 Fælles fagtorv Stamlokale A3 A3,g A3 35.0 m²

A3,g

05.2.10 Fælles fagtorv 13.7 m²

05.2.06 Fælles/Gang 150.4 m²

A3,b 5

*10 A3,b

A4,f

A3,b

02.2.02 Fællesrum/projektflade 81.8 m²

A3,b c S2,b

A4,a

N10

02.1.14 Trappe T2 19.8 m²

A3,g

63.5 omitted

63.5

B.E.G. PD4N-1C-I, on/off, 24 m., bevægelsesføler. Indby

B.E.G. PD3-1C-P,on/off,10 m., bevægelsesføler. Påbygn

B.E.G. Luxomat RC-plus next 230 grå, 130°, 8 m., bevæ

A3B.E.G. PD4N-1C-P, on/off, 24 m., bevægelsesføler. Påb

B.E.G. Luxomat RC-plus next 280 grå, 130°, 8 m., bevæ

B.E.G. PD4-M-TRIO-3P, tænd/sluk til fælles adgangsvej

Luxmåler DALI, 1 - 2000 lux

B.E.G. PD2-S-I, slave, 24/8 m., bevægelses/tilstedevære

B.E.G. PD2-S-I, slave, 10/4 m., bevægelses/tilstedevære A3

63.5

Henvisningsarmatur flugtvejsbelysning, lodret pil ned

01.2.08 Grupperum 20.2 m²

63.6

S2 63.6

Henvisningsarmatur flugtvejsbelysning, enkeltsidet, højre

Henvisningsarmatur flugtvejsbelysning, dobbeltsidet, høj

NOTE:

63.6 Panikarmatur flugtvejsbelysning i trapper. Monteres på g N10 I fælles adgangsveje fordeles forsyning skiftevis på hvert 2. armatur. A3 andet er anført, forsynes installationer fra den pågældende etagetavle. Hvor intet 63.6 Panikarmatur flugtvejsbelysning indbygget i loft N20

Trappe T1 forsynes fra ET 0.1-13.5, 13.7, 13.8 63.6 Panikarmatur flugtvejsbelysning, projektør N30 Trappe T2 forsynes fra ET 0.2-13.5, 13.7, 13.8 Trappe T3 forsynes fra ET 0.3.1-13.5, 13.7, 13.8 63.6 Panikarmatur flugtvejsbelysning, projektør på 3 m galvan TrappeN30 T4 forsynesA3 fra ET 0.4-13.5, 13.7, 13.8 Trappe UT1 forsynes fra ET 1.1-13.5, 13.7, 12.8 01.2.10

4 a,b

A3,a

med 2 sluttefunktioner

A2 med indikeringslampe Tryk

Trykafbryder med 4 sluttefunktioner

05.2.05 Depot Trykafbryder 14.2 m²

Trykafbryder med 4 sluttefunktioner, til overstyring af aut. ly lampeudtag for særbelysning (b), placeres i 1,8 m o.f.g.

polet afbryder med indikeringslampe

A3,a1 polet afbryder

Belysningsarmatur, indbygget i loft, her type B. J

Vægudtag

Lampeudtag på loft

Korrespondanceafbryder

T2.12 TAGTERRASSE 16.6 m² 1

SIGNATURFORKLARING:

01.2.16 Trappe T1 21.0 m²

*11 Hvor der (udendørs) benyttes to eller flere 2PIR-meldere ( HENVISNING: parallelt jf. brugsanvisning. Elinstallationer Armaturfortegnelse 6.73X0 D Princip for PIR og UG6 i fælles adgangsveje 6.73X1 A2 Strømskinne med DALI-bus forsynet fra 1 stk. 2P gruppe

Stamlokale g,h,i Trappe UT2 forsynes fra ET Tænding 1.2-13.5, gangareal 13.7, 12.8 60.3 m² A Trappe UT3 forsynes fra ET 1.3.2-13.5, 13.7, 12.8 t Tænding med terrænbelysning A3 A3 Alle DALI-spoler i belysningsarmaturer skal afbrydes af PIR-melder (eller relæ) *10 i samme rum. PIR-melderes I områder, er fællesadgangsveje, skal der ved siden placeret L' som benyttes til dette. monteres en UG6 eller lign. Se i øvrigt princip 6.73X1. For fælles adgangsveje, se dog 6.73X1.

PA3

01.2.07 Depot

A2 10.2 m² D1

05.2.04

63.6

Belysningsarmatur, vægmonteret, her type D.

PD4-M-Trio-2R-1D-i, DALI, dagslys, 1 on/off tryk ell bevægelse/tilstedeværelse. Indbygning.

63.5

B.E.G. PD4-M-DALI/DSI-1C-I, DALI, dagslys, 1 on/off (tryk bevægelse/ tilstedeværelse. Indbygning.

A3 PD2-M-DALI/DSI-1C-I, DALI, dagslys, 1 on/off (tryk B.E.G. bevægelse/ tilstedeværelse. Indbygning.

63.5

B.E.G. PD2-M-1C-I, ET on/off, 2.1 10 m., tilstedeværelse. Indbygn

63.5

ET 2.410 m., bevægelsesføler. Indbygnin B.E.G. PD3-1C-I, on/off,

B.E.G. PD2-M-1C-P,on/off,10 m., tilstedeværelse. Påbygni

63.5

next 230 grå, 130°, 8 m., bevæge

next 280 grå, 130°, 8 m., bevæge

tænd/sluk til fælles adgangsveje t

B.E.G. PD2-S-I, slave, 24/8 m., bevægelses/tilstedeværels

B.E.G. PD2-S-I, slave, 10/4 m., bevægelses/tilstedeværels

Betegnelse/Revision B.E.G. PD4-M-TRIO-3P,

B.E.G. PD4N-1C-P, on/off, 24 m., bevægelsesføler. Påbyg

63.5 A3 B.E.G. PD4N-1C-I, on/off, 24 m., bevægelsesføler. Indbygn

63.5 B.E.G. PD3-1C-P,on/off,10 m., bevægelsesføler. Påbygnin omitted

04.2.01 Musik, Fagkerne E2 m² 68.9

T2.11 Overdækket 63.5areal B.E.G. 25.7 m²

A3 63.6

24.7 m²

D2PLC

A3,a

S1.2 Teknikskakt 6.9 m²

01.2.06 Stamlokale 60.7 m²

A,a,b

01.2.09 Grupperum 12.1 m²

A3,a D3

A3,a

a,b

Dato 20.2 m²

B.E.G. Luxomat RC-plus FD 2015.09.15 Armaturer tilpasset nyt loft C 2015.08.25 Belysning tilpasset 04.2.01 Musik, B Fagkerne 2015.03.12 A5 Revisioner, skyer B.E.G.seLuxomat RC-plus G 68.9 m² A3 01.2.08 A 2015.03.06 Grupperum Revisioner iht. rettelser

Udgave H

A5 FREDERIKSBJERG BYGGERIET A3

Elinstallationer 63.5 Luxmåler DALI, 1 - 2000 lux 1. sal_Nord_Belysning

63.6 Henvisningsarmatur flugtvejsbelysning, lodret pil ned Mål: 1 : 100 Sign.: EBS / LNF 210589 A3 Henvisningsarmatur flugtvejsbelysning, dobbeltsidet, højre

Emne:

Sag nr.:

63.6

Henvisningsarmatur flugtvejsbelysning, HOFFMANN A/S

S263.6

Panikarmatur flugtvejsbelysning i trapper. Monteres på gav

Panikarmatur indbygget i loft ARKITEKTERflugtvejsbelysning MAA PAR

R enkeltsidet, Edwin højre/v 8220 Bra hoffman Grønneg 8000 Aa gpp@gp

63.6

Panikarmatur flugtvejsbelysning, projektør

GPP ARKITEKTER A/S

TOTALENTREPRENØR

63.6

N10

63.6

Vesterbr

N30

N20

N2 Rev.:

A4 A5

A5 A3

01.2.07 Depot

A2 10.2 m² I

01.2.09 Grupperum 12.1 m²

A3,a

05.2.03 PLC 64.4 m²

Figure 6.41 Room L2.04 Furniture Layout

Figure 6.40 Room L2.03 Furniture Layout

S2,g

N10

Figure 6.39 Room L1.02 Furniture Layout

Figure 6.38 Room L1.01 Furniture Layout

A3,b

D 02.2.15 Grupperum 10.9 m²

A3,g

05.1.01 Fælles/Gang 250.7 m²

Initially it was anticipated that the furniture would be moved around in the central working areas of the learning spaces during or between sessions. But in the pre-intervention workshop it became evident that the positioning of desks and seating was not often changed. The teachers had already agreed on a basic furniture layout for their respective spaces, and most would adhere to this during regular curricular sessions. Agreement on placement of the pendants was therefore relatively easily reached. See Figure 6.38 – 6.41 for an overview of the furniture layouts agreed for the central areas of the four learning spaces. These layouts were agreed to be kept in place to throughout the duration of the experiment. T1.03

30 N

N30 N20

H,a

S2,g

ET 1.1

Furniture layout

N20

G4 A

D2 S2.1 Teknikskakt 16.7 m²

A3,g

ET 1.2

p. 158

ET 1.2

N20

02.2.11

60.0 m²

A3 Stamlokale

T 1.2

T 1.3.1

N20

complemented by two to four smaller desks or private workstations. The positioning of the pendants and the furniture layout were discussed and agreed per space with the six teachers during the preintervention workshop on 14 December 2016. Four of the pendants N3 were directly aligned above the main group desks and the remaining two pendants placed above the smaller working desks that would otherwise may become underlit.

Figure 6.42 Room L1.01 Pendants (red dots)

Figure 6.43 Room L1.02 Pendants (red dots)

Figure 6.44 Room L2.03 Pendants (red dots)

Figure 6.45 Room L2.04 Pendants (red dots)

Suspension height The suspension height of each pendant above a work desk was also discussed and agreed on during the pre-intervention workshop. There were four requirements: 1.

The pendants needed to be placed high enough so that pupils could walk underneath without bumping their heads;

The pendants should not be in a direct line of sight, or obstruct a pupils’ view on their surroundings and the teacher–both in seated and standing position;

The pendants should not be placed in direct eyesight so that they would attract too much attention and possibly encourage pupils to touch, swing or pull them;

The pendants should not be placed too high so that the pools of light would not manifest anymore.

The Experimental Context, Setup and Design

p. 159

Figures 6.42 – 6.45 show the placement of the pendants (red markers), aligned with the furniture layout and ceiling arrangement including the light tiles, ceiling panels and other equipment.

p. 160

A compromise was reached at placing the pendants at circa 0.8 m above a desk surface. The desk height is also 0.8 m and the floor-toceiling height 3.0 m. The pendants were thus suspended 1.4 m from the ceiling and 1.6 m above the floor—allowing pupils of up to 12 years old to walk and see underneath. See Fig 6.46 – 6.49 for impressions of the final positioning of the pendants and how these illuminate the desk areas in each of the four learning spaces.

The Experimental Context, Setup and Design

Figure 6.46 Room L1.01 Pendants

Figure 6.47 Room L1.02 Pendants

Figure 6.48 Room L2.03 Pendants

Figure 6.49 Room L2.04 Pendants

Control The six pendants were circuited as one independent group. They could only be switched on or off and were not dimmable. This was a deliberate choice made in agreement with the teachers during the pre-intervention workshop. The teachers expressed that the manual dimmability of the existing lighting was of little use to them, and as long as the new lighting would not cause uncomfortable glare, they suggested that complex controls would merely inhibit its use. It was agreed to assign one of the double wall switches to this group to allow for manual switching of six pendants per space. The group of pendants were also connected to the occupancy sensor and the BMS, so when no presence was detected for 15 minutes and at 22:00, the lights would be automatically deactivated.

p. 161 Figure 6.51 Room L1.02 Pre installation

Figure 6.52 Room L2.03 Pre installation

Figure 6.53 Room L2.04 Pre installation

Figure 6.54 Room L1.01 Post installation

Figure 6.55 Room L1.02 Post installation

Figure 6.56 Room L2.03 Post installation

Figure 6.57 Room L2.04 Post installation

The Experimental Context, Setup and Design

Figure 6.50 Room L1.01 Pre installation

6.2.3

Installation of the Experimental Lighting

p. 162

The installation of the additional pendants, including the circuiting and added control switches, took place during the school winter break in week 7 of 2017. It was performed by the original electrical installer of the standard artificial light tiles, EL-team Vest. Figure 6.50 – Figure 6.53 show the four spaces before the installation of the research intervention, and Figure 6.54 – Figure 6.57 show the pendants installed.

6.2.4

Making the Artificial Light Patterns

The standard-versus-experimental-group research design for the experiment (see section 5.1.2), requires that each of the four learning spaces can alternate between the standard situation (uniform light pattern) and the experimental situation (nonuniform pools-of-light pattern), while all other intervening variables are kept as constant as possible. The Experimental Context, Setup and Design

Because this experiment takes place in a real-life school environment, it appeared not feasible, nor desired to prescribe the exact artificial lighting setting during the experiment. In the preintervention workshop on 14 December 2016, the teachers requested reasonable authority over the control of the artificial lighting and operate the lights as they considered appropriate for a particular learning session. Specifically, they did not want to rely solely on the pendants to illuminate the learning spaces, as there were concerns this would compromise visibility for some of the pupils. Therefore, it was agreed to alternate between standard and experimental situations, within which various lighting scenarios could occur (see Table 6.2).

Table 6.2 Standard and Experimental Situations

Situation A represents the standard artificial lighting situation, making available

only the existing light pattern. In this situation the ceiling tiles could be activated and dimmed by the teachers and pupils, resulting in a uniform pattern of artificial light. The pendants were disabled and strung up against the ceiling to conceal them from their view. Situation B represents the experimental situation, making available also the new,

non-uniform pools-of-light pattern. In this situation both the ceiling tiles and the pendants could be independently activated by the teachers and pupils, resulting in either uniform or non-uniform patterns of artificial light. The pendants were now enabled and suspended from the ceiling.

Because multiple lighting scenarios could be present in each situation, it became crucial to monitor which luminaires were activated when, for the duration of the experiment. An overview of the available scenarios is presented in Table 6.3

p. 163

Table 6.3 Available artificial light scenarios in situation A and B

(A1)

(B0)

(B1)

(B2)

(B3)

Situation A: Standard When situation A is operational in the learning space, only the ceiling tiles are available for use. The power to the pendants is temporarily disabled and they are physically tied against the ceiling to avoid interreference as much as possible. In this setting the teachers and pupils continue to use the light tiles as they normally would pre-intervention. Situation A thus allowed teachers and pupils to choose or alternate between two artificial lighting scenarios: •

(A0) Deactivated ceiling tiles and relying on natural light only. In practice, this scenario was rarely observed during the experiment.

•

(A1) Activated ceiling tiles resulting in a uniform light pattern. The ceiling tiles are connected to a light sensor that is set to adjust the output of the tiles to meet the target level of circa 300 lux at the working plane. However, the output of the tiles could be manually increased or decreased by the teachers, which would impact on the brightness of the space but not the expression (contrasts) of the patter itself.

Situation B: Experimental When situation B is operational in the learning space, both the pendants and ceiling tiles are available for use. The pendants are positioned as intended: suspended above the working tables just above eye height and powered so that they can be activated on demand. The ceiling tiles could be used as normal, only the light

The Experimental Context, Setup and Design

(A0)

p. 164

sensor was now adjusted to a target level of circa 200 lux at the working plane (see next section for argumentation). This was done for two reasons. The first reason is that teachers had described the standard lighting to be too bright, using words as “harsh” and “hospital-like”. Prior to this research they would thus regularly lower the light output manually by operating the wall switches; in their experience 200 lux would suffice during most curricular activities in the learning spaces. The second reason for the decrease was to create a greater contrast between the pools of light created by the pendants and the general illumination provided by the light tiles. The lower output of the tiles would accentuate the effect of the pools of light. The target level for the sensor was set to 200 lux at working height in scenario B, but occupants could still manually adjust the brightness of the ceiling tiles. Situation B allowed teachers and pupils to choose or alternate between one of four artificial lighting scenarios:

The Experimental Context, Setup and Design Figure 6.58 Ceiling Tiles Only (B1)

•

(B0) No artificial lighting. Both luminaire types deactivated and relying on natural light only. In practice, this scenario was rarely observed during the experiment.

•

(B1) Activated ceiling tiles only, resulting in a uniform light pattern with circa 200 lux at the working plane (Figure 6.58). The resulting light pattern is the same as for scenario (A1) only featuring a lower overall brightness.

•

(B2) Activated ceiling tiles and activated pendants at the same time, resulting in a moderate non-uniform light pattern (Figure 6.59). In theory this scenario would account for a build-up of 500 lux at the working plane near the pendants, and circa 200 lux in-between *.

•

(B3) Activated pendants only, resulting in a pronounced nonuniform light pattern (Figure 6.60). The pendants are not dimmable, resulting in measured light levels at desk height of apprx. 500 lux nearby a pendant, and 50 – 200 lux in-between.

Figure 6.59 Ceiling Tiles + Pendants (B2)

Figure 6.60 Pendants Only (B3)

* when the pendants are active in situation B, their output will partake in the 200 lux that the light sensor is aiming for, and the control system automatically decreases the output of the ceiling tiles. Recordings from the experiment indicate that the ceiling tiles would operate at 30% output.

the teachers wanted to keep the ability to adjust the lighting to their teaching activities during the weeks when the experiment took place; also to choose their standard lighting;

•

to keep the whole learning space functional. Activating only the pendant lighting creates local pools of light, but other areas in the space are left relative darkness. Although most pupils would sit at the desks and chairs provided, some would also opt to use the corner couch, the windowsill, or simply somewhere on the floor or the podium. Ensuring a basic illumination across the entire learning space allowed pupils to continue choosing their preferred position, which may have been away from any pool of light.

6.2.5

Analysis of the different Lighting Scenarios

The five light scenarios —A0/B0, A1, B1, B2, and B3—described in section 6.2.4. have been mapped with help of two methods: •

Illuminance measurements across the horizontal working plane of each learning space using a handheld lux meter, and

•

Spatially by taking high dynamic range images (HDRI). Mappings were performed during daytime and night-time.

The purpose of these mappings was to establish the contrast ratios in the standard uniform and experimental pools-of-light scenarios. Christopher Cuttle (2015) describes perceived differences of illuminance as noticeable when their ratio is at least 1.5:1, distinct when the ratio is 3:1, strong when the ratio is at least 10:1, and emphatic when it exceeds 40:1. His rating scales have been used to assess the extrapolated contrast rations of the five different light scenario mappings.

Horizontal Illuminance Distribution The light level measurements in lux were taken with a handheld Konica-Minolta CL-200 Chroma illuminance meter. Measurements we taken on a grid of 1 × 1 m at pupil desk height, 0.6 m above the floor. The measurements with daylight were taken under overcastsky conditions, and daylight-only measurements were taken twice, on 8 and 29 March 2017. The daytime measurements were taken also for scenarios A1 and B2, because these were expected to be used the most. Night-time measurements for analysis and comparison reasons were taken for scenarios A1, B1, B2 and B3. An overview of these mappings is given in Table 6.4.

The Experimental Context, Setup and Design

•

p. 165

Keeping both luminaires available during situation B required additional monitoring and led to more elaborate procedures in the data analysis. The reasons for keeping both available are because:

14. Interruptions

Interruptions monitored during observations study II.

No significant external or classroom interruptions occurred. No effect.

Table 6.4 Illuminance mappings Scenario

Description

Day

A0/B0

natural light only

natural light + light tiles (300 lux)

natural light + light tiles (200 lux) + pendants

light tiles (300 lux)

light tiles (200 lux)

light tiles (200 lux) + pendants

pendants

p. 166

When?

Night

The Experimental Context, Setup and Design

The collected numerical data has been translated into 3D graphs showing the distribution of light for the mapped scenarios, in each learning space. The daylight measurements for room L1.01 can be seen in Figure 6.61 and the night-time measurements for the same room in Figure 6.62. For graphs representing rooms L1.02, L2.03 and L2.04, see Appendix E. All four graphs in Figure 6.61 show that natural light has a significant presence near the windows in the four rooms, and that without artificial light (scenario A0 and B0) the contrast ratio is about 7:1. In Cuttle’s terms, this difference is distinct to strong. The graphs in Figure 6.61 also show that the lighting tiles balance the overall distribution of light in the space significantly. In scenario A1 (natural light plus ceiling tiles) the contrast ratio becomes closer to 1.75:1, which according to Cuttle is noticeable, but only just. It seems therefore justified to describe the distribution of light for scenario A1 (ceiling tiles with and without natural light) as uniform. Scenario B2, with activated pendants, however, shows clearly visible brightness peaks throughout the space of varying heights. Comparing the light levels directly underneath these pendants versus the levels measured at in-between areas, a conservative reading would allow for a ratio of 4:1, which according to Cuttle is distinct. We may therefore describe the distribution of light in scenario B2 (and by extension B3) as non-uniform. The graphs in Figure 6.62 show the night-time measurements which allows to evaluate the particular effects of each of the artificial lighting settings on their own. Graphs showing scenarios A1 and B1 confirm that the light tiles provide for a relatively even or uniform distribution of light throughout the space. The distribution is also sloping slightly upwards away from the windows, which helps explain the levelling effect in scenario A1. The graphs representing scenarios B2 and B3 demonstrate the pronounced effect of activated pendants with and without activation of the tiles. Clearly indicating a relatively non-uniform distribution of light.

p. 167 Scenario B0: Daylight Only

Scenario A1: Daylight + Light tiles (300 lux)

Scenario B2: Daylight + Tiles (200 lux) + Pendants

Figure 6.61 Four Illuminance graphs based on handheld lux measurements in Room L1.01 – Daytime (overcast sky)

Scenario (A1): Light tiles only (300lux)

Setting (B1): Light tiles only (200 lux)

Scenario (B2): Tiles (200 lux) + Pendants

Scenario (B3): Pendants only

Figure 6.62 Four Illuminance graphs based on handheld lux measurements in Room L1.01 – Night-time (no daylight)

The Experimental Context, Setup and Design

Scenario A0: Daylight Only

Table 6.4 Night-time illuminance and uniformity values based on handheld lux measurements in all four rooms

p. 168

(A1) LIGHT TILES ONLY (300 LUX)

(B1) LIGHT TILES ONLY (200 LUX)

ROOM

Average

Max

Min

Uniformity

ROOM

Average

Max

Min

Uniformity

L1.01

300

465

0.33

L1.01

190

314

0.44

L1.02

325

477

119

0.37

L1.02

232

339

0.35

L2.03

235

425

0.27

L2.03

195

361

0.32

L2.04

386

520

143

0.39

L2.04

230

346

105

0.46

(B3) PENDANTS ONLY

(B2) LIGHT TILES + PENDANTS

The Experimental Context, Setup and Design

ROOM

Average

Max

Min

Uniformity

ROOM

Average

Max

Min

Uniformity

L1.01

144

680

0.21

L1.01

626

0.09

L1.02

175

1337

0.19

L1.02

192

1550

0.06

L2.03

263

1550

0.16

L2.03

139

1557

0.06

L2.04

289

1231

0.11

L2.04

190

1263

0.04

Spatial Luminance Distribution Where the analysis described before concerns the horizonal working plane and is of importance to those working on their learning task, it is the appearance of the entire space and the brightness variations therein as a whole that ultimately define the appearance of the light pattern for the occupant of the room. To document and assess the appearance of the artificial light patterns in three-dimensional space, luminance maps have been created with help of HDR images. These images were created by taking a series of nine photos with a range of exposure times. The photos were taken at night-time to isolate the artificial light. The photos were taken at pupil’s eye height and in two directions in each learning space: along the central axis from the back wall towards the facade and in the opposite direction. To calibrate these photos, luminance values were measured with a hand-held luminance meter at fixed points on both walls for all measured scenarios. These measurements were taken from the same position as the HDR images. Figure 6.63 shows HDR images taken in Room L1.01 for scenarios B1, B2 and B3 in two directions.

(B2) Light tiles + pendants

(B3) Pendants only

Figure 6.63 Night-time HDRI’s for Room L1.01

The HDR images were also transformed into calibrated false-color luminance maps (FCLMs) using photometric software Photolux 3.2 (Photolux, 2019). These FCLMs quantify brightness and map luminance to hue. Pixel values from the HDR images were converted to luminance measures after calibration of the camera. The FCLMs assist with further analysis of the different brightness appearances. Figure 6.64 shows the FCLMs created for Room L1.01 when facing the backwall for scenarios B1, B2 and B3. For a complete overview see Appendix F.

(B1) Light tiles

Figure 6.64 Night-time FCLMs for Room L1.01

(B2) Light tiles + Pendants

(B3) Pendant Only

The Experimental Context, Setup and Design

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(B1) Light tiles

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What can be seen in these HDR images and FCLMs is that scenario B1 with only active light tiles results in a rather uniform appearance of the entire space; both across the main horizonal and vertical surfaces there is very little contrast. Whereas active pendants, with or without light tiles in scenarios B2 and B3, create a greater diversity in brightness throughout the space. These variations are clearly evident across the horizontal working plane, with clearly visible hotspots of light directly underneath the pendants. Another effect of active pendants is the appearance of shadows, which adds to the contrast diversity. The entire field of view therefore becomes richer in contrast.

6.3

The Experiment’s Research Protocol

The Experimental Context, Setup and Design

This experimental field study’s key ambition is to assess if the different artificial lighting patterns affect pupils’ behaviour and learning. But because these are abstract terminologies, they have been made operational by employing three related variables that were proven by previous research measurable or observable for change: Study (I) – noise during class; Study (II) – observable disruptive pupil behaviour; and Study (III) – cognitive performance (see section 5.3) These three studies were conducted in two separate time intervals in 2017. Study I and II took place simultaneously during spring 2017. This period is referred to as the: Spring experiment. Study III was conducted during the autumn of 2017; is and referred to as the: Autumn experiment. Both experiments followed their own research protocols with specific data collection activities and timing thereof. The experiments had in common that they share the same underlying crossover research design *.

6.3.1

Spring Experiment – Study I + II

Study I was set up to measure noise levels during class, while Study II was designed to observe pupil behaviour. Several potential intervening variables were monitored during these studies.

Crossover Research Design These two studies ran simultaneously, and both adhered to the same crossover research design. This type of design meant that each of the ten pupil groups experienced both lighting situation A and B, but the order of exposure varied. These two situations were always opposing per learning space pair. For example, when L1.01 was hosting situation A, L1.02 was hosting situation B, and vice versa. The same applies for the pair on the second floor, L2.03 and L2.04. As a result, the spring experiment was split into two consecutive phases of three weeks each, that would see the same situation in each room. The schedule of exposure per learning space and phase is presented in Table 6.5. * The experiments also required consent from the parents or guardians of the pupils. The school administration helped collecting the written consent.

During these two three-week phases, which ran from Thursday to Thursday, a broad palette of data was collected. Some of the data was collected continuously, for example the indoor climate variables. The methods for collecting these data are described in section 5.4.3.

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Data Collection

Table 6.5 Crossover Research Schedule Spring Experiment

Phase I Week 1

Week 2

Phase II Week 3

Week 4

Week 5

Week 6

Room L1.01

Room L2.03

Room L2.04

While other data, including noise levels and pupil behaviour, was collected during four appointed field days. Each phase included two field days; the second Wednesday and Thursday per phase. These field days were used for three reasons: •

The qualitative studies, in the form of observations, had to take place during live teaching. This involves having a researcher present during class, which could affect the daily routine. To limit any disturbance to the learning, it was agreed with the teachers to perform the observational research during confined times on pre-agreed days.

•

A prerequisite for Study I and II was that the same pupil group could be followed, performing similar curricular activities. On the first floor the two learning spaces host the same pupils every day of the week, but the curricular schedule varies per weekday. On the second floor, the two learning spaces host at least ten different pupil groups, but the activity is similar in every learning session. A review of both schedules indicated that on Wednesday and Thursday the occupancy of the spaces was most consistent. The teachers agreed on the dates for observational studies.

The Experimental Context, Setup and Design

Room L1.02

•

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The sound recording tools are highly sensitive and exclusive recorders that could only be borrowed from collaborator DTU Acoustics for brief segments at a time. The lending time was agreed for four days per period: one day before to setup, the two field days to record, and a day to remove, download the data and handing back the equipment. The equipment was available for the two weeks of the appointed field days from DTU’s lending roster.

Pupil Groups During these four field days data was collected in the four learning spaces for ten different pupil groups. Each group was exposed to situation A and B, half the groups in reverse order. The pupil groups and their demographic characteristics are shown in Table 6.6.

Table 6.6 Pupil groups and demographics

The Experimental Context, Setup and Design

Room

Name

Total

Female / Male

Age

L1.01

Panda

14 / 11

06 – 08

L1.02

Isbjørn

12 / 15

06 – 08

L2.03

Delta

14 / 10

09 – 10

Charlie

13 / 13

10 – 11

Merkur

13 / 13

11 – 12

Bravo

12 / 15

10 – 11

Neptun

13 / 12

09 – 10

Sterneskud

14 / 11

10 – 11

Nordlys

12 / 15

11 – 12

Jupiter

12 / 11

10 – 11

L2.04

Curricular Schedules A normal school day in all four learning spaces includes three curricular sessions of 90 minutes (sometimes 2 × 45 minutes). The sessions taking place in room pair L1.01 and L1.02 are committed to a range of topics such as mathematics, Danish, and natural sciences, as well as play, music, and art activities. In order to study pupil behaviour during focused-learning activities, the curricular sessions with mathematics and Danish were of interest. The

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sessions in room pair L2.03 and L2.04 were all dedicated to mathematics, which involves focused learning. Table 6.7 and Table 6.8 outline which groups were present during what sessions in each learning space on Wednesday and Thursday. Sessions marked with * were observed in person. Table 6.7 Field day: Pupil groups per learning space on Wednesday

Wednesday

Room L1.01

Room L1.02

Room L2.03

Room L2.04

Session 1 08:00 – 09:30

Panda

Isbjørn

Delta *

Neptun

Session 2 10:00 – 11:30

Panda

Isbjørn

Charlie *

Stjerneskud

Session 3 12:30 – 14:00

Panda *

Isbjørn

Merkur (45 min)

Thursday

Room L1.01

Room L1.02

Room L2.03

Room L2.04

Session 1 08:00 – 09:30

Panda

Isbjørn

Merkur (45 min)

Nordlys *

Session 2 10:00 – 11:30

Panda

Isbjørn

Bravo

Jupiter *

Session 3 12:30 – 14:00

Panda

Isbjørn *

Bravo (45 min)

Charlie (45 min)

Research Activities The total number of curricular sessions studied during the four field days accumulates to 48 (4 days × 4 rooms × 3 sessions per room). During all 48 sessions the sound levels were measured, and videos were recorded of the pupils undertaking their learning activities in the central areas of the respective rooms. These videos allowed for a revisit of each session, because not all sessions could be attended in person. See Appendix H for full protocol description. Detailed observations by the researcher during a session, followed up by an interview with the respective teacher thereafter could only take place during one of four sessions. This accumulated to 12 observed sessions in total (6 during period I and 6 during period II). The choice for which session was observed by the researcher was based on the scheduled curricular activities and in agreement with the respective teachers. Each of these sessions was observed once while the pupil group was exposed to situation A and once while exposed to situation B. The advantage of having only one researcher observing the pupils is a relatively high consistency in interpreting displayed behaviour and increased reliability of the analysis thereof. A disadvantage is that not all sessions could be attended. Attendance is marked with * in Table 6.7 and Table 6.8.

The Experimental Context, Setup and Design

Table 6.8 Field day: Pupil group per learning space on Thursday

Timeline

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The experimental studies I and II took place simultaneously during six consecutive weeks, starting on Thursday in week 8 and ending on Wednesday in week 14. This period fell between the winter holiday (week 7) and the Easter holiday (week 15) of the school’s spring semester 2017. The first three weeks of the experimental period are referred to as Period I; the second three weeks as Period II. A general timeline of the key pre-, during and post- experimental activities is outlined in Table 6.9, for an enlarged version of the planning see Appendix I. The activities are clustered into three key phases: (1) pilot study to test the anticipated qualitative research methods, (2) installation and testing of the experimental lighting system and data loggers, and (3) the actual data collection activities during Period I and II, including the four field days. The three phases are further described in the next sections. (1) Pilot Study

The Experimental Context, Setup and Design

On Wednesday and Thursday in week 5 of 2017, prior to the installation of the lighting installation, a pilot study was done to test the prepared qualitative data collection protocols and templates, in particularly that of observing pupil behaviour during class. Mocking the observations in a pilot study served three functions. First, it gave pupils and teachers the opportunity to become accustomed to having an observer in their learning space. This helped mitigate behavioural changes due to an observer being present. Secondly, it was used to further refine the data collection protocols and the design of templates for taking notes. Thirdly, it helped the observer to become familiar with a normal class day including how pupils typically behave, the type of curricular activities the pupils undertake, and the course of a taught class. There were two key learnings from the pilot studies that informed the experiment. The first one was an insight in the structure of the 90-minute curricular sessions. The observed structure was comparable in all four spaces and suggested that each curricular session would include up to two segments of 30 – 45 minutes during which focussed-learning activities could take place (Table 6.10). This insight helped to structure the observation template more fittingly. The second learning was that during the focussed learning activities pupils would spread out to different areas of the learning environment. The spreading was much more diverse than initially anticipated. About half of the pupil group, 10 to 14 pupils, would settle in the central area of the learning space where the sound and behavioural data was gathered. The other half would be seated either in the adjoining group room, in the podium area, in the windowsills or in one of the common areas outside the learning space. As this number would fluctuate, the observation template was given an extra area to track of the number of pupils present during data collection.

PILOT STUDY

pre

6 m

INSTALL

HOLIDAY

7 m

8 t

- workshopS with teachers

- focus groups

- interviews with teachers

- observations during class

QUALITATIVE DATA COLLECTION

- handheld light measurements + (HDRI) photography

- sound recording

QUANTITATIVE MEASUREMENTS (SPOT)

- activate, measure + store data, re-activate recorders

MARTS

The Experimental Context, Setup and Design

3 WEEKS

QUANTITATIVE CLIMATE MEASUREMENTS (CONTINUOUS)

SITUATION B

SITUATION A

- collect data (X = FIELD DAYS) ROOM L1.02 + L2.04

FEBRUAR

- collect data (X = FIELD DAYS) ROOM L1.01 + L2.03

STUDY I + II

- remove (or permanently install pendants)

- save data and discuss light plan / STOP

- change lighting and save data / START PERIOD II

- start loggers and lighting / START PERIOD I

- test loggers and lighting TEST

- install of new lighting + data recorders

- meetings with EL TeamVest about installation

LIGHTING INSTALLATION + DATA LOGGERS

- test sound recording

- test observations

HOLIDAY

WEEK

DAYS

JANUAR

2017

11 f

3 WEEKS

SITUATION A

SITUATION B

12 t

14 t

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post

REMOVE

APRIL

t HOLIDAY

15 f

Table 6.9 Gantt chart of the research planning. Key activities are highlighted.

Table 6.10 Pilot study observations of the structure of curricular sessions

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Duration

Observation

5 to 15 minutes

A general introduction to the entire group in the podium area of the learning space.

30 to 45 minutes

Learning activities, some of which could be categorized as focussed-learning activities, with the pupils scattering throughout the different learning space areas.

5 to 10 minutes

Break

30 to 45 minutes

Learning activity (often a continuation of the first) in the places they had before.

5 to 10 minutes

Session closure for the entire group, either in the central area or again in the podium area of the learning space.

The Experimental Context, Setup and Design

(2) Installation and Testing The 24 pendants were sponsored and delivered to the school by Fagerhult in week 2. The indoor climate recorders, lent by Aarhus University, arrived at the school in week 3. During this week several meetings and site visits took place with the electrical contractor that would install the pendants and the indoor climate data loggers. The actual installation in the four learning spaces took place in week 7, and because that was a holiday week it did not interrupt any normal school activities. The works included positioning and fixation of the pendants and recorders, setting up electrical circuiting, and amending the control settings. Testing and adjusting of the experimental lighting system took place the first two school days in week 8. The removal of the pendants and loggers, and the restoration of the four spaces back to their pre-intervention conditions was initially agreed with the school board and was scheduled for week 15, a holiday week as well. The loggers were indeed removed during this week, but instead of taking out the pendants, the school requested these to be installed permanently (see Chapter 8 for further details about this decision). (3) Study I + II Data Collection Phase I of the field experiment commenced in week 8 of 2017, on Thursday 23rd of February. All indoor climate data loggers were activated the day before and continued logging until the end of the last day of Phase I, 15th of March. At the end of this day, the loggers were de-activated, the data extracted, and the loggers cleared. The first ten schooldays of Period I were allocated for the pupils and

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teachers to familiarize themselves with the lighting situations A or B present in their learning space. This was done to avoid the novelty of new lighting affecting the pupils’ natural behaviour. The two field days of Phase I then took place on Wednesday 8 and Thursday 9 March 2017. The research activities during both days included sound recording (Study I), observational studies, and teacher interviews (Study II), which took place before, during, and after the three curricular sessions scheduled per day. The activities of the researcher on those day were structured as per Table 6.11.

Table 6.11 Researcher activities during a field day Tim e

Activity

07:00 – 08:00

Preparing furniture layout in the four rooms Activating video and sound recorders in the four rooms

08:00 – 09:30

Video record session 1 in all four rooms Observer one room in person

10:00 – 11:30

Video record session 2 in all four rooms Observer one room in person

11:30 – 12:30

Checking on status of video and sound recorders, replacing memory cards Interview teachers of session 1 and 2

12:30 – 14:00

Video record session 3 in all four rooms Observer one room in person

14:00 – 16:00

Deactivating video and sound recorders in the rooms Interviewing teacher session 3

6.3.2

Autumn Experiment – Study III

Study III ran during the following autumn semester and revolved around administering two types of tests, an addition test and a figural creative thinking test, while pupils were exposed to one of the two lighting situations A or B. Both tests were designed to assess pupil performance in terms of their ability to concentrate, and the tests were successfully used in previous studies (Petersen, 2016).

The Experimental Context, Setup and Design

Phase II commenced in week 11, on Thursday 16 March. All indoor climate data loggers were cleared and re-activated the day before to continue logging until the end of 5 April, the last day of Phase II. At the end of this day, the loggers were de-activated, and the data extracted. The second pair of field days took place on Wednesday 29 and Thursday 30 March, and they followed the same data collection and research activity protocol as per Table 6.11.

Data Collection

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These tests were executed five times – on a weekly basis at the end of the third curricular session on Tuesdays an. The first test day was on Tuesday the 7th of November, the last test took place on the 6th of December 2017. The test took place at the end of a regular second curricular session. The teachers allocated the last 30 minutes of this session for pupils to perform the test.

The Experimental Context, Setup and Design

During each test session, pupils had to be seated at the same placement. A seating plan was therefore made together with the respective teacher prior to the start of study III for each pupil group. However, not all pupils could be seated in the central area of the learning space; the area of interest for this experiment. Some pupils would be seated in the group room, podium area or study areas outside of the learning space. Only the tests of pupils seated in the central area of the learning spaces were considered of interest, as these pupils were explicitly exposed to the standard and experimental lighting scenarios. However, as the testing took place during a regular curricular session, all pupils were participating to upkeep the motivation. All tests were collected however those made by pupils seated outside the central area were discarded from analysis. The indoor climate sensors were setup in each learning space before and kept logging during each test session. The same setup of the furniture was also ensured in place before each test session.

Pupil Groups In contrast to Study I and II, the tests were administered to only four pupil groups on the second floor, who were regularly scheduled to reside in either of the two Mathematics learning spaces L2.03 and L2.04. The younger pupils at level 1, who were included in the first two studies during the Spring semester, were excluded here. This was done firstly, because these tests were specifically designed for pupils of circa 9 – 12 years old. Secondly because the Folkeskole pedagogy is not supportive of testing the younger age group. In consultation with the two teachers of the groups on the first floor, it was therefore decided to not impose a test on pupils who had not yet experienced such a task. Thirdly, only four second-floor groups were tested as the school requested to limit the impact of this study, as it both required time and effort to attain consent from their parents and these tests would intervene with the regular teaching. Limiting to four groups was considered acceptable for the school, while still ensuring a representative test population. The four pupil groups demographic characteristics partaking in Study III are shown in Table 6.12.

Room

Name

Total

Female / M ale

Age

L2.03

Delta

14 / 10

10 – 11

Jupiter

12 / 11

11 – 12

Bravo

12 / 15

10 – 11

Nordlys

12 / 15

11 – 12

L2.04

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Table 6.12 Pupil groups and demographics

Study III followed the crossover research design, like studies I and II, and was performed as a repeated-measures study. The four pupil groups were paired; Delta and Bravo took the tests on a Tuesday, Jupiter and Nordlys took the tests on a Wednesday. Of each pair, one group would undertake the tests in a space staging lighting situation A, while the other group would be exposed to situation B. The four groups were systematically exposed to the two lighting typologies according to a predefined intervention schedule while conducting the two different tests, see Table 6.13. Table 6.13 Crossover Research Schedule Autumn Experiment

Rehearsal Period Week 1

Experiment Week 2

Week 3

Week 4

Week 5

Room L2.03 Room L2.04

Rehearsal Period An important lesson learned from previous studies (Petersen, 2016) was that the performance of the pupils increased significantly over time due to growing familiarity with the performance tests. To minimize this eﬀect, a rehearsal period of three testing rounds was added to the experiment. During this rehearsal period, the pupils completed each test with the purpose of familiarizing with each test’s formats. Systematic changes during the performance in the actual experiment due to learning and increased familiarity would therefore be minimized and a baseline was established. The baseline data could be used to adjust data from the crossover experiment, due to learning, increased familiarity, or lack of motivation. Thus, only data of week 4 and 5 was used for analysis.

The Experimental Context, Setup and Design

Crossover Research Design

Double-blind Experiment

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To improve the robustness of the experimental design, the study was conducted as a double-blind experiment. Therefore, the pupils were not aware of the intervention, alias its purpose to study potential effect of the artificial lighting pattern, and the actual purpose of the performance tests, and the research staﬀ were not aware of the intervention schedule until after the data was processed.

6.4

Summary

The Experimental Context, Setup and Design

The field experiment took place in two pairs of learning spaces at Frederiksbjerg Skole, following a crossover research design. Significant benefits of conducting a field experiment are that pupils, the subjects of interest, continue their normal (school) routines, in their normal environments they know very well, which allows to investigate for realistic behavioural change. Ideally though, in order to compare data gathered in these learning spaces, the environmental, demographic and pedagogical circumstances in each space would be exactly the same. However, because this experiment did not take place in a fully controlled laboratory-type of setting, inherently there were differences between spaces themselves and the conditions under which the experiments were conducted. The aim has been therefore to select four learning spaces where such differences between the spaces were judged to not influence the results significantly. Hereto an extensive analysis has taken place to compare potential learning spaces in the school, to ultimately arrive at four learning spaces deemed most comparable. These learning spaces are labelled L1.01 and L1.02, located on the first floor, and L2.03 and L2.04 on the second floor.

6.4.1

Comparability

The six aspects used for comparison were: (1) age group, (2) spatial layout, (3) interior design, (4) lighting, (5) acoustics and (6) curricular schedule. (1) Because of how the school is organised, pupil age is a given for each of the learning spaces, and the age groups are the same for spaces on the same floor. Comparability exists because all children on the first and second floor are in the developmental stage of school-aged children. Pupils in the two first-floor spaces are 6 – 8 years old, and pupils in the second-floor spaces are 9 – 12 years old. (2) Spatial organisation and interior design are more difficult to express quantitatively, and therefore a qualitative judgement has been made. Each learning space consists of different areas. The central area of the four learning spaces was selected as the

(4) With regards to the lighting conditions some quantitative and some qualitative judgements have been made. The existing artificial lighting tiles are positioned in a playful though organised fashion in all four rooms. The light has been designed to provide the same lux levels, following the same building code, and their output is adjusted in the same way in all four rooms. The controls in all rooms also work the same. The environmental conditions driving the availability of natural light cannot be controlled, but it is the same for all four rooms at the same time as they are orientated similarly. This is true for time of day (and time of year) and for weather conditions. The effect of environmental conditions for the daylight inside the learning spaces will differ slightly due to the different window arrangement per room. Even though the four spaces are selected to be adjoining and above each other, all facing the same direction. To understand these conditions better, a qualitative assessment was made informed by the quantitative measures of daylight factor (DF), useful daylight illuminance (UDI) and sunlight penetration. -

The relation between a given outdoor lighting situation and the resulting indoor condition is given by the DF. This has been simulated for the four spaces, based on the spatial characteristics of the learning spaces, their orientation, and their window layout. There are differences in the distribution of daylight factor for the four spaces—the aspect to note however is that for all of the spaces the simulated DF is below 2% for at least two thirds of the space, followed by a rapid increase of the DF towards the windows. To the human eye this threshold is arbitrary, and the four spaces will all appear similarly dark apart from the brighter spots near the windows. A detailed mapping of the DF for the four spaces was also made by manual daylight measurements. The outcome of that study confirms the patterns that were found in the simulations.

The Experimental Context, Setup and Design

(3) The layout of the furniture in each space, was agreed upon with the teachers so that it would remain comparable between the learning spaces throughout the experiment. Ultimately, it was expected that differences in the spatial organisation and interior design between spaces would be of less importance as long as pupils had adjusted to it long enough for it to be their normal, and as long as the spatial factors would not seem to cause variations in the other identified variables.

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focus area for the research and was used to compare the spaces. The four central areas are similar in dimensions and shape, with the second-floor spaces being slightly narrower than the first-floor spaces.

The effects of variation in daylight with time have been assessed by means of the UDI and sunlight penetration. The results were such that differences we not deemed significant in terms of perceived lighting in the four spaces.

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(5) The acoustic character of the spaces was initially assessed indirectly by evaluating the finishes and the furniture in the spaces. In similar shaped rooms the reverberation time, a measure for speech intelligibility, may be altered by surfaces that are more or less acoustically absorbing. Based on the visual assessment the rooms were judged comparable. In the pilot phase of the study acoustic measurements were performed that confirmed this assessment.

The Experimental Context, Setup and Design

(6) The curricular schedule in all four spaces is comparable because of how the day is structured in the school. The main difference between learning spaces on the two floors is that the younger groups on the first floor remain in their own learning space, where the older groups on the second floor rotate through different rooms for topical teaching. Each day, at both levels, is structured in three sessions separated by breaks. Each of those session may have two sub-sessions of 45 minutes. The first-floor spaces are used for a variety of curricular topics, while the second-floor learning spaces selected are used for mathematics classes. Therefore, the study focusses on investigating behaviour change initially separately; between first level pupils and between second level pupils. Only at a generic level results were discussed combined.

6.4.2

Control and Experimental Situations

The crossover research exposes pupils to a: (A) standard uniform light pattern and (B) experimental pools-of-light pattern. •

The standard situation (A) is the normal lighting situation as it was initially found in Frederiksbjerg Skole. The lighting situation encompasses the lighting fixtures and their automatic and manual controls. The lighting is uniform and responds to daylighting to provide a minimum lux level prescribed in the building code. The fixtures are generic ceiling tiles used throughout the school.

•

The experimental situation (B) adds a new luminaire type to the lighting design. Pendants are suspended from the ceiling to allow for a non-uniform lighting pattern that consists of pools of light. The automatic controls in the learning spaces are adjusted so that the ceiling tiles will be less prominent, and manual controls are added for the pendants. The experimental situation is thus not non-uniform per se, but it adds the possibility—leaving teachers in charge of their learning spaces.

The experiment was timed and organised to fit the normal curriculum without disturbing the normal goings-on in the learning spaces. It was conducted in two phases. Studies (I) – noise during class and (II) – observable disruptive behaviours were performed simultaneously during the weeks between the winter break and the Easter holiday of 2017. These studies included ten pupil groups in four learning spaces. Study (III) – cognitive performance was conducted in late autumn of 2017 and included four pupil groups in the two learning spaces on the second floor. The next chapter discusses the actual data collection, the analysis thereof, and subsequent results derived from these.

The Experimental Context, Setup and Design

After the installation of the pendants was complete, measurements have been taken to confirm the significance of difference between the standard and experimental artificial lighting patterns. Mappings have been produced of the different lighting scenarios possible, where ceiling tiles and/or pendants were activated during daytime as well as night-time. Christopher Cuttle’s framework of perceptible differences based on contrast ratios has been used to assess the lighting scenarios. A research protocol was established to expose the pupil groups to the standard and experimental situations. Some groups would be exposed to the standard situation (A) first, others to the experimental situation (B). When situation (A) was active in one space, situation (B) would be active in the adjoining space on the same floor, and vice versa.

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Because teachers have been extensively involved in the process, and easily controlled, the pendants were also frequently used.

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Data Collection, Analysis, Results and Conclusion

In the previous two chapters the approach, context, design and implementation of the field experiment have been discussed. This chapter describes the actual activities that took place to gather all the necessary data, the processing thereof, and the interpretation of results. The data and findings are presented following the structure of the research protocol as presented in section 6.3. Hereto, the first part of this chapter discusses the Spring experiment that included Study I – Noise during class, Study II – Disruptive pupil behaviour and a broad range of intervening variable studies. The second part of this chapter discusses the Autumn experiment that included Study III – Cognitive performance and a range of indoor climate studies. The third part of the chapter provides summaries for each of the studies and provides for an overall conclusion related to the original research question described in chapter 1.

C h ap t e r 7 Pa r t I I – A u t u m n Ex p e r im e n t

Pa r t I I I – S u m m a r y

Study I – Noise during Class

Study II – Disruptive Pupil Behaviour

Study III – Learning Performance

Intervening Variables

Indoor Climate Variables

Pa r t I I I – C o n c l u s io n

Pa r t I – S p r in g Ex p e r im e n t

Indoor Climate Variables Only

Chapter 7 – Structured in Part I (Spring Experiment), Part II (Autumn Experiment) and Part III (Summary and Conclusion).

PART I – Spring Experiment Section 7.1 describes the sound recordings that were undertaken for study I. The instrumentation of the learning spaces is described in detail, and the steps are outlined to arrive at relevant timeslots, corresponding sound plots, and a single time-average value of the measured sound level. Based on the assessment of several intervening variables for each timeslot, a series of 20 cases pairs with opposite artificial light patterns is formed that allows for a comparison between their respective sound levels.

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DATA COLLECTION, ANALYSIS, RESULTS AND CONCLUSION

Data Collection, Analysis, Results and Conclusion

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Section 7.2 describes the observations of pupil behaviour and the interviews with teachers and pupils that were made for study II. The qualitative data collected has been assessed following the method of thematic analysis. This process resulted in five themes that each represent an important finding from the data set: attraction, locality, calming, stationary, and variation.

Data Collection, Analysis, Results and Conclusion

Section 7.3 describes the measurements and observations of a range of intervening variables during study I and II. The architectural variables were excluded in the setup of the field experiment, while the expression of the interior variables was monitored throughout. Because of its confounding effect, the assessment of natural lighting has been given significant attention. A description of the instrumentation and interpretation of the lightlevel measurements is complemented with observational data and consultation of meteorological records of the testing period. Temperature, humidity and CO2 levels were also continuously measured to evaluate their potential influence. Subject and activity variables played a role in the analysis of studies I and II. The level of interference as a result is discussed per variable.

PART II – Autumn Experiment Section 7.4 describes the procedure of collecting the cognitive performance data for Study III, the statistical analysis thereof and subsequent findings that hint at a potential positive impact of the experimental pattern, pools-of-light, in learning spaces on pupil’s performance for a focused learning task, such as a mathematical exercise. Section 7.5 describes the measurements and observations of the same intervening variables during study III, the analysis thereof and subsequent findings. This section concludes with relating the results of the indoor climate variables with the cognitive performance findings.

PART II – Summary and Conclusion Section 7.6 provides for a summary of Study I – Noise during class, Study II – Disruptive pupil behaviour pupil behaviour, and Study III – Cognitive Performance. It also discusses the results from both studies about the intervening variables during both the Spring and Autumn periods. Based on the joint findings of these studies, section 7.7 concludes this chapter with a reflection upon the original research question this field experiment set out to answer.

Study I: Noise During Class

This study looked for perceptible differences in the sound level recorded in the four learning spaces whilst pupils were engaged in focussed-learning activities. The methods of investigation used were sound measurements supported by video recording. The data collected and analysis thereof to arrive at results is addressed in the next three sub-sections.

7.1.1

p. 187

7.1

Data Collection

The sound levels in the four learning spaces were recorded continuously between 08:00 and 14:00 during the four field days (see subsection 6.3.1). The recordings were made with a Brüel & Kjær 2250 professional sound level meter, provided by DTU Acoustic Technology. Each recorder was positioned at ceiling level, relatively central in each space. The recorder would be at least one meter away from any ventilation outlet to avoid noise interference. The sound sensor, at the tip of the recorder, was positioned 20 cm below the ceiling. This was low enough to enable unobstructed sensing for clean sound recording, and high enough so it would not draw attention and could not be touched. Figure 7.1 shows an example of the sound recorder placement in learning space L2.04.

Figure 7.1 Sound recorder positioning in learning space L2.04

Each sound recorder could store 0.1 second data samples up to a maximum of 8 hours each time. On each field day the four recorders were activated about 30 minutes before the first curricular session would start (circa 07:30) and deactivated about 30 minutes after the third curricular session finished (circa 14:30). The subsequent seven-hour sound logs, which included the three 90-minute curricular sessions of that day in the respective learning space were extracted and stored on a computer. The sound recorders’ data storage was cleared and readied for the following recording day.

Data Collection, Analysis, Results and Conclusion

Sound Measuring

Video Recording

p. 188

During the same curricular hours, time-lapse videos were recorded in the four learning spaces during the same four field days. This was done with the camera of a Samsung smartphone fitted out with a wide-angle lens so that the entire central area of a learning space would be in view. The camera was placed against the back wall of the learning space facing towards the windows, at a height just above adult eye height to prevent easy access for the pupils. To hide the recorders from view, they were covered with white paper shields, colour matching the wall. See Figure 7.2 for an example of a camera positioned in learning space L2.04.

Data Collection, Analysis, Results and Conclusion

The videos were recorded in time-lapse mode with one second intervals, meaning that a single frame was captured every second. The resulting video was processed to show 30 seconds of real time in one second of playback time. This method would allow the researcher to revisit each teaching session, while reducing the required data storage.

Samsung Video recorder

Figure 7.2 Camera positioning in learning space L2.04

7.1.2

Analysis

There were two main parts of the analysis process. The first part of the analysis revolved around reducing the raw sound-level recordings to an A-weighted, equivalent continuous sound level (LAeq) for each focussed-learning activity. LAeq is the time-average sound level expressed in dB(A), which is a metric for sound level related to human hearing and is therefore relevant for the perception of noise. The second part of the sound data analysis was to assess each of the recorded focussed-learning activities based on a number of criteria, and to select those timeslots that were considered similar for comparison between standard (A) and experimental (B) situations. Figure 7.3 illustrates the two parts and the sequential analysis steps taken to eventually arrive at valid comparison cases.

Extraction Curricular sessions

Extraction Timeslots FLA

TimeAverage dB(A)

Apply

Assessment criteria

Weather condition Number of pupils

Select

Timeslot Evaluation

Learning activity

combined timeslots, same spaces combined timeslots, different spaces

Sound behaviour

Reduction of Raw Sound Data to LAeq

single timeslots, different space

p. 189

single timeslots, same space

Time of day

20 comparison cases

Analysis of Sound Data

Assessment and Evaluation

Figure 7.3 The two parts of the sound data analysis, and the different steps per part

In total, sixteen raw sound-level recordings of circa seven hours were collected from four field days in four learning spaces. The recordings were processed with a Matlab script to convert them into A-weighted decibels, dB(A). This process resulted in sixteen dB(A) logs of circa seven hours long. The seven-hour logs were then reduced to three files that captured the curricular sessions: 08:00 – 09:30; 10:00 – 11:30; and 12:30 – 14:00. This process resulted in 48 unique dB(A) records of circa 90 minutes long. Appendix J.1 shows an overview of these 48 recordings. Within the curricular sessions, the timeslots were then isolated that contained a focussed-learning activity. The time-lapse videos were used to identify these timeslots and to determine their start and end times. The video analysis resulted in 38 timeslots of 40 minutes duration on average, for which the corresponding sound data was selected. This process is illustrated in Figure 7.4, and the corresponding sound log in Figure 7.5. The measured sound data for the recorded focussed-learning activities was then converted to a single value, LAeq for each of the 38 timeslots. Table 7.1 gives an overview of the LAeq for all 38 timeslots. See Appendix J.2 and J.3.

(1) reduction to curricular hours

(2) reduction to three learning sessions

Figure 7.4 Extraction of timeslot 01 according to three steps

(3) isolating focused-learning activity

Data Collection, Analysis, Results and Conclusion

Reduction to LAeq

Timeslot L1.01 of March 08:53 – 09:16 Timeslot 01 01 ---dRoom Room 1A Wed --- 8th Wed 08 March 08:53-09:16

p. 190

90.00

80.00

( )

70.00 60.00 50.00 40.00 30.00

time 08.53 08.54 08.55 08.56 08.56 08.57 08.58 08.59 08.59 09.00 09.01 09.01 09.02 09.03 09.04 09.04 09.05 09.06 09.06 09.07 09.08 09.09 09.09 09.10 09.11 09.11 09.12 09.13 09.14 09.14 09.15 09.16 09.16

20.00

Data Collection, Analysis, Results and Conclusion

Figure 7.5 Timeslot 01 sound levels

Table 7.1 LAeq per timeslot Room L1.01

AVE dB (A)

Room L1.02

AVE dB (A)

Room L2.03

AVE dB (A)

Room L2.04

AVE dB (A)

timeslot 01 timeslot 02 timeslot 03 timeslot 04 timeslot 05

56,0 68,7 58,6 57,6 62,4

timeslot 06 timeslot 07 timeslot 08 timeslot 09 timeslot 10 timeslot 11 timeslot 12 timeslot 13 timeslot 14 timeslot 15 timeslot 16 timeslot 17

62,1 61,7 64,3 53,4 65,8 63,8 63,9 63,0 68,5 56,0 65,7 67,6

timeslot 18 timeslot 19 timeslot 20 timeslot 21 timeslot 22 timeslot 23 timeslot 24 timeslot 25 timeslot 26 timeslot 27 timeslot 28 timeslot 29

63,3 66,6 67,2 66,6 66,9 63,0 corrupt 65,1 68,2 64,8 66,5 61,9

timeslot 30 timeslot 31 timeslot 32 timeslot 33 timeslot 34 timeslot 35 timeslot 36 timeslot 37 timeslot 38

70,0 55,3 64,5 63,9 63,1 59,4 59,5 61,2 65,8

Situation A – St andard Uniform Light Pattern Situation B – Ex periment al Pools-of-light Pattern

Assessment and Evaluation The 38 timeslots were categorized per learning space and labelled according to the artificial light scenario that was active during each timeslot (Figure 7.6). The relevant scenarios for comparison were A1 (standard situation, ceiling tiles on), and B2/B3 (experimental situation, pendants on with/without ceiling tiles). In most cases a single scenario would remain in place during a timeslot, though video records indicate that in some cases a switch took place between scenario B2 and B3 (ceiling tiles were switched on or off). The teachers said the reason to change between lighting scenarios usually is incited by a significant change in natural light. If more daylight enters the learning space, ceiling light may not be needed. Or when cloud appear and daylight drops, the tiles are needed.

Scenarios used forused Analysis Scenarios for Analysis A1

SituationSituation A – Standard A – Standard

SituationSituation B – Experimental B – Experimental

p. 191

A1 A0

scenarios scenarios B0 A1

uniform light pattern uniform light pattern

B1 B0

B2 B1

B3 B2

non-uniform light pattern non-uniform light pattern “pools of light” “pools of light”

The timeslots were then assessed based on time of day, weather conditions, number of pupils present and type of learning activity. These variables have been described as potentially intervening variables and are discussed for the spring studies in section 7.3. In addition, an assessment was made of the sound pattern. To this end the 38 timeslots were developed into annotated plots with normalised sound data. An example is given in Figure 7.7, the sound pattern plots for other timeslots are found in Appendix K.

ROOM 01.1.05 EXISTING LIGHTING 08 March 2017

Data Collection, Analysis, Results and Conclusion

Figure 7.6 Lighting scenarios A1 (standard uniform pattern) and B2 + B3 (experimental pools-of-light) used for analysis

ROOM 01.1.05 NEW

08:53-09:16

Timeslot 01 dBRoom L1.01 Wed01.1.05 8th of March – 09:16 Timeslot 01 --vægtet --- Room --- Wed 08:53 08 March 08:53-09:16

29 March 2017

total time dB average dB min dB max

00.23.42 56,0 35,0 74,4

total time dB average dB min dB max

Session Group Activity No of Kids

1A Panda Book work 8 - 10

70,00

Session Group Activity No of Kids

Light scenario

Ceiling ON

60,00

Light scenario

90,00

80,00

50,00

40,00

30,00

tim e 08 .5 3 08 .5 4 08 .5 4 08 .5 5 08 .5 5 08 .5 6 08 .5 6 08 .5 7 08 .5 7 08 .5 8 08 .5 8 08 .5 9 08 .5 9 09 .0 0 09 .0 0 09 .0 1 09 .0 1 09 .0 2 09 .0 2 09 .0 3 09 .0 3 09 .0 4 09 .0 4 09 .0 5 09 .0 5 09 .0 6 09 .0 6 09 .0 7 09 .0 7 09 .0 8 09 .0 8 09 .0 9 09 .0 9 09 .1 0 09 .1 0 09 .1 1 09 .1 1 09 .1 2 09 .1 2 09 .1 3 09 .1 3 09 .1 4 09 .1 4 09 .1 5 09 .1 5 09 .1 6 09 .1 6

20,00

30 March 2017

Figure 7.7 Timeslot 01 – Edited sound graph in decibel, complemented by additional criteria notes.

The sound pattern plots visualize how the sound levels varied during a timeslot, which may also be of importance. For example, the LAeq for two timeslots may be very similar, but one of these could be the result of a relatively flat curve, while the other curve fluctuated significantly with various peaks and drops. The latter, somewhat erratic variations could suggest that there were

total time dB average dB min dB max Session Group Activity No of Kids Light scenario

p. 192

significant moments of sound bursts or dips. The patterns of the sound graphs thus could indicate whether pupils were engaged relatively consistently with their task (flat curve) or were interrupted often (erratic curve). To visualise the sound patterns, the original sound graphs (for example Figure 7.5) were edited to represent a normalized course trajectory. These curves allowed to review each timeslot’s general sound variation over time. Based on the individual assessment of each timeslot, potential comparisons between timeslots with similar characteristics were explored. Comparisons have been made between single timeslots recorded in the same learning space, pupil groups and daytime segment, as well as between combined timeslots to explore more generic trends. In total 20 comparisons were made. The creation of comparison cases was informed by four guidelines:

Data Collection, Analysis, Results and Conclusion

•

Comparisons were predominantly made with data from the same floor. This is because the age range of the pupils and use of the learning spaces differs significantly between the first and second floor (see section 6.1.1).

•

Comparisons were predominantly made with data from the same daytime session. This is because the pupils’ general behaviour differs between morning and afternoon sessions (see section 7.3.5).

•

Comparisons were made between groups of similar size. A deviation of ± 2 pupils has been deemed acceptable.

•

Comparisons were made predominantly between groups engaged in book tasks (see section 7.3.5).

Timeslot comparisons were explored following five steps: Step 1: Between two single timeslots recorded in the same learning space. Comparisons were made between individual timeslots per learning space that featured similar characteristics but opposing light scenarios (A1 versus B2/B3). Some comparisons concerned timeslots from the same pupil group, others compared records between two different groups. Two examples of single timeslot comparisons are shown in Figure 7.8 and Figure 7.9 for Room L1.01 and Room L2.03 respectively. In both examples the same group was measured twice. These examples include each timeslot’s sound graph with average, min and max dB(A) levels, and a still photo from the video recorded during that timeslot to serve as an impression of the ongoing activity. Both examples indicate a reduction of the average sound level of 6.3 dB(A) and 1.8 dB(A) in favour the of the experimental scenario (B2/B3).

Room L1.01 – Afternoon Session (3) – Light scenario B3

dB average dB min dB max

68,7 40,2 85,0

6,3

difference

dB average dB min dB max

62,4 40,8 80,9

Figure 7.8 LAeq comparison between timeslot 2 (A1 Ceiling tiles) and timeslot 5 (Pendants only) in Room L1.01

Room L2.03 – Morning Session (1) – Light scenario A1

dB average dB min dB max

66,6 38,8 83,4

Room L2.03 – Morning Session (1) – Light scenario B2

difference

1,8

dB average dB min dB max

64,8 35,4 83,9

Figure 7.9 LAeq comparison between timeslot 21 (A1 Ceiling tiles) and timeslot 27 (B2 Ceiling tiles + Pendants) in Room L2.03

Data Collection, Analysis, Results and Conclusion

p. 193

Room L1.01 – Afternoon Session (3) – Light scenario A1

Step 2: Between two single timeslots recorded on the same floor. None of these comparisons were considered viable due to divergence of the assessment criteria. p. 194

Step 3: Between two or more combined timeslots recorded in same learning space. Certain timeslots that featured the same light scenario (either A1 or B2 /B3) and some but not necessarily all assessment criteria, were combined and compared. These timeslots could be from the same pupil group (level 1) or multiple groups (level 2). Step 4: Between two or more combined timeslots recorded on the same floor. Two of these comparisons were made between all standard and all experimental timeslots from the two paired spaces on the first and the second floor.

Data Collection, Analysis, Results and Conclusion

Step 5: Between all standard and all experimental timeslots recorded. This has been the most generic comparison made, disregarding specific characteristic differences between timeslots. Seventeen of the comparisons were the result of steps 1 – 3. The three others represent more generic comparisons as described in step 4 and 5. See Appendix L for an overview of which timeslots were included per case.

7.1.3

Results

The LAeq levels for the 20 comparison-case pairs are shown in Figure 7.10. The blue columns represent the LAeq of single or combined standard scenarios; the red columns represent the LAeq of single or combined experimental scenarios. The graph shows that the differences per pair are relatively small in absolute sense. The numerical differences, either as a positive or negative, are shown in Table 7.2 and visualized in Figure 7.11. A negative difference means the LAeq of the experimental scenario was lower than the LAeq of the standard scenario, suggesting that the experimental light scenarios (with pendants) featured lower average sound levels, indicating more quiet pupils. Table 7.2 Difference in LAeq per comparison case Comparison case

LAeq dB(A)

Comparison case

LAeq dB(A)

-1,44

-2,72

-0,17

+2,10

-6,30

-3,02

-1,50

-2,60

+0,10

-1,38

-4,00

-2,25

-1,80

+1,55

+0,15

-0,26

-4,10

-1,90

-2,78

-2,20

p. 195

Figure 7.11 Difference in the A-weighted, equivalent continuous sound levels (LAeq) per comparison case

In total 16 of the comparison cases resulted in a lower LAeq for the experimental situation. This means that in 80% of the cases a lower average sound level was measured in those timeslots that featured the non-uniform pools-of-light pattern compared to the standard Experimental scenario (B2/B3) situation with uniform lighting (Figure 7.12). Ave dB(A) lower then

Scenarios used for Analysis A1

80% 20% 100%

Situation A – Standard

Experimental scenario (B2/B3) Ave dB(A) higer then Standard scenario (A1)

Standard scenario (A1)

20 comparison cases Situation B – Experimental

Experimental scenario (B2/B3) Ave dB(A) lower then Standard scenario (A1)

20%

scenarios

80%

uniform light pattern

non-uniform light pattern “pools of light”

Figure 7.12 Distribution of comparison results

20 comparison cases - significance

70% 10% 20%

Experimental scenario (B2/B3) Ave dB(A) significantly higer then Standard scenario (A1)

no significant change

20%

Experimental scenario (B2/B3) Ave dB(A) significantly lower then Standard scenario (A1)

Data Collection, Analysis, Results and Conclusion

Figure 7.10 Twenty case comparisons of LAeq for standard (blue) and experimental (orange) scenarios.

Significance of the Differences

p. 196

To judge whether the differences in dB(A) were significant, the results were assessed as perceptible differences. The decibel scale is logarithmic. The guidelines as outlined in Table 7.3 were used to interpret the comparison results *. A change of 1 dB(A) is considered as just noticeable, a little more than the perceptive threshold. A change of +5 dB is perceived as twice as loud and is considered to be significantly noticeable (see section 5.3.1).

Table 7.3 Difference in LAeq per comparison case dB

Guidelines

Data Collection, Analysis, Results and Conclusion

0 – 1 dB

A change between 0 and 1 dB(A) would not be audible;

1 – 3 dB

A change between 1 and 3 dB(A) would be noticeable

3 – 5 dB

A change between 3 and 5 dB(A) would be well noticeable; Experimental scenario (B2/B3)

5+ dB

80% 20% 100%

A change > than 5 dB(A) would be significantly noticeable.

Ave dB(A) lower then Standard scenario (A1)

20 comparison cases Experimental scenario (B2/B3) Experimental scenario (B2/B3) Table 7.2 shows that the differences of the 20 comparison cases lie Ave dB(A) higer then Ave dB(A) lower then Standard scenario (A1) Standard scenario (A1) between -6,3 and +2,1 dB(A), suggesting that audible changes did take place. Interpreting these20% results following these guidelines 80% suggests that for 14 cases (70%) a noticeable to well noticeable decrease of sound level was measured, while two cases (10%) showed a noticeable increase. In four or the 20 cases (20%), the difference would not have been perceptible (Figure 7.13). Appendix M provides further numerical data on the comparisons.

Scenarios used for Analysis A1

70% 10% 20% 100%

20 comparison cases - significance Situation A – Standard Situation B – Experimental

Experimental scenario (B2/B3) Ave dB(A) significantly higer then Standard scenario (A1)

20% 10%

scenarios

uniform light pattern

Experimental scenario (B2/B3) Ave dB(A) significantly lower then Standard scenario (A1)

no significant change

70%

non-uniform light pattern “pools of light”

Figure 7.13 Distribution of comparison results - significance

* These guidelines were provided by the Acoustics department of DTU, a research collaborator, based on acoustic standards.

The applied analysis procedure and interpretation of the results based on perceptibly significant differences to the average human ear, suggest that the experimental lighting with activated pendants resulting in pools-of-light, led to decreased sound levels in the learning space in comparison to the standard situation with the standard ceiling tiles activated. This outcome may be further interpreted based on two informed assumptions. Firstly, the reduction in the sound level measured during class is caused by a change in activity sounds produced by the pupils and teacher (see section 5.3.1). Background noise, the other contributor, is assumed to have stayed constant during the measurements. This assumption was based on the acoustic assessments as outlined in section 6.1.4. The second assumption is that activity sounds are considered unwanted noise and disturbing during focussed learning activates. This implies that a decrease in the overall sound level implies less noise is experienced by the pupils, which in turn suggests less disturbances to their concentration. The data hints at that the experimental lighting scenarios may decrease the noise level and herewith improve the aural conditions for pupils in the learning space. However, it needs to be demonstrated that this reduction is caused by the change in artificial lighting. Other intervening variables identified that may also have influenced pupil’s behaviour during the experiment, are hereto discussed in section 7.3.

7.2

Study II: Disruptive Pupil Behaviour

This study looked for observable changes in three types of pupil behaviour (expressive, social and physical behaviours, see section 5.3.2) considered disruptive to one’s own or others attention to the learning during focussed-learning activities. The three methods of investigation used to collect data are: •

non-participant observations during pre-selected learning sessions in the four learning spaces;

•

semi-structured interviews with the teachers in charge of those sessions afterwards; and

•

focus groups or groups interviews with the pupils studied.

The data collected with these three methods and the collective findings are addressed in the next three subsections.

p. 197

Discussion

Data Collection, Analysis, Results and Conclusion

7.1.4

7.2.1

Data collection

Non-Participant Observation p. 198

The observational studies were all done by the author and took place in all four learning spaces during the two pairs of appointed field days, while the pupils and teachers continued their normal curricular schedule and activities. This accumulated to twelve curricular sessions (three curricular sessions of 90 minutes per field day) observed in person (see section 6.3.1). During these sessions the observing researcher was seated in one of the corners of the learning space. The observer’s attention went out to study those pupils present in the central area of the learning space. A template was developed to guide the observer’s attention towards three preselected ‘disruptive’ behaviours referred to as: (1) expressive, (2) social, and (3) physical behaviours (see section 5.3.2) and to add notes according to the observations made.

Data Collection, Analysis, Results and Conclusion

During each session the observing researcher would also regularly assess the learning environment itself; for example, if any changes to the artificial lighting settings were made, if the weather conditions or blind settings changed, or whether any of the furniture was moved. Any unexpected interruptions or incidences would be noted down here as well. The twelve observed sessions were also documented on video. As described in section 7.1, all 48 curricular sessions used in Study I were documented by time-lapse video in order to assess the characteristics of each sound ‘focussed learning activity’ timeslot. Though these observational video recordings were done real-time, so that any uncertain or unclear observations during a session could be revisited afterwards. Pre-study The researcher acted as non-participant observer, meaning to not interfere with or manipulate the situation being observed, but to just observe as an outsider. Those under observation, the pupils and teachers, were, however, aware that they were being observed. In this situation, there is a risk that these subjects become too conscious of their actions and do not behave and/or decide as they normally would, but rather in accordance with the observer’s expectations. In an attempt to avoid such data contamination, the observer undertook a pre-study a few weeks prior to the actual studies (see section 6.3.1). During these pilot days, the observer was present in the scheduled sessions; three on Wednesday and three on Thursday. The pilot days proved successful for two reasons. Firstly, it gave pupils and teachers the opportunity to become accustomed to having an observer in their learning space. It appeared the pilot allowed them to attenuate to the “novelty” of having researcher present in the learning space. During these pilot

p. 199

visits, pupils often came over interact with the observer, to ask questions, etc. Whereas in the following rounds of observation sessions, they hardly approached and appeared more ignorant. And secondly, the pilot days provided opportunity to test the observation template and anticipated technique to observe the pupils. Observational Procedure

(1) About five to ten minutes prior to commencement of class the observing researcher would be present in the room. During this time the pupils and teacher (if not already present) would enter the room and find their place. The observer wrote contextual and demographic details about the session in the template’s general box. For example, room number, date and time, which teacher was present and if accompanied by a teaching assistant, which pupil group was present, and the type of activity to be expected based on the curricular schedule. (2) During the actual curricular session of circa 90 minutes pupil’s behaviour and environmental conditions were observed and noted down in blocks of 15 minutes intervals. The attention of the observer was guided by four themed boxes on the template – see below for details on the template. (3) After each observational session was followed up with a short 5minute mini-interview with the respective teacher. This conversation would provide information whether any pupils were absent or newcomers, if pupils with special needs required specific attention, or whether a situation had occurred that is out of the ordinary, for example a fight or an interruption by an (unscheduled) visitor. The mini interview was also used to briefly verify the observations made related to the general mood of the pupils and atmosphere during class. A more detailed interview of about 30 to 45 minutes with the teacher took place the same day either during their lunchbreak or after their last curricular session. These detailed interviews allowed to discuss the behavioural observations made by the researcher, and assess whether these were agreed, disagreed or experienced differently by the respective teacher. For an impression of the learning space activities and pupil’s whereabouts during the observational studies see Figures 7.14 – 7.17.

Data Collection, Analysis, Results and Conclusion

Each observational session followed the same procedure and was guided by the observation template designed to guide the observer’s attention towards the three pre-selected ‘disruptive’ behaviours and several environmental conditions in the learning space (see Appendix N for the template). Each observational study followed the same procedure that included three parts:

p. 200 Data Collection, Analysis, Results and Conclusion

Figure 7.14 Impression of focussed learning activity

Figure 7.15 Impression of focussed learning activity

Figure 7.16 Impression of focussed learning activity

Figure 7.17 Impression of focussed learning activity

Observational Template The template included one general box to note contextual and demographic details of each session, and four themed boxes to guide the observer’s attention. These notes were also used to interpret the sound data in Study I (see section 7.1.2). These four themed boxes are: (1) Learning environment: notes describing the current weather condition, window blind setting, the type of artificial lighting active and any unexpected interruptions such as external noise, presence of sun light or glare affecting pupil’s behaviour; (2) Activity type: notes describing the type of (learning) activity ongoing, for example book or computer based individual exercises, collaborative groupwork or instructional activates; the respective setup, for example individual, pairs, smaller or bigger group tasks; and the role of the teacher during class, for example actively engaged with one or more pupils, mostly walking around attending individual pupils with questions, sitting with one or few pupils, or quiet to oversee the group at a distance;

p. 201

(3) Atmosphere and Mood: notes describing the kind of atmosphere the room and mood of the pupil group radiated as perceived by the observational researcher. These included generic descriptions as: lively, focused, intimate, chaotic, passive, active, sleepy, cheerful, energetic, etc. These notes could also describe more specifically pupil’s apparent mood. These descriptors were interpretations by the observer and could be coloured by her own emotional mind state. These subjective interpretations were therefore verified with the teacher in post-session mini interview (see 3 below.

•

Expressive behaviours: notes about pupil’s actions that didn’t appear to be directed at someone nor relevant to the learning. For example, talking out loud but not at or with someone; noise making such as grinning, groaning or sighing; displays of fidgetiness or restlessness such as wobbling on a chair, playing with objects; or displays of daydreaming, sleepiness, resting down on a table surface.

•

Social behaviours: notes about interactions taking place between pupils, or pupil(s) and the teacher, that are not relevant to the learning. For example, seeking attention from the teacher in a disturbing way for example by shouting out or waving arms instead of quietly raising a hand; seeking contact or interacting with other pupils seated nearby in a way that has no relevance to the task at hand, for example chatting, joking, elbowing; or seeking contact with peers further away or outside the learning space in a way that has no relevance to the task at hand, for example by shouting, signing or knocking on a window

•

Physical behaviours: notes describing any physical, or movement, behaviour pupils displayed that was not required, for example a toilet visit, or necessary for the learning, for example, to acquire a learning tool from a cupboard. Notes here would describe actions such as needlessly wandering around, changing seats or location in the room, or repositioning seats and/or desks.

See Figure 7.18 for an example of observational notes. Pupil Mapping As described in section 6.3.1, during the pre-study it became evident that at the start of a “focussed learning activity” pupils tend to spread out to different areas of the learning environment. This spreading was much more diverse than initially anticipated. Only about half of the group, circa 10 to 14 pupils, would commonly settle in the central area of the learning space where the

Data Collection, Analysis, Results and Conclusion

(4) Disruptive pupil behaviour: notes describing the three pupil behaviours identified in section 5.3.2:

p. 202 Data Collection, Analysis, Results and Conclusion

Figure 7.18 Example of template notes during observation

observations were directed towards. The other pupils would be seated either in the adjoining group room, the podium area, the windowsills or in one of the common areas outside the learning space and wouldn’t be visible for observation. The pre-study also evidenced that pupil numbers in the central area may fluctuate during a learning session. It appeared pupils occasionally change their placement between the different areas, for example first choosing to sit at a group table in the central learning area but later decide to relocate to a windowsill and continue working on the respective exercise more solitary. In an attempt to keep track of the number of pupils present in the central working area, a quick pupil map was drawn about every 15 minutes of an observation session. These maps were simply crosses representing a pupil marked on printed floor plan of the respective room. Per session this accumulated into four to five plan views. The average number of pupils was then used as a guidance per session. For an example map, see Figure 7.19.

p. 203 Room L2.03 Time block: 08:50 – 09:00

Figure 7.19 Example of pupil mapping during observations

Semi-Structured Interviews Each of the twelve observed session was followed up with an individual interview with the respective teacher of that session. The interviewer had also acted as the observer. This resulted in twelve interviews. Six teachers participated in the experiment, and each teacher was interviewed twice: once after a session with lighting situation A active in their respective learning space, and once after a session with lighting situation B active. Due to the crossover research design of the experiment, three of the teachers were interviewed first about their experiences with situation A, and second about situation B. The other three teachers were interviewed in opposite order. The interviews commonly took place in the respective learning space the observation took place in, while the appointed lighting situation A or B was active. The interviews were scheduled either during the lunchbreak or after the teacher’s last teaching session that day. Each interview lasted for about 30 to 45 minutes. Interview Template The purpose of the interviews was firstly to verify the observations made by researcher, and to examine whether these were interpreted rightly from the point of view of the teacher – who may be regarded the expert on his or her pupil’s behaviour. Secondly, to probe the

Data Collection, Analysis, Results and Conclusion

Room L2.03 Time block: 08:30 – 08:50

p. 204

teacher’s own perspective on the respective lighting situation, if or how they believed it is or is not affecting their pupil’s behaviour, and whether it affects their own way of teaching and managing class. To guide these interviews, a template was used with open ended questions organized in four topics (see Appendix O): (1) Practical use: to open the conversation, the interviews started with practical questions that revolved around issues as: ease of use; their preferred way of using the lighting system; any limitations, inconveniences or (dis)comforts experienced during class. It had appeared this could be a good approach to start an interview with someone not necessarily experienced with talking about the subject of light and lighting. Previous experience through collaboration with the two MSc students from the Copenhagen University (DK), revealed that teachers in general would be somewhat reserved due to their limited knowledge and/or confidence on the topic (see section 5.3.2). Starting a conversation about practicalities allowed the teacher to become ease into the topic.

Data Collection, Analysis, Results and Conclusion

(2) Atmosphere and Mood: the following questions probed the teachers’ own (negative or positive) experiences with and feelings for the lighting situation active, and their impression of the subsequent lit atmosphere of their learning space. Secondly, they were also queried about how they believed the lighting and subsequent room atmosphere was experienced by and influencing the pupils. (3) Disruptive behaviour: this set of questions queried the teachers about whether they believed the artificial lighting affected their pupil’s behaviour, and particularly those behaviours identified as potentially disruptive: (a) expressive, (b) social, and (c) physical behaviours. Here examples from the observational notes were used. If acknowledged, they were then queried about whether they believed these behavioural changes affected pupils’ ability to concentration on their task. The last question explored whether the teacher considered, or would consider, the artificial lighting a classroom management tool to influence pupil behaviour in class. (4) Dream scenario: the teacher was asked to describe their ideal artificial lighting for their learning space. Now that they became aware that artificial lighting may impact more than to provide for sight and illuminate the space, this question was used to gain insight into whether the teacher was missing or believed to be of benefit to pupils learning. In addition to these four predefined questions, 5 to 10 minutes of the interview time was reserved for discussing the observational notes made during the preceding session. This was done firstly, to validate whether the researcher’s observations were truthful interpretations of pupil’s behaviours. As the observer had only limited experience with pupil behaviour in learning environments

Figure 7.20 Example of template notes during interviews

The information surfacing due to these probing questions was collected by making notes on the interview template of seemingly relevant opinions, experiences, feelings or arguments. The interviews were also voice-recorded, which were revisited during the analysis of the data collected during these interviews. Follow-up interviews In addition to these twelve individual interviews, follow up interviews were conducted in October 2017, about six months after the experiment had finished. One of the outcomes of the experiment was that Frederiksbjerg School had requested to permanently install the new artificial lighting system in the four learning spaces, and roll-out the same concept in equivalent learning spaces within its building (this outcome is further discussed in Chapter 8). These interviews gave opportunity to further investigate teacher’s experiences and opinions after having used the experimental lighting system for a much longer time,

p. 205 Data Collection, Analysis, Results and Conclusion

prior to this research, misinterpretation thereof is plausible. Secondly, to discuss whether certain observations were considered significant or marginal. Ultimately, the teachers may judge most accurately what observed (expressive, social, or physical) behaviours may significantly impact pupils’ concentration. This was particularly informative for the analysis of the observational data. See Figure 7.20 for an example of interview notes.

during a greater variation of curricular activities and with more groups of pupils. The same interview template was used to guide these interviews, and five of the originally six teachers participated. One teacher had left the school during the summer break of 2017. p. 206

Focus Groups In addition to interviewing the six teachers individually, four additional group interviews, or focus groups, took place. Two of these sessions hosted the six teachers together, and two hosted a small group of six to eight pupils. Focus Group with Teachers

Data Collection, Analysis, Results and Conclusion

The first group interview with all six teachers present took place prior to the experiment. This session took place during week 5, as part of the pre-study. The aim to learn more about the teachers’ current experience with the (artificial) lighting in their learning spaces; what aspects were perceived as positive and what were negatives or could, in their perspective, be improved upon. And secondly, to discuss if they considered artificial lighting a tool of use to address (disruptive) pupil behaviour. This was discussed in consideration of the other tools available to manage a class. The information derived from these discussions helped to describe their current (norm) use of and beliefs towards light in the learning environment. This was considered helpful to benchmark their thoughts and beliefs against when interviewed after having experienced the experimental light in installation. The second teacher-group interview took place directly after the experiment had finished. This session took place at the end of week 14. The aim was to jointly discuss their overall experience with the experiment itself, and the experimental lighting design in particular. This discussion allowed to question each teacher’s individual experiences, and appoint which of these appeared to be shared, alias objective, or to be rather individual interpretations, or subjective. The most evident outcome of this discussion was the unanimous declaration the teachers would prefer the experimental lighting to remain permanently in their learning spaces, instead of being removed as originally scheduled. Each group interview was scheduled to last about 45 minutes. To guide the sessions, two specific interview guides were created, each with a short list of open-ended, probing questions. A printout of the interview guide allowed for space to make quick notes of responses and thoughts directly during the interviews. In addition, each session was also voice-recorded so that the conversations could be revisited. This process helped to refine the original notes made during both group interviews.

In addition, the opportunity arose during the experiment to conduct two 15-minute group interviews with two groups of pupils at second level (9 – 12 year). One session included 12 pupils from group “Charlie”, the second session 10 pupils from group “Jupiter”. As both opportunities only arose while conducting the research, no specific template was prepared prior. The sessions took place very organically, as non-moderated sessions. Pupils were able to express their perspective, sharing some interesting insights. These brief sessions were also voice-recorded so that the conversations held could be revisited.

Method of Analysis

The format of the qualitative data collected during the twelve observations, follow-up interviews and focus groups are written notes supported by video recordings of the twelve sessions observed and voice recordings of the interviews conducted. The method used to analyse this data is thematic analysis, as described by Braun and Clarke (2006), see section 5.3.2. The main goal of this method is to extract themes from the dataset. A theme captures something important about the data in relation to the research question: Does exposure to the pools-of-light pattern in the Folkeskole learning environment discourage disturbing pupil behaviours and herewith improve quietness during class? And if so, does this change significantly affect pupils’ learning performance? For a theme to be representative it should occur more than once across the dataset (thus not being a single occurrence). There is however no quantifiable rule that defines how often or how much proportion of the dataset should display evidence of a theme to be considered a theme. The key is to be is consistent in determining themes (and prevalence) throughout the entire analysis. Themes can be identified in one of two primary ways: the inductive or deductive way. In this research the inductive approach was used, meaning the process of finding themes occurred without trying to fit the data into a pre-existing theory or framework but to let the data speak for itself. The data was reviewed from a semantic perspective, meaning themes were identified explicitly and no underlying or deeper ideas or ideologies were explored. Brown and Clarke (2006) created a six-step guide in order to arrive at a set of themes. These six: 1. Familiarization with data. This may include re-listening and transcribing, or re-reading notes; 2. Generating initial codes. Following Braun and Clarke’s interpretation, a code captures one or more insights about the

Data Collection, Analysis, Results and Conclusion

7.2.2

p. 207

Focus Groups with Pupils

data. While revisiting the data, quick notes were made when potentially important observations were expressed. These notes were then reviewed again, combined when bearing similar meaning, and assigned a code. p. 208

3. Searching for themes among codes. Following Braun and Clarke’s interpretation, a theme encompasses numerous insights organised around a central concept or idea. Hereto, codes that appeared to represent or fitting an overarching theme were clustered; 4. Reviewing, comparing and clustering the themes into higher-level themes. This process helps to assess whether the themes from step 3 accurately represent the data set, or weather something is missing. In the latter case step 3 repeats until a satisfactory set of themes is created. These themes were next assessed for overlapping or similar meanings. Those who did were then combined into one higher-level theme;

Data Collection, Analysis, Results and Conclusion

5. Defining and naming, or labelling, these higher-level themes. This process is also referred to as labelling. A label is a word that captures or represents what that particular theme stands for, what aspects of the data it captures and what is interesting about it. 6. Producing results. Lastly, it is decided which of these higherlevel themes make meaningful contributions to understanding what is going on within the data, and how it relates with the research’s main question(s) or hypothesis. This process, also referred to as coding, was followed to analyse this research qualitative data set. For step 1 however, it was decided early onwards not to transcribe all the data collected due to bulk of it and time constrains of this project. Instead, each interview was relistened to while comparing it against the respective observation’s notes of the curricular session discussed. During these evaluations, codes were generated as per step 2. After these evaluations, the codes were collected and compared amongst to form themes (3), which were next clustered into higherlevel themes (4), defined and finally labelled (5). The latter steps turned out to be a rather iterative process of going back and forth between comparing and matching codes into themes. Five of these themes were eventually considered meaningful results in light of the research question. See Figure 7.14 for a diagrammatic overview of steps taken following the six-step guide by Brown and Clarke (2006). The diagram starts with step (1), the collection of the qualitative data, next the analysis thereof (step 2 – 5), resulting in five themes (step 6).

Observations

Focus groups

Interviews

raw data

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Qualitative data set

Thematic Analysis Codes Themes

results

Attraction

Locality

Calming

Stationary

Variation

7.2.3

Results

These five themes are labelled: attraction, locality, calming, stationary, and variation. Each represents a perspective of a perceived change in pupil behaviour related to concentration.

Attraction For each pupil group occupying one of the four learning spaces, the respective teachers made a placement plan indicating which table a pupil would be seated at either the larger group tables or one of the smaller individual tables, predominantly when working on a (individual) focussed learning activity. During the observation sessions however it showed that pupils remain relatively free to deviate from the default plan and sit where and with whom they wish for that session. It also was observed that pupils would occasionally choose to sit elsewhere than at the working tables, and for example seat themselves on the podium in the instruction area, on the floor or soft furniture, or in the windowsills. An observation that was addressed frequently by both the observer as teachers relates to these seating preferences. When the experimental situation (B2/B3) with pendant lighting was active in a learning space, more pupils were found (and counted) seated at tables with pendants above, than during the standard situation (A1) with the standard ceiling tiles. In these standard sessions’ pupils were found placed more dispersed throughout the learning space. The teachers who addressed this, believed that pupils preferred the pendant during focussed-learning activities, and were particularly attracted by the pendants when activated and created well visible “pools-of-light”.

Data Collection, Analysis, Results and Conclusion

Figure 7.21 Process of this study’s data analysis to five thematic outcomes

“.. The pupils really like to read close to the lights. They often ask me to switch them on during a task exercise and go sit closely” (teacher A)

p. 210

When discussing these observations with the pupils during the focus groups, it appeared they intuitively associate this type of lighting with the safe and comfortable atmosphere of their home décor. Most pupils said they have one or more pendants in their own homes. Most pupils expressed to feel more at ease and comfortable when sitting nearby an activated pendant when doing their (paper-based) exercise work.

“.. I like the pendant lighting and want to sit close to it. I think it helps me focus” (pupil A)

Data Collection, Analysis, Results and Conclusion

It was also discussed whether the pendants were visually comfortable, or possibly too bright as they are suspected just above eye-height and the light source is relatively close in comparison to the general lighting in the learning space. Though both pupils and teachers found them to be comfortable to the eyes, both at a distance as well as nearby. Thus, relative closeness of the light source didn’t prevent attracting the pupils towards the pendants.

“.. I do not feel blinded by the light, it makes actually makes me feel relaxed” (pupil B)

However, the observer and teacher also noticed that a few pupils generally chose to sit away from the pendants when activated – as attracted by the darkness instead of brightness. Their motivation therefore appeared to be that these preferred a more subdued and shielded place to work, in fact, away from the pools-of-light. These pupils considered these to expose them too much; they preferred to attract less attention and work more on their own or in pairs. They felt this allowed them greater privacy and shielding from peers while undertaking their activity. Whereas pupils sitting around the pools-of-light expressed preference preferred being amongst each other and feel part of a group. The variation of brighter and dimmer areas in the learning spaces seemed to cater well for both types of pupils; those who prefer to be seen and connected. As well as those who prefer more privacy.

“.. I think is it really nice that there is not so much light everywhere. Now I can choose where I like to sit and don’t have to do the same as anyone else” (pupil C)

Jointly these findings suggest that the experimental setting, with activated pendants creating pools-of-light, improved pupil’s general comfort in and with their learning space by offering a choice in micro-environments and heightening a feeling of safety. Most pupils appear to be attracted to the light and group together underneath. While some actually prefer a place away from the ‘spotlight’ and preferred a more subdued place to work on their learning task.

Locality As described in the first theme, pupils appeared attracted to position themselves at tables underneath active pendants. In this setting they were working on their curricular exercises in the context of a small group. The Folkeskole pedagogy encourages pupils to collaborate and learn from each other instead of consulting the teacher primarily. By working on their tasks while seated in these small groups, it appeared more natural for pupils to interact locally with their neighbouring peers instead with peers seated at other tables. Or in other words, the pendants appeared to discourage interactions between groups or pupils outside their own circle. Some of the teachers believed that this orientation towards neighbours also led to lesser disruptions during class, for example more quiet talk, less interactions between pupils seated at different tables, and herewith less shouting or talk across the room.

“.. I am not sure if the new lights have improved the concentration of the pupils directly, but I did notice they focus more on themselves or neighbours instead of the rest of the room” (teacher B)

p. 211 Data Collection, Analysis, Results and Conclusion

These observations suggest the pendants affected pupil’s pupil choice of placement. Both the researcher and teachers observed that most pupils were attracted towards the pendants. They were more often found seated together in small groups around a table where a pendant was activated. While in comparison, under the standard situation with only the ceiling tiles activated, pupils were more scattered across the learning space. At the same time, activated pendants create for a greater diversity in light conditions within the learning space. This allowed pupils to choose their own comfortable micro-environment according to their personal preference at that moment in time; either a brighter or a dimmer area. This indirectly improved their individual experience of comfort as they were able to choose what suited them best. Thirdly, the pendant as a luminaire type was considered a very familiar object for most pupils and associated with the safety and comfort of their home décor. This in itself was considered by the teachers an important side effect that contributed for pupils to feel more at ease in their learning environment.

p. 212

At the same time, those pupils that deliberately choose areas outside the pools-of-light to sit and work in, expressed they felt less bothered by their peers – both directly, for example they felt being less approached, as well as indirectly, for example they rated the learning space to be more restrained. The data suggests that the experimental setting with pools-of-light serves both type of pupils; those who prefer to sit in each other company and work conjointly, as well as those who prefer a more solitary arrangement. The experimental setting provided both with (more) opportunities to find a fitting micro-environment, and to decrease disturbances amongst and between pupils. The teachers believed this led to more suitable environmental conditions for all pupils to learn and thrive in.

Calming

Data Collection, Analysis, Results and Conclusion

The third theme relates to how the pendants, and subsequent pools-of-light, may have a calming effect on pupils. One of the teachers expressed for example that he found pupils to be less (quickly) agitated and delayed asking for assistance. Several mentioned they observed less wiggles and fidgeting during class; while another described the pupils voiced less urgency for him to respond to their questions directly. A third teacher believed the need for him to quickly attend to pupils decreased somewhat.

“.. I feel that I do not have to walk around so much to assist pupils individually” (teacher B)

Another observation originated from one of the mathematics teachers who noticed the pendants with pools-of-light had a particularly calming effect on pupils that were known to have certain behavioural or concentration issues and are generally viewed as quickly distracted or causers of disruptions during class. This teacher noticed that when these pupils behaved calmer, the entire class became calmer. Or in other words, calming those pupils whose behaviour normally has a relatively big impact on the group, indirectly benefited the entire class. This belief by the mathematics teacher was later discussed in the second focus group with all six teachers present and sparked a lively discussion as the other teachers could relate and supported this observation. The data set thus suggests that activated pendants, resulting in pools-of-light, have a relative calming effect on pupils. And this is particularly evident for those pupils prone to display disturbing behaviour. The entire class benefits when their behaviour was experienced to be subdued.

The fourth theme describes that active pendant lighting seemingly encourages pupils to stay in their place for longer during exercise time. There was clear agreement amongst the teachers interviewed that necessary get-up-and-walk activities, for example a visit to the restroom, and learning-related get-up-and-walk activities, for example to approach the teacher or to take an item from a storage cupboard, didn’t appear to be affected. Pupils would undertake these regardless the lighting situation present.

p. 213

Stationary

“.. My impression is that the pupils pay more attention on their own area and feel less a need to visit pupils seated elsewhere. I cannot say for sure, but I believe I am less busy asking pupils to go and sit down again” (teacher C) There is no quantitative data, such as counting non-learning related pupil movements during a session to support this belief. It therefore remains an informed assumption that activated pendant lighting appears to discourage pupils to move around without a learning-related purpose. It is important to note that during discussions around this theme, several teachers also pointed out that lesser get-up-and-walk activities was mostly appreciated during these specific focussed learning exercises. Various other curricular activities in fact thrive on social interaction, collaboration and communication. During these activities, teachers would encourage pupils to approach each other, interact and collaborate. During these sessions it could be beneficial to deliberately not activate the pendants. However, this hypothesis was not investigated.

Variation The fifth theme relates to room appearance and variability thereof. Both pupils and teachers commented how the experimental lighting system allows for greater variation in the appearance of a learning space. Switching between the system’s two luminaire types, pendants and ceiling, tiles instantly changes the perceived appearance of a learning space.

Data Collection, Analysis, Results and Conclusion

Though certain non-learning-related get-up-and-walk activities that pupils commonly also show, were thought to occur less frequent when the pendants were activated. These concern activities where a pupil would get up without any direct learning-related purpose, for example when feeling restless, wanting to wander around or to attend a pupil seated at another table or place in the learning space for a social chat.

“.. It took me by surprise how the same room can appear quite different because of the lighting. I knew from my own home, but I didn’t think of it in the classroom – to me a learning space was supposedly to always look the same. How wrong I was!” (teacher F) p. 214

“.. I like that we do not have the same lighting on all the time. I or the pupils can make some changes, that work best for mood of my pupils that day” (teacher C)

The two main lighting situations (A versus B) explored with the experimental lighting system were evaluated by the observing researcher, pupils and teachers as following:

Scenarios used for Analysis

Situation A – Standard (ceiling tiles only)

Data Collection, Analysis, Results and Conclusion

The lighting condition that appears when only the ceiling tiles are – Standard Situation B – Experime activated was Situation commonlyAlabelled by the teachers and occasionally pupils with reference words as: •

practical, which refers to that the teachers considered these lighting tiles simple and use – they trusted to scenarios B0 themB1 A0 A1 easy to illuminate the room will and evenly and said they normally would not worry or pay attention to identify inadequate lighting unless prompted by the pupils;

•

clean, which refers to what the teachers described as: the uniform light pattern non-uniform ligh lighting to be the ‘same everywhere’. This was considered an “pools of lig adequate form of illumination for their own and pupil’s eyes without causing discomfort;

•

generic, which referred to the teacher’s belief that the lighting tiles didn’t imply or reveal what type of space it concerned or what activities were hosted. It is the type of lighting that could be applied anywhere; it does not suggest a specific identity.

The subsequent lit appearance of the learning space in situation A was affiliated with reference words as: •

hospital-like, which was described to represent a feel of artificial and sterile. Not a child-friendly type of lighting;

•

equal, which was described to represent a feel of universality, to cater for everyone, and for all the same. One teacher referred to it as a democratic lighting condition; all pupils are lit the same as is their surrounding environment. Nothing is given priority, no desk no pupil.

Scenarios used for Analysis •

dull, referencing that this type of illumination appeared to lose its presence relatively quickly and doesn’t provide for Situation A – Standard Situation B – Experime much visual stimulation.

In contrast, the lighting conditions with activated pendants, and scenarios wasB0 A0 B1 particularly if the ceiling tilesA1 were deactivated, referenced with words as:

•

changeable, refers to the ability to change between the two types of luminaires (ceiling tiles and pendants) was highly uniform light pattern appreciated both by teachers and the pupils. Due to the non-uniform ligh “pools of li simplicity of their control, alternating between both could very easily be achieved. This allowed the teachers to quickly adapt the lighting – either when they considered it of use or beneficial, for instance when pupils started to lose attention, a change in the lighting would bring them back. Or when pupils informed the teacher, they preferred a change. The data set collected during study I indicated that a change in lighting setting did occurs during class, however it appeared limited to once or twice only. The lighting setting didn’t alternate too often; which may become a nuisance in itself.

•

recognizable; the pendants as interior objects made the space appear more comfortable, with several teachers referencing to their living room. This similarity was believed to fortify a feeling of safety, which was believed to benefit pupil’s learning. Pupils who feel at safe and comfortable, don’t need to spend their time being alert or worrying – instead focus their attention to their learning;

•

care, referring to a concern most teachers expressed towards their own classroom management load. They felt they had to pay greater attention to make sure the lighting situation worked for all pupils. Where active ceiling tiles ensure a learning space would be illuminated well and evenly, active pendants result in relatively bright and dark areas. The teachers felt, particularly during the first days of use, a greater responsibility to actively check if each pupil was able to visually perform well and adjust if needed. This task required their active attention; time that could not be invested into the actual task: teaching. This meant the new pendants needed some time of the teachers to accustom to. Though most teachers commented that after a week of use, they started to understand how the pendant light was behaving in the learning space, and how to use their locations to their benefit. The same accounts for the pupils. Most appeared naturally drawn towards the pools-of-light though some preferred the exact opposite. It took a few days for pupils the latter preference to find their comfort and

Data Collection, Analysis, Results and Conclusion

p. 215

Situation B – Experimental (pendants with or without ceiling tiles)

place in the learning space. But when they did, they felt more at ease then in the standard situation.

p. 216

The subsequent lit appearance of the learning space in situation B was affiliated with reference words as:

Data Collection, Analysis, Results and Conclusion

•

cosy, with the pendants present and activated, the learning space felt more like a living room with several zones or areas to use instead of one large space. The average number of pupils in a group is about 24. It may feel cramped when these are seated in the central area of the learning space. However, with the pendants activated, it appeared the pools-of-light emphasises each of the separate groups bathing in light instead of the larger room as an entity. This visual was closely linked to that of the living room.

•

intimate, pupils described feeling closeness to a few pupils instead of the entire group when seated in a pool of light. While the teachers described that overseeing a few teams of pupils was easier to manage rather than one large group. They could attend each group separately and address any issues or questions, while the other groups would continue their task. It was believed there were overall less disturbances to each pupil than when having to address the entire group more often.

•

relaxed, although a positive attribute of the pendants was the feeling of comfort and safety, some concerns were expressed that the pendant only situation may result in pupils becoming a little too “relaxed”. Like pupils would feel and act as if they were seated on their couch at home, possibly falling asleep or becoming drowsy. However, this may occasionally have occurred, most teachers described this association to have been more of a concern prior the experiment than it actually proved to be.

The described characterizations suggest that the possibility to set different lighting conditions in the learning space may aid the teacher in managing his or her pupils. The two lighting conditions discussed here, standard and experimental, were found to provoke different perceptions and experiences, which in turn was described to influence the teacher as well as pupils. Matching an artificial lighting condition to the right learning setting, which may differ per tasks, activity and even mood state of the pupils, is key in benefitting from such system.

7.2.4

Discussion

The five themes address the responses elicited in pupils and teachers by the experiential lighting system, and the experimental setting with active pendants in particular, from different

•

Heightening pupil’s comfort in the learning space by comparison with ones living room, and a feeling of safety;

•

Attract pupils while at the same time acknowledge pupil’s individual “light” preferences by offering different luminous micro-environments including subdued areas;

•

Have a calming effect on pupils, and particularly those pupils prone to display disturbing behaviour;

•

Discourage pupils to move around without a learning-related purpose, and stay seated longer;

•

Offer the teacher a way to harmonize the learning space’s appearance with pupil’s mood, or direct pupil’s mood and attention to match with the activity at hand.

These observed changes may all be considered to improve one’s general feeling of comfort and to decrease occurrences of disturbances. Both imply better circumstances for pupils to concentrate as: feeling safe allows a pupil to let go of a state of alertness and instead focus on the task at hand; being able to place oneself in a micro-environment that matched one’s personal preference increases comfort even further. Calmer pupils, less fidgetiness and unnecessary movement implies less disturbances occur to oneself and peers in the learning environment. Although most of these changes are ignited by the presence and activation of the experimental scenario, alias by activating the pendants, it also appears the variability the experimental system allows the (teacher to) adapt learning environment to presented circumstances. Overall this to better the environmental conditions in the learning space. The observed changes by the experimental scenario appear to be instigated by two characteristics of the pendants: •

The pendants’ physical identity. Pendants appear to be familiar and recognizable objects that most pupils (and teachers) were familiar with from their homes. Pendants are associated with certain form of usage, being positioned above a table (working) surface, and with a rather intimate atmosphere. Because of such familiarity, simply the presence of pendants already evokes some of the changes observed.

Data Collection, Analysis, Results and Conclusion

The experimental lighting system that included active pendants creating pools-of-light was believed to:

p. 217

viewpoints. Jointly they seem to imply that the experimental lighting creates a learning environment that is able to acknowledge, support and steer pupil’s mood and behaviour during class.

•

p. 218

The pools-of-light. Appear to attract most pupils intuitively towards them and create for a local feeling of intimacy. It appeared pupils would interact more amongst the group instead of with others seated at other tables or places. They also seemed to remain seated for longer and be less fidgety.

Other Findings Three other findings emerged from the data that could not be placed within a theme yet considered relevant in light of this research.

Data Collection, Analysis, Results and Conclusion

Visual (dis)comfort. In general, both pupils and teachers did not find the new pendants to be bothersome. The brightness of the light sources (which are relatively close to the eye) as well as the pools-oflight falling on the table surfaces were regarded within normal visual comfort conditions. The physical presence of the pendants was also considered acceptable. They were left alone, none got damaged during the experiment and it was not observed any of these were harmed. Only during those occasions that tables and seats had to be moved around for alternative activities, the pendants floating freely in the air was considered unpractical. Thus, a type of pendant that could be either strung up against the ceiling or temporarily be removed, would have been ideal. Pendants made young pupils feel less exposed. This was particularly addressed by the two teachers at first floor, who were responsible for the youngest pupils participating in the experiment. The average height of these pupils is significantly less than a full-grown adult, though their learning spaces are designed for the latter. Hereto the height of the space appears to feel too “big” for these pupils. The teachers describe how they often would seek out places to sit underneath something, for example a canopy or tabletop. Their interpretation of this behaviour was that pupils are looking for a safe space, one less exposed or out in the open and more shielded. Interestingly, activated pendants appear to have such effect; as if they bring the ceiling down. The pupils seemed to feel comfortable in their respective rooms and less inclined to find a covering spot. This may not necessarily impact their concentration but can be considered to benefit their overall comfort with their environment. Ease of use. Key for any electrical (lighting) system inside a building to be used by occupants, is for its controls to be accessible and easy to manage. Various digital systems have come to market the past years, allowing for sophisticated regulation of lighting or other environmental variables of indoor spaces. Though in learning environments these appear often not (well) used. With the teachers being occupied with managing their class and running the teaching, they often lack time and attention to address these options, which end up not used or ignored. The choice to use simple wall switches for teachers and pupils to (de)activate the

Intervening Variables Studies

This section describes the measurements and observations of identified intervening variables, conducted in spring, during study I and II as part of this field experiment. The collected data will be discussed, and conclusions will be drawn about whether the variables are likely to have distorted the results of study I and II, and about the comparability of the 38 timeslots. Indoor climate variables natural light, temperature, relative humidity and CO2 level have been measured through sensor instrumentation continuously throughout the experiment. The other variables have been observed and were intermittently checked at pre-set time intervals during the experiment. The amount of natural light in the space, due to weather conditions, has led to the exclusion of an afternoon teaching session in two learning spaces from comparisons. Time of day and the number of pupils that were present has affected which timeslots were compared in the analysis.

7.3.1

Natural Light

The manifestation of the natural light indoors potentially affects the perception of artificial light in the learning spaces. In the setup of the experiment simulations were performed to assess the natural light situation in each learning space. The results of the simulations were confirmed with a lux-mapping using a hand-held illuminance meter that has been conducted during the field days, in-between observation sessions. The results of that mapping are discussed as part of the setup of the lighting installation in subsection 6.2.5. Continuous light level measurements during the experiment were undertaken to assess whether changes in natural light should be considered in the analysis. Natural light’s appearance was also considered, informed by pre-experiment interviews with teachers, and by observations of the sky conditions and the blind settings during the experiment. The results are discussed here.

Data Collection, Analysis, Results and Conclusion

7.3

p. 219

lighting is considered a crucial choice for this experiment success. Both teachers and pupils could access and use so easily, the threshold for using these was very low. In addition, the pendant is also an object that is visible; it sits in one’s line of sight. They are not secretly hidden light sources tucked away in the ceiling, but well visible in one’s sight. Hereto, they were not forgotten about a few days into the experiment when their novelty wore off. But instead pupils and teachers were constantly reminded of their presence, and once got used to them, felt even more comfortable to alternative with them. This too is considered a crucial aspect for any added feature to succeed in practice.

Continuous Light Measurements

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For the continuous measurement of light levels, the four learning spaces were each instrumented with two light level loggers. For calibration, one learning space also featured a more advanced photometric light level logger. Two Onset HOBO UA-002-64 pendant loggers (Figure 7.22) were installed in each space:

Data Collection, Analysis, Results and Conclusion

•

One was placed in a windowsill, horizontally, and facing up (Figure 7.24). This logger would record the natural light as it appeared outdoors. The windowsill position varied a little in each space. Three loggers were therefore placed at a similar height of about 2 m above the floor. Space L2.04 only allowed floor-height placement.

•

The second logger was placed centrally in the space, suspended 25 cm below the ceiling, facing the windows (Figure 7.25). This logger would measure both natural and artificial light.

The position of all loggers is indicated in Figure 7.26 – Figure 7.29.

Figure 7.22 Hobo Light Logger

Figure 7.23 LI-COR Light Sensor

Figure 7.24 Light Logger Windowsill

Figure 7.25 Light Logger Space

p. 221 Figure 7.26 Space L1.01 HOBO loggers

Figure 7.27 Space L1.02 HOBO loggers

Figure 7.28 Space L2.03 HOBO loggers

Figure 7.29 Space L2.04 HOBO loggers

Because the HOBO sensors measure a wide spectrum a LI-COR Photometric LI-210R sensor (Figure 7.23) was installed in room L2.03 next to each HOBO to reference the results from the HOBO sensors to the spectral sensitivity of the human eye. The use of HOBO sensors was practical—they are battery powered, more robust, and significantly more affordable than LI-COR sensors. The comparison between data from both sensors is given in Appendix P. The trend of the natural light is assessed for the duration of the entire experiment and more specifically for the field days. The data from the loggers in the four spaces was reduced to the curricular hours between 08:00 and 14:00 of the 30 measured school days, 15 days in each period. Plots for average day values in each period in each room are given in Appendix Q. The windowsill loggers show a relatively large variation over the duration of the experiment, which is not surprising given their direct exposure to the sky. The values of space L2.04 are significantly lower than those in the other spaces, likely due to the divergent positioning of the sensor in that space. Some similarity in pattern can be discerned between the spaces, but the readings do have less relevance for the general perception of light inside the space. This is in accordance with the simulations and manual luxmappings that were conducted for the setup of the experiment.

Data Collection, Analysis, Results and Conclusion

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The loggers inside the space show a more constant and aligned picture with some more variation in period II of the experiment (Figure 7.30 – Figure 7.33 – the four field days are highlighted with a circle). The readings here include contributions from the artificial lighting. Because it was found that during curricular hours the artificial lighting was generally activated, significant variations in the extracted light intensity averages may be attributed mostly to variations of natural light. The plots indicate that light intensity levels averaged mainly between 100 and 500 lux, which are standard indoor light intensities. The patterns of each graph further indicate good comparability between the spaces, because corresponding peaks and valleys can be clearly identified.

Figure 7.34. For each plot, the lighting scenario is indicated that was present that day. This was either A1 (standard situation, ceiling tiles only), B2 (experimental situation, ceiling tiles and pendants), or B3 (experimental situation, pendants only). Because the HOBO loggers were positioned above the pendants, they would have registered the output of the ceiling tiles directly, but only some indirect effects from the pendants. What can be seen in the plots is that the light levels across the spaces are closely aligned both in the trends and actual light levels. The exception is field day 2, where the weather showed a lot more variation throughout the day with bursts of direct sunlight hitting the sensors; particularly the sensor in space L1.02 seems to be directly hit a number of times during the morning. For the secondfloor rooms, there is alignment during the morning until about 11:00 after which levels in space L2.03 go up, while in space L2.04 they remain low. It might be the sensor in L2.03 was moved a little. The early peaks that can be observed in the plot from field day 2 in space L1.02 fall in the first break of that day, and therefore both morning sessions seem unaffected by direct sunlight. Sunlight cannot directly enter through the windows in the afternoon, but the light levels in space L1.02 are relatively high, nevertheless. Comparing data from a timeslot in the afternoon of field day 2 in this space with other timeslots should therefore be done with care, however, an observer was present in L1.02 during that time without remarking anything extraordinary. Even though the first and second floor measurements in the morning of field day 2 seem to diverge, the alignment of L2.03 and L2.04 combined with the presence of an observer in L2.04 during that time, suggest that at least data from timeslots in the morning can be used to compare to other cases.

Data Collection, Analysis, Results and Conclusion

The trends of light intensity in the spaces between 08:00 and 14:00 for the four field days are presented in

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For period I and II the weather records of central Aarhus have been consulted from the archive of the Danish Meteorological Institute (DMI). For an overview of these records, see Appendix R. For the four field days the records are presented in Figure 7.35. The graphs of these four days, during the hours of interest (morning 08:00 – 09:30 and 10:00 – 11:30, afternoon 12:30 – 14:00), show semiclouded, foggy and overcast conditions for 6-hour intervals. Even though this data is fairly course, the semi-clouded conditions are indicative of potentially varying conditions with patches of direct sunlight. Observations from the field days have noted similar conditions, although no significant variations have been noted, even though these variations might show in the sensor readings. This would indicate that even though changes were measurable, for occupants in the space they were not clearly noticeable.

p. 225 Field day 2: Thu 9th March semi-clouded morning semi-clouded afternoon

Field day 3: We 29th March foggy morning semi-clouded afternoon

Field day 4: Thu 30th March overcast morning semi-fog afternoon

Figure 7.35 Field day weather records

Blind Settings For all four spaces the blind settings were monitored, either by the observer in the space, or by consulting the time-lapse video recordings of the experiment. The blinds are deployed automatically if direct sunlight is detected on the facade for a certain duration, or they can be controlled in each space by the occupants. Deployment of the blinds significantly alters the lighting condition inside the space, but no deployment was noted during the field days. This is a further indication that direct sunlight might have occurred during the field days, but that it would have occurred in short bursts, leading to relatively large changes in illumination close to the windows.

7.3.2

Temperature and Air Quality

Temperature and air quality were measured throughout the experiment in four learning spaces. For this purpose, sensors were installed in all four spaces to measure temperature, relative humidity (RH) and CO2. Temperature and RH were measured with two Tinytag sensors (Gemini Data Loggers: Tinytag Plus 2 TGP4500, Figure 7.36). CO2 was measured with a Fluidic Vaisala GMT220 Carbon Dioxide (CO2) Transmitter (see Appendix X). The Tinytags were placed on either side of the space, near the back wall and the facade, and the CO2 sensor was placed centrally in the room. All sensors were placed just below the ceiling, strategically away from air vents and ceiling luminaires (Figure 7.38).

Data Collection, Analysis, Results and Conclusion

Field day 1: Wed 8th March semi-clouded morning overcast afternoon

p. 226 Figure 7.36 Tinytag

Figure 7.37 CO2 sensor

Figure 7.38 Location of sensors in Room L1.02 (marked in red)

Data Collection, Analysis, Results and Conclusion

All devices continuously logged their respective data throughout the six-week period. CO2 levels were logged every two minutes whereas the temperature and humidity levels were logged every five minutes. The collected temperature, RH and CO2 data was treated similar to the light intensity data. The logs were split in two periods, after which data corresponding to the curricular hours between 08:00 and 14:00 on schooldays was extracted. For an overview of average, minimum and maximum values per research day, per learning space, see Appendix S. Due to the similarity between graphs in different spaces, averages for all spaces are displayed in Figure 7.39 – Figure 7.41 as an indication.

Assessment The assessment of the indoor climate variables was based on the recommendations in DS/EN 15251:2007 (Dansk Standard, 2007). The results are comparable between spaces and are within the recommended ranges. This suggests that indoor climate variables have not significantly affected the results of study I and II. •

The temperature measurements indicate stable conditions during the experiment with average temperatures ranging from 20.5 °C to 21.5 °C. These fall within the recommended range of 20 – 24 °C.

•

The RH measurements varied a bit more, following the outdoor weather conditions in a range of 32 – 55% RH, which is considered acceptable.

The CO2 measurements indicate stable conditions, with an average range of 700 – 900ppm, well within the recommended range of 400 – 1000ppm. Exceptions occurred on day 6 with a peak above 2000ppm, and on day 28, with an average level of 1400ppm. The exceptions appeared to be days where pupils had been attending the spaces during breaks in larger groups than normal due to adverse weather conditions. These days were not field days.

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•

7.3.3

Interior Variables

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The furniture and its layout, and room decorations have been identified as potentially intervening variables. These aspects have played a role in the room selection, and following that, a fixed setup had been agreed with the teachers in the spaces. For that purpose, the setups in each room were photographed, see Figure 7.42 – Figure 7.45. These photographs were used during the experiment to review, and when necessary to correct the expressions of both variables. These reviews took place twice, both just prior to each field day pair. During these reviews the four learning spaces were visited and compared against the original photos. When a difference was spotted, the misalignment was corrected.

Data Collection, Analysis, Results and Conclusion

During these reviews, no changes to the furniture or decorations were found that could not be corrected. Hereto it can be concluded that the interior variables did not change significantly during the studies, and therefore can be excluded as intervening with the results of study I and II.

Figure 7.42 Interior of room L1.01 as seen from facade (left) and back wall (right)

Figure 7.43 Interior of room L1.02 as seen from facade (left) and back wall (right)

p. 229 Figure 7.45 Interior of room L2.04 as seen from facade (left) and back wall (right)

7.3.4

Subject Variables

The ten pupil groups and six teachers were subject variables that could potentially interfere with the research outcomes. The groups of pupils have been compared prior to the start of the research and teachers were interviewed to establish comparability. For continuity is was critical that pupil groups and teachers would not change significantly during the research and especially during field days. The groups were discussed with the teacher in a short interview after each observation session. For the sessions not observed, the school administration was consulted. None of the groups underwent changes beyond sick leave of the occasional child. There were, however, changes in the number of pupils present in the central learning area during the tests. This has been assessed based on the time-lapse video recordings. The teachers were also tracked to be teaching their normal groups during the experiment. For sessions not attended, the time-lapse video recordings were consulted. No changes had occurred. This suggests that subject variables have not significantly affected the results of study I and II.

Data Collection, Analysis, Results and Conclusion

Figure 7.44 Interior of room L2.03 as seen from facade (left) and back wall (right)

7.3.5

Activity Variables

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The type of the curricular task, the time of day of the curricular session, and unexpected interruptions during sessions have been identified as potentially intervening variables.

Task Although the predefined schedules for each learning space indicated what curricular topic would be addressed in each session, the pre-study had shown that actual activities could deviate from the schedule. By observing the learning sessions and consulting the time-lapse video recordings, three types of focussed-learning activities were distinguished:

Data Collection, Analysis, Results and Conclusion

•

Book tasks: pupils were engaged in paper-based learning exercises related to language or mathematics. Pupils were working alone or in small groups of up to four pupils. This was the most common type of activity.

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Science tasks: pupils were engaged in activities that required slightly more collaboration and communication in comparison to book activities. These sessions could be potentially louder due to the nature of the activity.

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Reading tasks: pupils were engaged in reading from a book or a computer screen. This is an individual activity, and potentially quieter than book work.

If none of these labels could be applied, the sessions were excluded from the studies. The labelling was used in the selection of comparable timeslots.

Time of Day The general mood of pupils in the mornings was excited and energetic, while the mood was less active and even disengaged during afternoons. This had been described by teachers during interviews. To track the differences in mood, these were marked during the observational studies and confirmed in short postsession interviews with teachers. However, the interpretation of these notes proved difficult to use in the analysis process. Therefore, a distinction was made instead between morning and afternoon sessions for comparison reasons.

Interruptions From observations no significant interruptions were perceived. Such interruptions could originate in the classroom or outside of it. The time-lapse videos were consulted for in-classroom disruptions in the non-observed sessions. None were detected.

Discussion

Of the fourteen identified potentially intervening variables described in section 5.4, only a smaller number has been playing a role in the data analysis from studies I and II. The indoor climate variable natural light was investigated extensively. Although some modest variations for its expression inside the four learning spaces did occur due to variable weather conditions, this only led to the exclusion of data from one afternoon in two spaces from certain comparisons.

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7.3.6

7.4

Study III: Cognitive Performance

This section describes the analysis and interpretation of the data collected during Study III, conducted during the Autumn semester, aimed to establish whether the experimental lighting influences the third outcome variable, pupil’s cognitive performance. The study took place in rooms L2.03 and L2.04, both on the second floor, and included four pupil groups: Bravo, Jupiter, Delta and Nordlys.

7.4.1

Data Collection

For five weeks, starting on Tuesday the 7th of November and finishing on Wednesday the 6th of December 2017, pupils seated at the same placement and room underwent two performance tests: •

Standard addition test—the pupils added two three-digit numbers (see for an example test Appendix T);

•

Figural creative thinking test—the pupils draw as many objects or pictures as they can envision using the lines and circles provided (see for an example test Appendix U).

The two tests were executed at the end of the second mathematics session, between 11:00 and 11:30, on Tuesday and Wednesday, and took place under the administration of their usual teacher, who would also ensure the pupils would be seated according to the predefined seating plan (see section 6.3.2). The researcher remained outside the rooms before and during the testing to avoid distracting or drawing attention. The four pupil groups used the same test material each week. The time allocated per test was 10 minutes, with a 10-minute break in between. The addition test was done first, followed by the creativity

Data Collection, Analysis, Results and Conclusion

Even though the composition of pupil groups remained constant, the number of pupils present in the central learning area during the tests did change. This became an additional assessment criterion for study I. Similarly, activity type has been a criterion in the assessment of data in study I.

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test after the break. Teachers were asked to stop the individual tests for the entire class if one student had finished all tasks within the 10 minutes. However, the number of tasks in each test was set to make it unlikely that the pupils were able to complete them all within the given time. These weekly tests took place under specific artificial lighting settings. For these a crossover research design was applied (see section 6.3.2). Table 7.4 shows the settings the four groups were exposed to during the five test weeks. Delta and Jupiter always underwent the tests in Room L2.03 while Bravo and Nordlys underwent the test in Room L2.04. Delta and Bravo underwent the tests on a Tuesday, while Jupiter and Nordlys underwent the tests on a Wednesday. Lighting settings (A) – standard, and lighting settings (B) – experimental (pools-of-light) were alternated per week, per learning space.

Data Collection, Analysis, Results and Conclusion

Table 7.4 Test schedule per room, per pupil group and lighting setting

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The first three weeks of study III were reserved to act as rehearsal weeks. During these weeks the teachers had been asked to instruct the pupils on how to perform the tests and provide their professional feedback to the researcher regarding any need for adjustment of, for example, each test’s format and difficulty. To keep the pupils blind to the experiment, the teachers were instructed to integrate the tests as a natural part of their lessons, for example, by referring to the tests as ‘exercises’. Based on the experiences from the rehearsal week, the teachers expressed no need for adjusting the tests. The teachers were then asked to execute the tests in the same manner and same time and day for the last two weeks of study III. See Figure 7.46 for an impression of pupils working on the addition test.

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At the end of each session the tests were collected by the teacher and handed over collectively to the researcher, who then split the tests between those made by pupils seated in the central area of the learning space, and those outside thereof. The first group of tests, those exposed to the experimental lighting, was further processed for analysis. The number of pupil tests further processed per group: Bravo: 13, Jupiter: 9, Delta: 8 and Nordlys: 11. Each pupil had been asked to note their name on the first page of the test. The researcher covered the name with black tape so that the tests would be blindly assessed. To ensure that those assessing the tests would not be biased, each test was also colour coded. This made it possible to, after assessing the tests, trace back which date, pupil group and learning space each originated from for comparison purposes.

7.4.1

Analysis

The premise is that pupils would score better on both tests whilst being exposed to the experimental, pools-of-light, condition (B) as this were found in study I and II to result in less (pupil activity) noise and distractive behaviours. Performance on the addition test was measured in terms of the number of correct answers versus the number of errors. For creative thinking tests, performance was measured in terms of fluency (number of interpretable pictures

Data Collection, Analysis, Results and Conclusion

Figure 7.46 Pupils working on the addition test in Room L2.03.

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created), flexibility (number of different categories) and elaboration (number of details). As particularly assessment of the latter tests required experiences reviewers, all tests were evaluated and marked a score by two experienced researchers of Aarhus University, who had been responsible for the analysis of similar tests in previous studies (Petersen, 2016). After these assessments, the test results were related back again to the respective session and lighting settings they originated from. Only within-subject comparisons were made between the two test results (from week 4 and 5) in order to eliminate any bias due to individual diﬀerences in the ability to perform schoolwork. Consequently, incomplete pairs of test responses, for example when a pupil did not conduct a test in both conditions during the intervention, were discarded.

Statistical Analysis Data Collection, Analysis, Results and Conclusion

A statistical analysis was then conducted to quantify the statistical significance of the data. First, a Shapiro–Wilk’s test with a P-value criterion of >0.05 was used to determine whether the residuals in the two lighting conditions were normally distributed. If the residuals in both conditions were normally distributed, then a paired t-test was applied to investigate whether the differences between data in the two lighting conditions were statistically significant. If the residuals in at least one of the conditions were not normally distributed, the data were considered non-parametric and a Wilcoxon signed-rank test was applied to investigate the statistical significance of the differences between data in the lighting conditions. Because an improvement in performance due to exposure to a pools-of-light pattern was expected, the P-values for the number of correct answers are one-tailed tests. The accepted level of confidence in statistical tests conducted was P < 0.05. These statistical analyses were done by the researchers from Aarhus University as well. For further details refer to rapport: van Mil, 2018.

7.4.2

Results

Standard Addition Test The outcomes of the statistical analysis of the addition tests are shown per pupil group in Figures 7.47 – 7.50. The vertical axis shows the number of correct additions pupils made per test, while the horizontal axis indicates the two test weeks (4 and 5) and respective lighting situation (A or B) activated during each week. For example, Figure 7.47 indicates that the number of correct additions made by Bravo pupils in Room L02.03 ranged between circa 31 and 63 with an average of 46,0 when exposed to lighting situation A. While the number of correct additions made by the same Bravo pupils ranged between circa 35 and 70 with an average of 51,9 when

Figure 7.47 Addition Test Results: L02.03 – Bravo (13) Correct answers: (A) 46,0 versus (B) 51,9. Rel.diff: +5,9%.

Figure 7.48 Addition Test Results: L02.03 – Jupiter (9) Correct answers: (A) 62,0 versus (B) 63,4. Rel.diff: +2,0%.

Figure 7.49 Addition Test Results: L02.04 – Delta (8) Correct answers: (B) 44,6 versus (A) 40,5. Rel.diff: -4,1%.

Figure 7.50 Addition Test Results: L02.04 – Nordlys (11) Correct answers: (B) 22,3 versus (A) 16,6. Rel.diff: -5,7%.

The overall finding is that pupil’s addition performance in all classes seems to be improved while exposed to the experimental situation (B) – pools-of-light compared to the standard situation (A) – ceiling tiles. The improvements expressed in percentage ranged between +2,0% to +5,9%. However, these percentages are based on only very small absolute differences in the number of wrong answers, and none of the differences are statistically significant. Hereto, the results only indicate a statistical tendency for the data to go in this direction of pupil performance improvement. Meaning, the differences found could to some extend still be due to change or other factors (see section 7.7), and not (solely) due to the lighting intervention.

Data Collection, Analysis, Results and Conclusion

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exposed to lighting situation B. The relative difference in addition performance is +5.9% in favour of Situation B. More statistical details are provided in Appendix V.

Figural Creative Thinking Test

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The outcomes of the statistical analysis of the creativity tests are shown per pupil group in Figures 7.51 – 7.54. The vertical axis shows the total score pupils drawn pictures received per test, while the horizontal axis indicates the two test weeks (4 and 5) and respective lighting situation (A or B) activated during each week. For example, Figure 7.51 indicates that the drawing score by the Bravo pupils in Room L02.03 ranged between circa 43 and 81 with an average of 58,8 when exposed to lighting situation A. While the drawing score by the same Bravo pupils ranged between circa 38 and 82 with an average of 61,8 when exposed to lighting situation B. The relative difference in creativity performance is +3.0% in favour of Situation B. More statistical details are provided in Appendix W.

Data Collection, Analysis, Results and Conclusion

Figure 7.51 Creativity Test Results: L02.03 – Bravo (13) Correct answers: (A) 58,8 versus (B) 61,8. Rel.diff: +3,0%.

Figure 7.52 Creativity Test Results: L02.03 – Jupiter (9) Correct answers: (A) 39,2 versus (B) 60,1. Rel.diff: +20,9%.

Figure 7.53 Creativity Test Results: L02.04 – Delta (8) Correct answers: (B) 30,9 versus (A) 39,3. Rel.diff: +8,4%.

Figure 7.54 Creativity Test Results: L02.04 – Nordlys (11) Correct answers: (B) 48,3 versus (A) 60,3. Rel.diff: +12,0%.

The overall finding is that pupil’s creativity performance in all classes seems to be improved in second week of the intervention (week 5), i.e. not following the changing of lighting condition.

Discussion

The results form Study III indicate for a potential positive impact of the experimental pattern, pools-of-light, in learning spaces on pupil’s performance, particularly during a focused learning task such as mathematical exercises. However, none of the correct answer differences were found statistically significant. The results from the creativity tests do not suggest for a relationship to exist between the lighting situation and creativity performance. These mainly suggest pupils get better at doing these exercises when practising more often. Overall, both test results are only suggestive and more alike studies are needed to fully understand the potential mechanism that may lie underneath.

7.5

Indoor Climate Variables Studies

In order to evaluate artificial light’s potential impact on pupil performance on the exercise tests, other variables that may have been of influence are to be ruled out. These potentially intervening variables are discussed in section 5.4. During study I and II (Spring experiment) some of these variables were possible to omit, while others were monitored. For Study III the same variables were considered of relevance: •

Architectural variables: spatial geometry (1), floor layout (2), and window design (3);

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Interior variables: furniture (4) and decorations (5);

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Indoor climate variables: (natural) light (6), sound (7), temperature (8), and air quality (9);

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Subject variables: pupils (10) and teachers (11);

•

Activity variables: curricular task (12), timeslot (13), and unexpected interruptions (14).

Most of these variables however could be excluded as intervening based on findings and learnings from the preceding Spring studies, while a few were still monitored. The architectural variables (1 – 3) could be excluded as these characteristics were already considered sufficiently comparable during Study I + II. As study III took place in two of these four learning spaces, the same conclusion applied.

Data Collection, Analysis, Results and Conclusion

7.4.3

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For all classes, except Bravo, the difference in scoring is statistically significant. This could indicate that a certain learning effect was in progress during the intervention, for example that the pupils got better at doing the drawing exercises due to repeated training. It could also indicate that the lighting condition is important. However, this cannot be ascribed to one certain condition, and further testing would be necessary.

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The expressions of the interior variables (4 – 5) were, like in Study I + II, agreed upon with the teachers beforehand, and monitored for change on the test-days of the study. Most importantly, the setup of the seat and desk furniture in both rooms was checked upon and corrected if needed prior to each test. This was done during the first formal break (between 09:30 and 10:00) before the start of session 2. This made sure pupils participating in the test could be seated at exactly the same place during each test. See Figure 7.55 for the furniture setup in room L2.03 just before testing commencing.

Data Collection, Analysis, Results and Conclusion

Figure 7.55 Furniture setup in Room L2.03

Although the results of Study I and II indicated that the indoor climate variables (6 – 9) could be regarded as non-intervening and predominantly stable in and between the learning spaces, it was yet decided to monitor their expression during the four test days in study III in case their expression would behave differently during the Autumn period. Temperature and air quality were measured with the same sensors as before. Each room was fitted out with one Tinytag sensor, logging temperature every minute, and one CO2 sensor per room logging the CO2 concentration in one-minute intervals (see for technical details, section 7.3.2). The Tinytag sensor was placed at desk height towards the back of the room as shown in Figure 7.56, while the CO2 sensor was placed at floor level, as shown in figure 7.57, to make it less visible for the pupils. The light conditions were monitored by four light loggers (HOBO UX90-001, see section 7.3.2) per room measuring light intensity (lux levels). One logger (A) was placed in the windowsill, to monitor the outdoor conditions, while the other three (B, C and D) were placed at desk height, on different working areas to monitor the indoor conditions. See Figures 7.58 – 7.61 for placement of the four recorders in room L2.03.

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The weather condition, affecting the natural light indoors, was also observed by the researcher just before and after the test. In addition, weather records for central Aarhus were consulted from the archive of the Danish Meteorological Institute (DMI) similar as during the Spring experiment.

For an overview of indicative locations of the sensor and recorders monitoring the different indoor climate variables in room L2.03 an L2.04 during Study III, see Figure 7.62.

Figure 7.56 Tinytag sensor: logging temperature and air humidity (as set up in room L02.03)

Figure 7.57 CO2 sensor: logging CO2 (as set up in room L02.03)

Data Collection, Analysis, Results and Conclusion

The sound level in the learning spaces was not measured during the testing, but the experience thereof in general, and that of unwanted sounds specifically (or noise), was monitored for significant change or unexpected occurrences by the researcher outside the learning spaces. As the performance tests were considered highly focussedlearning exercises, it was also anticipated pupils would be paying full attention to their task. Hereto (pupil activity) sound levels were anticipated to be relatively low and considered non-disturbing during the tests.

p. 240 Figure 7.58 Light sensor A: windowsill (room L02.03)

Data Collection, Analysis, Results and Conclusion

Figure 7.59 Light sensor B: desk surface (room L02.03)

Figure 7.60 Light sensor C: desk surface (room L02.03)

Figure 7.61 Light sensor D: desk surface (room L02.03)

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B B

Figure 7.62 Indoor Climate Sensor overview – Room L2.03 and L2.04

The subject variables (10 – 11) were also monitored during the test session. The pupils partaking in the tests themselves were monitored through name tagging on the tests. Test results from pupils who had not performed the test during both light situations were excluded from the analysis. The teacher present was monitored during the test to make sure the same teachers would be present during both tastings per pupil group. Of the activity variables (12 – 14) only unexpected interruptions were monitored by the researcher residing outside the two learning spaces while pupils were conducting the tests. Timing and task were both predefined variables that could not change.

7.5.1

Analysis

All measuring equipment to record the light level, temperature and CO2 concentration in both rooms was placed and activated before the tests, between 10:00 and 10:30 and deactivated and removed after the tests, between 11:30 and 12.00 in the two learning spaces. The data used for analysis was corresponding to the 30-minute test timeslot between 11:00 – 11:30. For each data log the mean, min and max values of these three variables were calculated. For the light level recorders, only the data recorded by loggers B and C was used for analysis. Data from both loggers A indicated erratic values, suggesting either their data got corrupted or errors were made during measuring. Hereto it was decided to discard this data and instead consult the weather data for an understanding of the outdoor lighting conditions. The data from loggers D showed many variations, suggesting the sensor may be been covered up partly during the tests. It is believed the pupils seated at this table may

Data Collection, Analysis, Results and Conclusion

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have folded their test papers over the sensors occasionally. This data stream was therefore also discarded from further analysis. The researchers’ notes were also reviewed for indications about the prevailing weather condition as well as any out-of-ordinary sound observations during the test timeslots.

Table 7.5 Room L2.03 – Indoor climate data

Pupil group Logger

Bravo Standard situation A

Jupiter

Experimental Situation B

Standard situation A

Experimental Situation B

Average (min, max)

127 (97, 151)

799 (162, 850)

172 (65, 194)

723 (65, 829)

164 (140, 172)

521 (452, 560)

169 (22, 193)

647 (43, 807)

Temperature

CO2

1024 (965, 1094)

987 (918, 1059)

899 (788, 1012)

988 (918, 1094)

Light

Data Collection, Analysis, Results and Conclusion

Table 7.6 Room L2.04 – Indoor climate data

Pupil group Logger

Delta Standard situation A

Nordlys

Experimental Situation B

Standard situation A

Experimental Situation B

Average (min, max)

255 (172, 280)

838 (743, 926)

355 (86, 549)

175 (162, 194)

589 (527, 635)

299 (75, 344)

Temperature

24.2 (23.9; 24.5)

23.4 (22.3; 24.3)

CO2

1034 (1000, 1118)

978 (918, 1047)

1005 (812, 1029)

Light

7.5.2

Results

The mean, min and max values for the light level (loggers B and C), room temperature and CO2 concentration during the test timeslots are shown in Table 7.5 for room L2.03 and Table 7.6 for room L2.04. Some of the data was corrupted and could be not used for analysis. The respective data boxes are left blank.

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The light logger results indicate that the average light level on the working surfaces was significantly higher while the experimental situation B with the pendants was active in both rooms, and for all four pupil groups. And secondly, the light levels measured during situation A are relatively comparable, between both rooms and testing days as well as those values measured under situation B. The indoor temperature measurements were corrupted in most cases. Though those available are of the same magnitude as measured during the spring experiment. Hereto it is considered likely that temperature had remained relatively stable and within normal comfort limits during the four test days. The concentration of CO2 remained relatively stable and within comfort ranges as well.

The notes on the weather conditions during testing can be described with the following key words: Tuesday 28th of November

clouded sky

Wednesday 29th of November

semi-clouded sky

Tuesday 5th of December

clouded sky

Wednesday 6th of December

very overcast sky

Week 1

Week 2

Historic weather records were also consulted from the archive of the Danish Meteorological Institute (DMI) for central Aarhus. These provided the number of sun-minutes per hour. See Figure 7.63 for the graphs of the four test days. The column representing 11:00 is highlighted, corresponding with the 30-minutes of testing.

Figure 7.63 Weather data during the four testing days

Data Collection, Analysis, Results and Conclusion

The sound notes did not present any abnormalities occurred during the testing timeslots. Herewith it is assumed the sound levels remained relatively stable and within normal ranges.

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These records suggest that test 1, 3 and 4 featured comparable weather conditions (< 2 min of sun – these weather conditions may be considered significantly overcast), while the learning spaces during test 2 most likely featured a higher proportion of natural light (circa 22 min of sun). However, the light logger data does not suggest significantly higher light levels were measured indoors. Therefore, the indoor lighting conditions are considered sufficiently alike for test data to be compared from all four test days.

7.5.3

Discussion

Data Collection, Analysis, Results and Conclusion

In general, the measurements of the environmental parameters, CO2, temperature, and light level show stable and comparable conditions between the two learning spaces and four test sessions. The weather conditions were also found comparable to allow all test data to be compared amongst. The interior, subject and activity variables also did not significantly change either. Therefore, these identified intervening variables do not appear to have influenced the results of the cognitive performance tests.

7.6

Summary

This chapter described the collection, analysis and interpretation of all data gathered as part of Studies I, II and III. These studies investigate the effect of non-uniform pools-of-light pattern on pupils’ behaviour and learning performance. Each study investigates an outcome variable related hereto: (I) noise during class, (II) disruptive pupil behaviour, and (III) cognitive performance.

7.6.1

Study I – Noise during Class

Study I was based on the premise that noise levels during focussedlearning activities are lower when pupils express less(er) disruptive behaviours – as pupils are found the main cause of noise in class. Less noise hereto implies that pupils are working in a higher state of concentration. Less noise also equals better aural conditions, or a better-quality learning environment, as set out in the goals of the 2014 Folkeskole reform. For this reason, sound levels were recorded during focussed-learning activities while the pupils were exposed to either the standard (A) or experimental (B) lighting situations. The data was subsequently analysed in order to arrive at a number of cases where differences in the recorded sound level during class could be attributed to differences in artificial lighting. A number of procedures were undertaken that led to 20 of such comparison cases. Initially, with the help of time-lapse video recordings, 38 timeslots were identified during which pupils were engaged in specific activities that could be classified as focussedlearning. For these timeslots the equivalent continuous sound level

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(LAeq) was calculated, and a time-history plot was produced to assess how the sound had changed over time. These timeslots were than assessed based on intervening variables that could not be neutralized in the setup of the experiment, notably changes in natural light, number of pupils present in the learning space’s central area, and type of focussed-learning activity. This led towards exclusion of data from two timeslots only. In 70% of the comparison cases the experimental lighting situation (B)—with pendants producing pools-of-light—showed a perceptibly significant reduction in sound levels. Following the premise of this study, this reduction in noise suggests less disruptive behaviours occurred in those cases, and pupils may have been working in a higher state of concentration. More directly, the reduced sound levels contribute to perceptibly improved aural conditions, or a better learning environment, as set out in the goals of the reform.

Study II – Disruptive Pupil Behaviour

Study II was based on the premise that when pupils display less disruptive behaviours, they are more engaged with their learning – alias working in a higher state of concentration – and hereto less disturbing to their own and others learning. A reduction in disruptions also equals a better learning environment as set out in the goals of the 2014 Folkeskole reform. This study looked for observable changes in three typical disruptive pupil behaviours: expressive, social and physical behaviours (see section 5.3.2) during focussed-learning activities. These three behaviours are considered disruptive to one’s own or others concentration on their learning. The occurrences of these three disruptive pupil behaviours were observed while the pupils were exposed to the standard (A) or experimental (B) lighting situations. In addition, teachers were asked to respond to those observations, and were interviewed about their own observations. In some cases, pupils were also interviewed about their experiences with the experimental lighting situation. The subsequent qualitative data set was analysed following the method of thematic analysis. This resulted in five themes that each represent an important finding from the data set: attraction, locality, calming, stationary, and variation. The general consensus amongst these themes is that the experimental lighting situation (B)—with pendants producing pools-of-light—showed to have had a positive effect on the occurrence and display of the three types of disruptive behaviours identified. The experimental lighting system in general was believed to heightening pupil’s comfort in the learning space and add to a feeling of safety when activated. When the pendants are activated (situation B), the subsequent brighter pools-of-light appeared to

Data Collection, Analysis, Results and Conclusion

7.6.2

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attract pupils towards these, while this lighting situation (B) at the same time acknowledges pupil’s individual light preferences by offering different luminous micro-environments including more subdued areas. The pendant lighting situation (B) was also believed to have a relatively calming effect on pupils, particularly those pupils prone to display disturbing behaviour, and to discourage pupils to move around without a learning-related purpose. Pupils were believed to stay seated longer, though quantitative evidence thereof was not collected to endorse. In addition, the experimental lighting system, which allows both lighting situation (A) and (B) to appear on demand, offered teachers a way to harmonize the learning space’s appearance, or atmosphere, with pupil’s mood, or to direct pupil’s mood and attention to match with the activity at hand. Often such alignment took place for focussed-learning activities, but teachers changed between settings to a lesser degree during other activities too.

Data Collection, Analysis, Results and Conclusion

These observed behavioural changes with the experimental lighting scenario (B) in place appear to be instigated by two characteristics of the pendants part of this scenario. Firstly, the pendants’ physical identity seems to be a familiar and recognizable object that most pupils (and teachers) knew from their homes. Pendants appeared to be associated with certain form of usage, being positioned above a table (working) surface, and related to a rather cosy atmosphere. Because of such familiarity, simply their physical presence evoked some of the changes observed. Secondly, the pools-of-light that emerge when the pendants are activated appear to attract most pupils intuitively towards them, to sit within and create for a local feeling of intimacy. It appeared pupils interacted more amongst their local peers instead with others seated at other tables or places. They also seemed to remain seated for longer and be less fidgety. Following the premise for this study, the noticeable behavioural changes this study found when the pendants were activated during focussed-learning activities suggests that pupils were more drawn towards the learning task and may have been working in a higher state of concentration. In addition, less occurrences of distractions also suggest a more comfortable learning environment.

7.6.3

Study III – Cognitive Performance

Study III was based on the premise that less disruptions during class would show in improved cognitive performance. The improvement could be directly related to the change in the artificial light pattern, as well as the previously established decrease in noise during class, lesser occurrences of disruptive behaviours and pupils feeling more at ease in their respective learning environments. Hereto pupils were repeatedly subjected to two kinds of exercise tests, namely a specialized math test and a creativity test, while exposed to either the standard (A) or experimental (B) lighting settings. The data collected was sorted and subjected to statistical

7.6.4

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analysis. The subsequent findings hint at a potential positive impact of the experimental pattern (B), pools-of-light, in learning spaces on pupil’s performance on a focused learning task such as a mathematical exercise like additions. However, the findings are only suggestive and further studies are needed to fully understand the potential mechanism that may lie underneath.

Intervening Variables

7.7

Conclusion

Central to this research is the quest to create learning environments that are supportive of pupils' learning performance. It specifically addresses the need to improve quietness during class as called for by the 2014 Folkeskole reform. A quieter environment can be achieved by reducing disturbances, which are found to be predominantly caused by pupils themselves. In this research it is hypothesised that the artificial lighting in the learning space, besides providing for good visibility during all hours of use, can also act as a tool to discourage disturbing behaviours, and herewith reduce the occurrence and/or impact thereof. The questions this research looks to address is hereto formulated as: Does exposure to the pools-of-light pattern in the Folkeskole learning environment discourage disturbing pupil behaviours and herewith improve quietness during class? And if so, does this change significantly affect pupil’s learning performance? Jointly, the findings from studies (I), (II) and (III), supported by the overarching intervening variables studies, suggest that the experimental lighting pattern, pools-of-light, lowers classroom noise levels during focussed-learning activities, and reduces the occurrences and impact of three type of disruptive pupil behaviours – herewith improving quietness during class. The results also hint at that these changes may lead to improved cognitive performance. Jointly these findings seem to suggest that the experimental lighting settings (B) may positively contribute towards creating a better learning environment as advocated by 2014 Folkeskole reform.

Data Collection, Analysis, Results and Conclusion

During the three studies (I), (II) and (III) a broad range of potentially intervening variables, that could not be eliminated in the setup of the experiment, were monitored for significant change too. Those with notable changes were found to be the natural light (or weather) conditions, the number of pupils present in the learning space’s central area, and type of focussed-learning activity. These required two data sets to be excluded from further analysis in Study I. Otherwise, the remaining variables could be eliminated as intervening with the data collected during the three studies.

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An important observation amidst these studies is that natural light’s presence inside the learning spaces, even when relatively small from a quantitative perspective, influences the expression of the light pattern and herewith the occupant’s overall visual impression of their environment. The presence of artificial and natural lighting is (during daytime hours) irrevocably linked, and one cannot be considered without the other. Hereto further studies are necessary to establish the relationship between the artificial light pattern and pupil’s learning outcomes, while accounting for natural light’s presence. Suggestions for such future research are provided in the next, and final Chapter. The chapter will also discuss other learnings from the field experiment that not directly answer to the research question as stated above, but are of value to the academic and practice fields this research is associated with.

Data Collection, Analysis, Results and Conclusion

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Discussion

How the findings from the field experiment’s data set serve to answer the research questions has been outlined in the previous chapter. This final chapter discusses findings from (performing) the field experiment in a broader perspective. Section 8.1 describes five other take-aways from the field experiment itself, or the data set derived from it, that are related to the academic and practice fields this research seeks to contribute to. Section 8.2 elaborates on the field experiment’s validity, reliability, replicability, and generalizability, while section 8.3 concludes the chapter with three key suggestions for future research.

8.1

Research Contributions

As outlined in section 1.3, this research looks to add new knowledge to the academic fields of environmental psychology and lighting science about how the built environment, and light in particular, influences occupant behaviour. It also looks to showcase an exemplary design of how artificial lighting may become a tool for teachers to encourage certain behavioural change in their pupils, to provide specific design information for the architectural industry, and to contribute to the broader debate about improving the indoor quality of learning environments in general. the following five subsections outline how different findings and learnings from the field experiment contribute hereto.

8.1.1

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DISCUSSION

Artificial and Natural Light, a Joint Condition

In the four learning spaces hosting the field experiment, and commonly for most of today’s learning environments, natural light is present during curricular hours. Its manifestation in the learning space however depends on the time of day, weather conditions and window blind settings, and has been diligently studied both quantitively and qualitatively throughout the experiment. Without artificial lighting activated, it would be the only source of light and herewith fully define the occupant’s visual impression of their learning space. Though, the experiment in Frederiksbjerg school indicated that naturally lit learning spaces were only found to occur sporadically during curricular hours, and predominantly on sunny days. Most often artificial lighting was activated when the learning spaces hosting the experiment were in use. Regardless of the artificial lighting being the standard (A) setting or the experimental (B) settings (see Figure 8.1), in both situations natural light was found to only play a minor role in defining the occupant’s visual impression of the learning space with the artificial light dominating the visual scene. Hereto changing between light setting (A) and (B) was considered to have a profound visual effect to the occupants.

Discussion

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Nevertheless, artificial and natural light are (during daytime hours) irrevocably linked and to be mediated between. It appeared for example, that the natural light conditions in a learning space would inform how occupants would operate the artificial lighting. If artificial light setting (B), which includes the pendants, was accessible on a sunny day, often only the pendants would be activated without the supplementary ceiling tiles. Whereas on poor daylight (overcast) days, the same pendants would be activated but now together with the ceiling tiles. This finding suggests that even tough natural light may be visually less informative, it still plays a significant role in deciding which artificial light setting is activated. At the same time, when questioning teachers about the qualities of the lighting condition in their learning spaces, almost all answered their ideal light source to be the natural light. Their preference went out to harvest and utilize the natural light as much as possible, for example by placing tables near to windows and keeping blinds open as much as possible. Though occasionally practicalities as glare and heating required them to limit or prevent natural light to enter.

Discussion

These findings jointly suggest that isolating the artificial light component as defining the occupant’s visual impression of a space is invalid. Natural light plays a significant role in how the occupant treats the artificial lighting, and therefore should be informing the artificial lighting design for learning environments. However, treating artificial lighting solely as a complementary source to boost the light levels in the learning space when natural light is lacking (as what most architects typically consider the artificial lighting’s role to be in the learning space according to the interviews) does not do justice to its opportunities either. This research shows that artificial lighting’s role may be considered more broadly, for example a tool for teachers to manage their learning spaces. Yet, design of artificial and natural light is to be viewed jointly.

Figure 8.1 Available artificial light scenarios for Lighting Setting A (Standard) and Setting B (Experimental)

(A0) no lighting

(A1) ceiling lighting

(B0) no lighting

(B1) ceiling lighting

(B2) ceiling + pedants

(B3) pendants only

Variable Lighting Conditions

This study focussed on investigating the effect of the experimental settings (B), which includes the pendants, on pupil’s behaviour and learning performance relative to control setting (A) during focussedlearning activities. This type of activities typically took place in the central working area of the learning space, though the adjoining group room and podium area may be included: Often seating positions per pupil were predefined for these activities (Figure 8.2).

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8.1.2

learning spaces group room central working area

Figure 8.2 Typical learning space layout with three zones: separate group room,

centeral working area and podium (group instruction) area.

These focussed-learning activities however only took place during certain time intervals. During the remainder of a curricular day pupils engaged in various other types of activities. Although these are not the specific interest for this study, these activities were often observed and measured as well during the data collection as no precise distinction of the focussed-learning activities timeslots could be anticipated beforehand. These out-of-scope observations revealed two types of other typical activities that are alternated with the focussed-learning activities. These can be roughly categorized as: tutoring activities and free play activities. •

Tutoring activities take place most often in the instruction area of the respective learning space (see Figure 8.2), where pupils would all gather together seated on the podium while the teacher would lecture the entire group about a topic or following exercise or activity, or summarize the activity just undertaken. Typically, these tutoring activities would be 1o- to 15-minute long and take place both at the beginning and end of a 90-minute curricular session. Pupils would remain seated in their choosen place at or around the podium and pay attention to their teacher in front.

Discussion

podium area

•

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Free play activities were found to take place anywhere in the learning space as well as outside with no pre-defined seating positions in place. It includes activities pupils undertake when they have finished their ‘official’ curricular work for that session. These may concern individual, social or artistic activities that allow for free talking and interaction. On the first floor, where the youngest pupils reside, free activities ranging between 15 to 45 minutes, are regularly scheduled because alternation between work and play time is required due to these pupil’s limited attention span. On the second floor, hosting the older pupil groups, free time is generally scheduled around the middle of a curricular session and lasts about 10 minutes. At both levels significant amount of movement, socializing and other playful interactions in- and outside the learning spaces took place.

The observations and interviews performed during the experiment revealed these three activity types are typically complemented by specific artificial lighting settings. During focussed-learning activities the ceiling tiles were almost always activated in learning spaces setup with lighting setting (A). Reasons therefor appear to, firstly, ensure good visibility for all, and secondly, to sustain pupils actively working on their task. However, when the experimental setting (B) was accessible, the pendants were almost always activated – and only at certain times supported by the ceiling tiles activated. In principle it was found that teachers preferred to only use the pendants during these activities as this would create the most evident intimate and focused room impression. However, in some circumstances the teacher would activate the ceiling tiles (completely or at a dimmed level) for example, when they noticed a few pupils working in relative “darkness” (when not enough seats at the pendant tables were available) or when natural lights’ presence was limited.

•

During tutoring activities either no artificial lighting would be activated – the teacher and pupils would rely on natural light to illuminate their space (particularly when the smartboard is in use), or only the ceiling tiles would be activated. This was also the case during the observed experimental (B) sessions where pendant lighting was available. It appears to be preferred to only have gentle, uniform background lighting present and avoid any visual distractions for the pupils that may draw their attention away from the teacher and smartboard.

•

During free play activities the ceiling tiles would be almost always activated; both during sessions with and without the pendants available. These activities generally don’t require traditional learning behaviour such as concentration, but rather benefit from an environment that allows for social

Discussion

•

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interactions, creativity, and physical activities to unfold. Occasionally, tables and seating would be moved aside to open up a greater play area to emerge. This situation would render the pendants unusable, or even a physical hindrance when suspended too low and pupils or the teacher could bump against. In an ideal situation, the pendants could be either removed or put up to the ceiling to prevent such hinderance.

It is thus not advocated that a non-uniform pools-of-light pattern is better or worse than a uniform pattern in absolute sense, but merely that alternation between these settings would accrue most overall user satisfaction, and possibly performance outcomes as one can select the most appropriate settings per curricular situation. Such adaptability of the lighting also supports teachers to deal with the diversification of curricular activities brought about by the 2014 Folkeskole reform.

Human Centred Lighting Another form of variable lighting that is often explored jointly by the lighting and luminaire design industry and the academic community is often labelled human-centric lighting, a form of dynamic lighting. This term typically refers to lighting systems that are pre-set with multiple different settings, often different combinations of illuminance and colour temperature values, between which the occupant can alternate (see section 3.3.4). These settings generally create uniform light patterns, of which the apparent brightness and colour appearances may be varied. These studies too found positive changes in pupil’s performance because of access to these different settings, and to limited degree uncovered some underlaying behavioural change(s) responsible thereof. Most notable findings are that combinations of relatively high light intensities and colour temperature helped pupils to focus on their learning, while combinations of relatively low intensities and colour temperatures were found to have a rather calming effect on pupils (see section 3.2.3). To a degree these findings may contribute to explain why the pools light pattern appeared favourable for focussed-learning activities as the measured lux levels on pupils’ working desk were higher when the pendants were activated (circa 500 – 600 lux, setting B) then under fully activated ceiling tiles (circa 300 – 500 lux, setting B). However, these intensity

Discussion

These findings suggest the pools-of-light pattern (B) is valued most during focussed-learning activities demanding pupil concentration. While for other activities, roughly categorized in tutoring and free play activities, preference appears to go out to the standard uniform pattern, or no artificial lighting at all. This suggests a lighting system that allows for a degree of variability, provides occupants the opportunity to change between and select their preferred lighting setting according to the needs of the task or activity at hand.

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differences are not significant enough to explain the overall effect. But what can be learned from these studies and the study presented in this thesis is that a lighting system that allows occupants to vary the lighting expression in their respective learning space, either by varying light intensity, colour or pattern benefits pupils learning.

8.1.3

Tool to Influence Pupil Behaviour

Discussion

This research also explores how artificial lighting in the learning environment may, besides making things visible, also act as a tool for teachers to either encourage or discourage certain pupil behaviours. As outlined in the preceding section, a lighting system as for example used in the field experiment allows occupants to select from a range of lighting conditions, or light patterns. The non-uniform pools-of-light pattern was found to discourage certain disruptive behaviours and improve pupils’ attention to their task. While the uniform light pattern was found to better support group tutoring and free play activities – which either thrive on joint attention towards the teacher or a collaborative and social state of mind. Both situations steer away from the individual pupil and towards the group as a whole, or multiple smaller grouped teams, instead. These associations appeared true for all six teachers involved in the experiment. Matching the right lighting condition with the curricular activity at hand seems to encourage pupil behaviour in favourable ways. The beforementioned associations between a certain light pattern and type of activity naturally formed while the teachers and pupils were experimenting with the new lighting system. They were not given any prescriptions of how to use the lighting system other than an introduction to its controls. During a post-experiment briefing these findings were presented to the entire teaching team of Frederiksbjerg School, the host of the field experiment. Their feedback suggests that most teachers believed these associations to be true, without having used the lighting system themselves. This may imply that intuitively different light settings were associated with different types of curricular activities and pupil behaviours. This may suggest other teachers, confronted with a similar lighting system, may use the lighting in a similar way.

Simple User Control One important feature of the experimental lighting setup was its relatively simple controls. Double, wall mounted switches of a similar type and in same locations as in the pre-experiment situation were used. This allowed the teachers (and pupils) to start using the system instantly without an extensive learning curve, and make a changes to the lighting system relatively easy. This may explain why the artificial lighting system was used extensively and intuitively – as no prescriptions were provided how to use other than a brief introduction to the wall switches.

8.1.4

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A second important feature of the lighting system was the use of pendants. These, as objects, are both well visible – ensuring the occupants would not forget about them after the novelty of the new lighting would wear off, and recognizable – most Danes would be familiar with a pendant and its function. From these findings it may be understood that for a (lighting) system implemented in learning spaces simplicity is key in order to capacitate teachers to use it well.

Permanently Installed and Expanded Design

Discussion

An explicit and practical outcome of the field experiment was that instead of remodelling the four host learning spaces back to their original form as agreed on with the school beforehand, the teachers and school management requested for the experimental lighting systems to be installed permanently in the four learning spaces. See Figures 8.3 – 8.5 two of the learning spaces with the now permanently installed lighting systems.

Figures 8.3 – 8.5 Permanent installation of the experimental lighting in two of the four host learning spaces

And secondly, the school instructed Henning Larsen to roll out the lighting concept to other, relevant areas within the school building. Hereto a spin-off design exercise was undertaken, which lead to extensive application of pendants in both formal and informal learning spaces and places throughout the school building. See for examples hereof Figures 8.6 – 8.8. Permanent installation of the experimental lighting system also allowed to revisit the school six month and one year later, and conduct follow-up interviews with the six teachers who initially participated about their experiences with the lighting over a longer period of time, and during all four seasons of the year. It appeared the pendant lighting had quickly become the new normal and teachers and pupils both would use it extensively. The same way-ofuse still applied; active pendants during seated, focussed activities

p. 258 Figures 8.6 – 8.8 Applications of additional pendant lighting in certain informal learning areas in Frederiksbjerg Skole

both with and without the ceiling tiles to complement, and active ceiling tiles for group and tutoring activities. The pendants were however said to be used less during summer months, as often preference would go out to reside in naturally illuminated spaces.

Discussion

Although during and directly after the experiment teachers had suggested for the pendants to be a potential hindrance when using the spaces for activities without furniture, in practice it hadn’t been perceived a significant issue. The few times a year this situation would arise, teachers would simply tie a knot in the suspension cords to that the pendants would be raised up. Also, none of the pendants, a year after being taken in use, had been damaged or vandalised. Maintenance personal briefly interviewed were surprised though confident in the robustness of the system. A downside however remained that these luminaires were added post-occupancy and therefore not fully integrated into the building management system (BMS). Hereto central control and automatic maintenance advice from these added luminaires was not feasible. In essence, the permanent placement of the pendant lighting system, and follow-up studies solidified the earlier findings from the experiment: a lighting system that allows the user to vary between different light patterns, including pools-of-light, is a valuable tool for teachers to nurture and encourage pupil’s different learning mind-states.

8.1.5

Design Approach and Recommendations

The practice-orientated aim for this study is to exemplify how artificial lighting may become a constructive design tool that architects can apply to create environments or spaces that allow their occupants to perform their task or activities to the best of their abilities. Herewith suggesting that artificial lighting may be considered an environmental quality that goes beyond ensuring for appropriate visibility only. The non-conventional experimental lighting system design that was installed in the learning spaces

However, interviews with several (educational) architects revealed that artificial lighting generally is not commonly considered a feature to contribute in other ways than providing for appropriate visibility as outlined by the respective building regulations. Generally, it is designed in such way it complements natural light (if present) while at the same time consume as little energy as possible. Typically, the topic of artificial lighting would only be actively discussed with the (electrical) engineer towards the later stages of the design to ensure the selected luminaires, which are commonly placed at or near the ceiling in learning environments, harmonize well with other ceiling-based services such as ventilation outlets, ductwork, fire and emergency systems, and IT related systems. Typically, not much attention appears to be given to the specific expression of space through the artificial lighting. In this regard, the process of developing the experimental lighting design as applied in the field experiment collaboratively with the teachers, school maintenance team and responsible architects has proven successful. For example, other schools took notice and initiated their own studies to explore how their facilities could benefit from more variable artificial lighting. While the broader architectural community was informed via publications in branch-related literature, which led towards various enquiries from other practices. The research may also point towards adaptation of the current regulations, which include predominantly recommendations to ensure for good visibility, for example to provide for a maintained illuminance level of 300 lux across the working surfaces combined with a relatively high degree of uniformity of 0.6 (as per EN 124641:2011). Such recommendations offer very little room nor motivation to aspire beyond a typical one-fits-all standardized artificial lighting design. But for both natural and artificial light, it is the architect’s responsibility to compose meaningful (which includes functional, aesthetic, healthy, economical, and sustainable) applications of light in coherence with each other, the users and their activities. The building regulations may need to allow for more scope to fulfil all of these needs.

8.2

Experimental Field Study

This section discusses the validity, reliability, repeatability and generalizability of the field experiment performed and the findings that were derived from it.

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hosting this research’ experiment was so well received by teachers, pupils and the school, that it was kept in place for permanent use. This outcome suggests that allowance for an artificial lighting system that can be varied indeed can be an active contributor to create better supportive environments. Although this research explored one particular variation only, namely the pools-of-light condition, different designs and outcomes may be thinkable.

8.2.1

Validity

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Research validity determines how true the results obtained through the data collection activities are. Or in other words, how well the results represent what is attempted to be studied. The aim for this field experiment was to investigate whether a specific artificial light pattern, namely pools-of-light, would affect pupils’ behaviour and learning performance. In order to measure change herein, three outcome variables have been appointed that could be either (positively or negatively) associated with behavioural and performance change: (1) noise during class, (2) observable disruptive behaviours, and (3) pupil’s cognitive performance. For each outcome variable a data collection protocol was set up, including various quantitative and qualitative methods, as well as corresponding data analysis procedures. The three subsequent data sets were analysed separately, and their results interpreted on their own account. Following, these results were reviewed jointly to reflect upon this research’ main question: Does exposure to the pools-of-light pattern in the Folkeskole learning environment discourage disturbing pupil behaviours and herewith improve quietness during class? And if so, does this change significantly affect pupils’ learning performance?

Discussion

This latter step allowed to arrive at the overall conclusion that the data sets tends to suggest that the pools-of-light pattern encouraged behavioural change in pupils that resulted in a calmer learning environment (less noisy) that benefits their concentration on the learning task and suggests a tendency for improved cognitive performance.

True Outcome Variables The three outcome variables used to assess behavioural and performance implications brought about by changes to the artificial lighting, were derived from preceding research that proved these variables to be measurable and relatable to pupil behaviour and/or performance. See section 2.4 and section 3.2. for reviews of the relevant research literature. These reviews revealed that outcome variable (2) disruptive pupil behaviour has been used by preceding researchers to successfully reflect upon changes in pupil behaviour due to certain environmental qualities, while outcome variable (3) pupil’s cognitive performance has been directly related to pupils’ ability to perform on academic tests. Though outcome variable (1) noise during class is a relatively unique outcome variable in the sense that in this field experiment noise, or sound levels, are not solely used to reveal differences between different environmental or contextual settings as preceding researchers done so far. But in this field experiment measured sound levels have also been interpretated as an indicator of change in pupil behaviour. The premise being that less noise (or

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lower sound levels) during class equals less pupil-made vocal and activity noise. This assumption suggests a link between sound levels and pupil behaviour, which has not yet been explored before (to this study author’s knowledge). To establish whether such relationship between noise and behaviour is a generally viable, further studies would be required.

Research validity also refers to how well the experiment’s treatment variable, in this research is the artificial light pattern, can be considered the sole cause for any documented change in the appointed outcome variables, in this research pupils’ behaviour and performance, versus other factors (or intervening variables) that may potentially affect the appointed outcome variables too. As this study was set up as an experiment in the field, or a real-life environment, it is impossible to control for all of these potentially intervening variables. But in order to limit data contamination as much as possible, the intent for this research has therefore been to, firstly, ensure potentially intervening variables remained constant and comparable amongst the four learning spaces during the experiment. For example, the three architectural variables identified as potentially intervening (see section 5.4.1) were eliminated by selecting four relatively comparable learning spaces concerning these three variables. Certain interior design features (see section 5.4.2) we’re monitored during the experiment for change, and if occurred, corrected back to the original setup to maintain consistency. Those identified variables that could not be omitted by means of comparability or consistency, were monitored for change during the experiment. The most challenging variable that had to be taken into account hereto was the natural lighting (or weather) condition. Luckily most of the critical days of the experiment were found to feature similar weather patterns (semi or overcast skies), limiting its interference with the data. Other indoor climate variables, including room temperature and air quality, were monitored too during the data collection activities. As were the number of pupils (section 5.4.4) and type of activities (section 5.4.5) ongoing as both were found to fluctuate significantly during the pilot studies. All data collected was taken into account during the data processing. The findings for these monitored intervening variables during the Spring Studies I and II and the autumn Study III, suggest these variables did not significantly change, or could be excluded from the data set. This strengthens the premise that the change in the artificial light pattern was the cause of change in pupil’s behaviour and performance. However, only a limited number of fourteen potentially intervening variables have been assessed or monitored during this experimental study. There is a possibility that other variable(s) not

Discussion

Intervening Variables

accounted for did play a role in the documented change in the outcome variables, pupil’s behaviour and performance. Hereto it may be concluded that significant effort has been made to exclude interference, however it cannot be ruled out completely. p. 262

The validity of the field experiment may therefore be considered reasonably strong, but it’s possible that the assumption that a link between the sound level during class and pupil behaviour exists is invalid, or that other variables not accounted for intervened.

8.2.2

Reliability

The reliability of a field experiment depends amongst others on the accuracy of the procedures and research techniques used to collect and analyse the data. This study revolved around uncovering whether pupil’s behaviour and performance would change by manipulating the artificial lighting in their learning spaces. The three outcome variables appointed to investigate if such change would occur, are: (1) noise during class, (2) observable disruptive behaviours, and (3) pupil’s cognitive performance. Different data collection techniques and analysis procedures were applied. The reliability of these processes is discussed next. Discussion

Preceding Research These three variables surfaced from the literature review and had been investigated successfully by others before. By taking inspiration from these studies to collect and analyse the respective data, a degree of reliability of these techniques and subsequent findings may be assumed. Noise and behaviour have been evaluated for perceptible differences as what matters in this research context is how the occupants themselves would experience a change, rather than statistical differences. Cognitive performance however was evaluated purely statically and considered to reflect a change in pupil’s concentration.

Respondents To increase reliability of findings further two pairs of learning spaces and ten groups of pupils were included in the study, increasing the pool of respondent in numbers as well as broadening their demographics. Also, the same six teachers, which each represented a stereotype of teacher (age, experience, gender) were consistently followed. This allows the findings of these studies to be relatively generalizable – at least for this school. This contextual setup also allowed to compare the collected data between the four learning spaces, and to estimate the consistency thereof. This was most evident for the sound data, which was found measured as relatively comparable ranges per room. But also, pupil behaviour was found comparable across the different rooms.

Research bias may also have played a role with the researcher herself (the author of this PhD), who acted both as the observer of pupils during class, and as the interviewer with the teachers. By being aware of the research question, and an inherent desire to uncover promising findings, qualitative research in form of observations and interviews may be prone to data collection and interpretation bias. In order to limit such bias, two steps had been taken. Firstly, the author teamed up with two ethnographic Master students (Applied Cultural Analysis, University of Copenhagen) to shadow their qualitative research work in school environments. Secondly, a consultation was held with an Associate Professor at DPU (Danmarks institute for pædagogik og uddannelse or Danish School of Education, Aarhus University) who has extensive experience in making classroom observations. Together my observation technique, focus and template were further refined. Both collaborations allowed to capacitate myself in acting as an objective observer and interviewer, as well as data interpreter.

8.2.3

Repeatability

A third aspect to evaluate the setup and procedure of the field experiment against is repeatability. Would the same results have appeared if the experiment had taken in place in other spaces of Frederiksbjerg Skole, or will the same results be repeated if the research is/was done at another time or different length of time? When designing the setup of this field experiment, significant attention was given to review all potential learning spaces within the school. Most of these appeared to be similar in their architectural detailing, materials and furnishings. Most evident differences are the window arrangement and orientation (defining

Discussion

Another element to consider is bias. The teachers were key participants in the experiment because they were predominantly setting the lighting conditions and managing pupil’s learning behaviour. While data collection partly relied on their own observations about the potential effect of the experimental lighting setup. To gain trust and willingness to participate, the teachers were well informed prior to the experiment about the purpose of the study. They were also consulted about the experimental lighting design proposal as it had to be used during their daily curricular schedule and was not allowed to form a disturbance to the normal ongoing of pupils learning. Hereto they might already have had a biased opinion about how the experimental lighting may bring about certain behaviours or changes in pupils and reflect these in their interviews. However, because the experimental lighting was kept in place, there was opportunity to revisit the same teachers after six and twelve months and re-interview them. By that time the new lighting had become the new normal, and herewith their initial bias may have been diminished.

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Research Bias

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the natural light’s presence in a space), and occupant type and room usage. As natural light has been found to influence the overall visual impression of the learning space, even tough to a minor degree relative to activated artificial lighting, it may have been valuable to execute the study in two pairs of spaces on the same floor (rendering occupant type and usage the same) with both different window orientations. This would allow to study natural light’s role herein instead of studying two different occupant types and room usages. It may be that natural light has a greater impact then this study evidenced. Whether the same results would also have emerged had the experiment taken place in another school is more problematic to judge as such a broad range of variables are at play – ranging from the architectural (and acoustic) context, to the demographics of the pupils, school culture, and importantly the teachers participating. However, the three studies that investigated the impact of dynamic lighting on primary school-aged pupil behaviour and performance (see section 3.3.4) each took place in different schools, and even countries. Nevertheless, these three studies exposed similar findings which suggests certain aspects of (artificial) lighting may stimulate certain behavioural responses that are not necessarily site or culture specific.

Discussion

8.2.4

Generalizability

The fourth aspect to assess this field experiment against is generalizability, which relates to how useful the study results are for a broader group of schools. The generalizability of this experimental study is limited because of the pupil groups studied, the type of curricular activities ongoing, and the specific lighting design applied.

Pupil Demographics This field study focused specifically on primary learning environments occupied by children aged between 6 and 12 years old. Is it not possible to speculate whether pupils aged younger or older would have exhibited similar changes, as these do not reside in the same child-development category referred to as: childhood (for further details on the categorization, see section 6.1.1).

Curricular Activities The same accounts for the type of educational activities these pupils were undertaking whilst being observed, and noise levels measured. These are specific activities labelled: focussed-learning activities, and typically included book-based (mathematical) exercise work or reading activities. Although these activities will manifest in most contemporary primary school environments, the specific pedagogical methods and teaching approach may vary.

The field study applied one specific type of artificial lighting design, including the choice of luminaires namely pendants, to create the pools-of-light pattern. In Denmark these pendants are relatively familiar objects and associated with certain atmospheric settings. This interpretation likely differs per cultural context. Also, there may be other design solutions thinkable to create a pools-of-light pattern. Whether these would incite similar changes in pupils cannot be speculated about.

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Artificial Lighting Design

Based on these arguments, the findings from the field study as performed should be considered site-and-demographically specific and cannot be related directly to other primary school environments or pupil populations. However, within Denmark, it may be likely that similar research in comparable Folkeskole learning spaces, with similar pupil demographics, sharing the same cultural context and adhering to the same pedagogy, may reveal similar findings.

Future Research

The research presenting in this thesis builds upon preceding research in the academic fields of lighting science and environmental psychology, while positioned in the practice field of architectural (lighting) design. It has contributed with new insights to both areas, yet to further our understanding about the impact of and opportunities for artificial lighting towards occupant behaviour and performance in indoor (learning) environments, further research is required. Three suggestions to further our knowledge, and that builds upon the field experiment performed during this study are: (1) to explore implications of different artificial lighting designs on occupant behaviour, (2) to associate artificial lighting more closely with indoor environmental research, and (3) to expand practice-based research in order to engage with the design and lighting industry community to test and develop appropriate lighting design products and applications.

8.3.1

Variations in Artificial Lighting Designs

This field study only explored how two different artificial lighting patterns, namely that of the relatively standard uniform light pattern and a (non-uniform) pools-of-light pattern as created by pendants, would affect pupils’ behaviour and performance. However, various other non-uniform artificial light patterns may be thinkable, as well as other types artificial light patterns entirely. Exploring the implications of different artificial light patterns on pupil (or occupant) behaviour and concentration would allow to further grow our understanding of the artificial light pattern’s relevance for and impact on the occupants more profoundly.

Discussion

8.3

p. 266

The knowledge derived from this research would serve not only the associated academic fields, but also provide designers of learning spaces greater insight into how, where and in what form to apply artificial lighting in their school building designs. Where most research on artificial lighting for learning spaces thus far has focussed on the impact of two other characteristics, namely light intensity and colour temperature (see sections 3.2.1 – 3.2.3), the expression of the light pattern is largely the responsibility of the designer as the occupants’ experience thereof greatly depends on how the emitted artificial light interacts with the architectural context it is placed in. The occupant’s visual experience of light intensity and colour expressions are less reliant on the specific architectural context, and changes therein have also been successfully studied in lab settings (see section 3.2 for examples). Yet the visual experience of the artificial light pattern is highly related to the architectural context. Therefore, behavioural changes incited by artificial light patterns are best studied in realistic architectural environments.

Discussion

Another benefit of studying the implications of artificial lighting in real-life field settings is that it allows the respondents under investigation to act and behave naturally, as they continue their daily activities and routines under normal conditions instead of being studied in the abstracted reality of the lab. Field studies also offer better opportunity to investigate light impacts for a considerable length of time than typically possible in lab settings. This allows occupants, who act as respondents in the experiment, time to adapt to their new situation. Future research building upon the research presented in this thesis should therefore ideally be placed in a real-life context, either in form of field studies or field experiments, to allow respondents to experience realistic artificial light patterns, and express realistic behaviours.

8.3.2

Relationship with the Indoor Environment

Artificial light is only one parameter of the indoor environment. There are other indoor environmental variables too, namely natural light, sound, temperature and air quality that ultimately jointly define, together with a broad range of architectural variables, the occupants overall experience in the built environment. Some initiatives have started to emerge in Denmark that stimulate such broad perspective research, for example “Skolernes indeklima” by Realdania, “Den Gode Indeliv” by Sustainable Build and “Lys i Skole” by Lighting Metropolis / Gate21 (see section 1.3.4 for details). These initiatives are predominantly concerned with improving the quality of life through the built (learning) environment as a whole, though the artificial lighting is often little references as a key environmental parameter. But as everything is connected, artificial lighting research could be more actively embedded in these large scale, multiple parameter research, and herewith play a more active role in shaping our indoor life quality.

Applied Research

Applied research in the field of the built environment, sometimes also referred to as design-based research, typically generates operational knowledge in relation to architecture's principal identifying characteristic, and that element which rests in the hands of the designer namely the organisation, materialisation and formgiving of space – including that of the light(ting).

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8.3.3

Being embedded in practice has allowed this work to exemplify how artificial lighting can be a constructive design tool that the architectural industry can apply in designing conditions where occupants of buildings can perform their task or activities to the best of their abilities. More applied research revealing the relationship between the artificial lighting and occupant behaviour and well-being in the built environment would provide the architectural industry with constructive knowledge about what type of lighting designs may serve certain occupant activities or mood settings, as well as inspiring architects to think beyond the standard artificial lighting applications commonly applied in learning environments. ___________________________________________________________ Having herewith shared the context, approach and design of this research as well as the findings and learnings collected along the way, I hope the work encourages future researchers to elaborate further on the insights achieved and to look for opportunities to detangle the relationship between artificial lighting and occupant behaviour and well-being further. I also sincerely hope the research will inspire the built environment design community to interpret and translate the acquired new knowledge into supportive artificial lighting applications that further enhance the quality of our everyday, indoor occupant life. Imke Wies Van Mil

Discussion

This research is an example thereof. It explored how two different artificial lighting expressions influence the behaviour of occupants, in this case primary pupils in their respective learning spaces. Its findings provided new knowledge to the academic fields of lighting science and environmental psychology, but also provided new insights to the practice of architectural design about how the artificial lighting could be considered a design parameter to create learning spaces supportive of the prevailing pedagogy. It also provided an example of how artificial lighting can be realized, in this case in form of pendants to create the pools-of-light and ceiling-based luminaires to provide for overall illumination of a learning space.

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References

Andersson, K., Fagerlund, I., & Aslaksen, W. (2008). The perceived indoor climate in Swedish schools. Conference: Indoor Air 2008, 17-22 August 2008, Copenhagen, Denmark

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REFERENCES

Barney, K. & Sørensen T.M. (2016). Light & Learning Environments: a cultural analytical exploration of light in learning environments as a social phenomenon (master's thesis). Kopenhagen University. Baron, R. A., Rea, M. S., & Daniels, S. G. (1992). Effects of indoor lighting (illuminance and spectral distribution) on the performance of cognitive tasks and interpersonal behaviors: The potential mediating role of positive affect. Motivation

Barrett, P. S., Zhang, Y., Davies, F., & Barrett, L. C. (2015). Clever classrooms: Summary report of the HEAD project. Salford: University of Salford. Bellia, L., Pedace, A., & Barbato, G. (2013). Lighting in educational environments: An example of a complete analysis of the effects of daylight and electric light on occupants. Building and Environment, 68, 50–65. https://doi.org/10.1016/j.buildenv.2013.04.005 Benya, J. R. (2001). Lighting for schools. Washington, DC: National Clearinghouse for Educational Facilities. Retrieved from http://www.ncef.org/pubs/lighting.pdf Bisgaard, M. P., & Poulin, P. D. (Eds.). (2017). Statistical Yearbook 2017 (121st ed.). Statistics Denmark. Bluyssen, P. M. (2016). Health, comfort and performance of children in classrooms – New directions for research. Indoor and Built Environment, 26(8), 1040–1050. https://doi.org/10.1177/1420326X16661866 Boray, P.F., Gifford R., & Rosenblood, L. (1989). Effects of Warm White, Cool White and Full-spectrum Fluorescent Lighting on Simple Cognitive Performance, Mood and Ratings of Others. Journal of Environmental Psychology, 9, 297-308. Boyce, P. (2014). Human Factors in Lighting. Boca Raton: CRC Press. https://doi.org/10.1201/b16707

References

and Emotion, 16(1), 1–33. https://doi.org/10.1007/BF00996485

Braun, V. and Clarke, V. (2006) Using thematic analysis in psychology. Qualitative Research in Psychology, 3:2, 77-101

p. 270

Cheryan, S., Ziegler, S. A., Plaut, V. C., & Meltzoff, A. N. (2014). Designing Classrooms to Maximize Student Achievement. Policy Insights from the Behavioral and Brain Sciences, 1(1), 4–12. https://doi.org/10.1177/2372732214548677 Clausen, G., Toftum, J., Bekö, G., Dam-Krogh, E. P., Fangel, A. B., & Andersen, K. (2017). Indeklima i skoler. Realdania. Retrieved from https://realdania.dk/publikationer/fagligepublikationer/indeklimaiskoler Creswell, J. W. (2009). Research design: Qualitative and mixed methods approaches. London and Thousand Oaks: Sage Publications. Cuttle, C. (2015). Lighting Design: A Perception-Based Approach. Routledge. https://doi.org/10.4324/9781315756882 De Kort, Y. A. W., & Veitch, J. A. (2014). From blind spot into the spotlight. Journal of Environmental Psychology, 39, 1–4. https://doi.org/10.1016/j.jenvp.2014.06.005

References

Dilaura, D. L., Houser, K. W., Mistrick, R. G., & Steffy, G. R. (2011). The Lighting Handbook: Reference and Application. Illuminating Engineering; 10th edition. IESNA (Illumination Engineering Society North America) Dunn, R., & Dunn, K. (1978). Teaching students through their individual learning styles. Reston, VA: Reston. Dunn, R., Krimsky, J., Murray, J., & Quinn, P. (1985). Light up Their Lives: A Review of Research on the Effects of Lighting on Children's Achievement and Behavior. The Reading Teacher, 38(9), 863-869. Retrieved from www.jstor.org/stable/20198961 Emmer, E. T. (1984). Understanding classroom behavior. Individual Psychology: The Journal of Adlerian Theory, Research & Practice, 40(1), 102. Retrieved from: http://www.alfredadler.org/ European standard EN 12464-1. (2011). Light and lighting - Lighting of workplaces - Part 1: Indoor workplaces. Fangel, A. B., & Andersen, K. (2017). Indeklima i skoler: Muligheder for adfærdsændringer i hverdagen. Alexandra Institute & Danmarks Tekniske Universitet.

Illumination on the Behaviour of Elementary School Children: Final Report to Extramural Research Programs Directorate, Health Services and Promotions Branch, Health and Welfare Canada. School of Child Care, University of Victoria.

p. 271

Ferguson, R., & Munson, P. A. (1987). The Effects of Artificial

Figueiro, M. G., & Rea, M. S. (2010). Lack of short-wavelength light during the school day delays dim light melatonin onset (DLMO) in middle school students. Neuro endocrinology letters, 31(1), 92–96. Flynn, J. E. (1980). Architectural Lighting and Behavior. Monticello, III.: Vance Bibliographies. Flynn, J. E. (1988). Lighting-design decisions as interventions in human visual space. Environment Aesthetic: Theory, Research, and Applications, 156-170. Cambridge University Press. Flynn, J. E. (1977). A study of subjective responses to low energy and

Flynn, J. E., Spencer, T. J., Martyniuk, O., & Hendrick, C. (1973). Interim study of procedures for investigating the effect of light on impression and behavior. Journal of the Illuminating Engineering Society, 3(1), 87-94. Flynn, J. E., Spencer, T. J., Martyniuk, O., & Hendrick, C. (1975). The influence of spatial light on human judgment. In Proc. CIE 18th Session. Gifford, R. (2007). Environmental Psychology: Principles and Practice (4th ed). Optimal Books. Giusa, F. F. L., & Perney, L. R. (1974). Further Studies on the Effects of Brightness Variations on Attention Span in a Learning Environment. Journal of the Illuminating Engineering Society, 3(3), 249–252. https://doi.org/10.1080/00994480.1974.10732259 Govén, T., Laike, T., Raynham, P., & Sansal, E. (2011). Influence of ambient light on the performance, mood, endocrine systems and other factors of school children. In Proceedings CIE 27 (pp. 112-121) Grangaard, E.M. (1995). Color & light effects on learning. Retrieved from http://www.eric.ed.gov/PDFS/ED382381.pdf

References

nonuniform lighting systems. Lighting Design and Application, 7(2), 6-15.

Guerra, N. G., Williamson, A. A., & Lucas-Molina, B. (2012). Normal development: Infancy, childhood, and adolescence. IACAPAP textbook of child and adolescent mental health, Chapter A, 2, 1-39. p. 272

Hawkes, R. & Loe, D. & Rowlands, E. (1979). A Note Towards the Understanding of Lighting Quality. Journal of the Illuminating Engineering Society. 8. 111-120. https://doi.org/10.1080/00994480.1979.10748578. Hertzberger, H. (2008). Space and Learning: Lessons in Architecture 3. 010 Publishers, Rotterdam. Heschong, L. (1999). Daylighting in Schools: An Investigation into the Relationship between Daylighting and Human Performance. California Energy Commission, Sacramento. Heschong, L. Heschong Mahone Group. 2003. Summary Of Daylighting In Schools: Reanalysis Report. California Energy Commission, Sacramento. Higgins, S., Hall, E., Wall, K., Woolner, P., & McCaughey, C. (2005).

References

The Impact of School Environments: A Literature Review. The Centre for Learning and Teaching-School Education, Communication and Language Science. University of Newcastle. Hopkinson, R. G. & Longmore, J. (1959) Attention and distraction in the lighting of work-places. Ergonomics, 2:4, 321-334. https://doi.org/10.1080/00140135908930446 Houghton, S. Wheldall, K. and Merrett, F. (1988), Classroom Behaviour Problems which Secondary School Teachers say they find most Troublesome. British Educational Research Journal, 14: 297-312. https://doi.org/10.1080/0141192880140306 Illuminating Engineering Society of North America. (2008). Light + design: A guide to designing quality lighting for people and buildings. New York. Keis, O., Helbig, H., Streb, J., Hille, K. (2014). Influence of blueenriched classroom lighting on students‫ ׳‬cognitive performance. Trends in Neuroscience and Education. 3. https://doi.org/10.1016/j.tine.2014.09.001. Kelly, R. (1952). Lighting as an integral part of architecture. College Art Journal, 12(1), 24-30.

Knez I. (1995) Effects of indoor lighting on mood and cognition.

Knez I. (2001). Effects of colour of light on nonvisual psychological processes. Journal of Environmental Psychology; 21: 201–208. Knez, I. & Enmarker, I. (1998). Effects of Office Lighting on Mood

p. 273

Journal of Environmental Psychology; 15: 39–51.

and Cognitive Performance And A Gender Effect in Work Related Judgment. Environment and Behavior. 30. 553-567. https://doi.org/10.1177/001391659803000408. Knez, I., Kers, C. (2000). Effects of Indoor lighting, gender, and age on mood and cognitive performance. Journal of Environment and Behavior, Vol. 32 No.6, 817-831 Sage Publications, Inc. Krimsky, J. (1982). A Comparative Analysis of the Effects of Matching

Kristensen, L. S., Traberg-Borup, S., Petersen, E., & Johnsen, K. (2004). Lyset i skolen: Effektiv belysning med høj dagslysudnyttelse. SBI forlag. Küller, R., & Lindsten, C. (1992). Health and behavior of children in classrooms with and without windows. Journal of Environmental Psychology, 12(4), 305– 317. https://doi.org/10.1016/s0272-4944(05)80079-9 LaGiusa, F.F. & Perney, L.R. (1973). Brightness Patterns Influence Attention Spans. IJD+A. 3. (No. 5). pp. 26-30. Lewis-Beck, M. S., Bryman, A. & Liao, T. F. (Eds.) (2004). The SAGE encyclopaedia of social science research methods (Vols. 1-3). Thousand Oaks, CA: SAGE Publications, Inc. https://doi.org/10.4135/9781412950589 Loe, D.L. and Rowlands, E. (1996). The Art and Science of Lighting: A Strategy for Lighting Design. Lighting Research and Technology. 28. pp. 153-164. Loe, L., Mansfield, K. P., & Rowlands, E. (1994). Appearance of lit environment and its relevance in lighting design: Experimental study. Lighting Research & Technology, 26(3), 119–133. https://doi.org/10.1177/096032719402600301

References

and Mismatching Fourth Grade Students with Their Learning Style Preferences for the Environ mental Element of Light and their Subsequent Reading Speed and Accuracy Scores. (doctoral dissertation). St. John's University, Jamaica, New York.

Löfberg, H. A., Löfstedt, B. E., Nilsson, I., & Wyon, D. P.

p. 274

(1975). Combined Temerature and Lighting Effects on the Performance of Repetitive Tasks with Differing Visual Content. Proceedings of the 18th CIE Session, Sept., London, England. London, W. P. (1987). Full-spectrum classroom light and sickness in pupils. The Lancet, 1205-1206. Maas, J. B., Jayson, J. K. & Kleiber, D. A. (1974). Effects of spectral differences in illumination on fatigue. Journal of Applied Psychology, 59, 524-526. Mangum, S. R. (1998). Effective constrained illumination of threedimensional, light-sensitive objects. Journal of the Illuminating Engineering Society, 27(2), 115-131. Marchand, G. C., Nardi, N. M., Reynolds, D., & Pamoukov, S. (2014). The impact of the classroom built environment on student perceptions and learning. Journal of Environmental Psychology, 40, 187–197. https://doi.org/10.1016/j.jenvp.2014.06.009

References

McColl, S. L., & Veitch, J. A. (2001). Full-spectrum fluorescent lighting: a review of its effects on physiology and health. Psychological Medicine, 31(6), 949–964. https://doi.org/10.1017/s0033291701004251 Moos, R. H. (1979). Evaluating Educational Environments: Procedures, Measures, Findings and Policy Implications. San Francisco, CA: Jossey-Bass. Mott, M. S., Robinson, D. H., Walden, A., Burnette, J., & Rutherford, A. S. (2012). Illuminating the Effects of Dynamic Lighting on Student Learning. SAGE Open, 2(2), 215824401244558. https://doi.org/10.1177/2158244012445585 Petersen, S., Lynge, K., Pedersen, A. L. S., & Rasmussen, H. S. (2016). The effect of increased classroom ventilation rate indicated by reduced CO2-concentration on the performance of schoolwork by children. Indoor Air, 26(3), 366-379. https://doi.org/10.1111/ina.12210 Price, G. E. (1980). Which learning style elements are stable and which tend to change over time. Learning Styles Network Newsletter, 1(3), 1. Rasmussen, S. E. (1962). Experiencing architecture. The MIT Press, Cambridge, USA.

Rautkylä, E., Puolakka, M., Tetri, E., & Halonen, L. (2010). Effects of

Journal of Light & Visual Environment, 34(2), 59–68. https://doi.org/10.2150/jlve.34.59

p. 275

Correlated Colour Temperature and Timing of Light Exposure on Daytime Alertness in Lecture Environments.

Rea, M. S. (1982). An overview of visual performance. Lighting Design and Application, 12(11), 35–41. Rea, M. S. (1983). Effects of Haidinger’s brushes on visual performance. Journal of the Illuminating Engineering Society, 12(3), 197–203. Rea, M. S. (1986). Toward a Model of Visual Performance: Foundations and Data. Journal of the Illuminating Engineering Society. 15. https://doi.org/10.1080/00994480.1986.10748655. Rea, M. S., & Ouellette, M. J. (1991). Relative visual performance: A

Rea, M. S., Ouellette, M. J., & Kennedy, M. E. (1985). Lighting and task parameters affecting posture, performance and subjective ratings. Journal of the Illuminating Engineering Society, 14(2), 231-238. Riding, R. J., & Pugh, J. C. (1987). Dark-interval-threshold, illumination level and children's reading performance. Journal of Research in Reading, 10(1), 21– 28. https://doi.org/10.1111/j.1467-9817.1987.tb00279.x Sala, E., & Rantala, L. (2016). Acoustics and activity noise in school classrooms in Finland. Applied Acoustics, 114, 252–259. https://doi.org/10.1016/j.apacoust.2016.08.009 Schreiber, M. E. (1996). Lighting alternatives: considerations for childcare centres. Young Children, 51(4), 11–13. Shaughnessy, R. & Toyinbo, O. & Turunen, M. & Kurnitski, J. & Haverinen-Shaughnessy, U. (2012). Indoor Environmental Quality in Finnish Elementary Schools and Its Effects on Students’ Health and Learning. https://doi.org/10.13140/RG.2.1.4525.2324. Shield, B. M., & Dockrell, J. E. (2016). The Effects of Noise on Children at School: A Review. Building Acoustics, 10(2), 97– 116. https://doi.org/10.1260/135101003768965960

References

basis for application. Lighting Research and Technology, 23, 135-144.

Simonsen, B., Fairbanks, S., Briesch, A., Myers, D. & Sugai, G. (2008). Evidence-based practices in classroom management: Considerations for research to practice. Education and Treatment of Children, 31(3), 351-380. p. 276

Sleegers, P., Moolenaar, N. M., Galetzka, M., Pruyn, A., Sarroukh, B. E., & van der Zande, B. (2013). Lighting affects students’ concentration positively: Findings from three Dutch studies. Lighting Research & Technology, 45(2), 159–175. https://doi.org/10.1177/1477153512446099 Smith, S.W., & Rea, M. S. (1980). Relationships between office task performance and ratings of feelings and task evaluations under different light sources and levels. CIE Publication No. 50, pp. 207–211. Søndergaard, D. M., Plauborg, H., Szulevicz, T., Fisker, T. B., Mørup, T., Tetzlaff-Petersen, L., et al. (2014). Ro og klasseledelse i folkeskolen. Danish Ministry of Education. Retrieved from https://www.uvm.dk/publikationer/ressourcecenter-forfolkeskolen/undervisningsmiljo-og-trivsel/2014-rapportom-ro-og-klasseledelse-i-folkeskolen

References

Sörqvist, P., & Marsh, J. E. (2015). How Concentration Shields Against Distraction. Current Directions in Psychological Science, 24(4), 267–272. https://doi.org/10.1177/0963721415577356 Stavnes, R. L. (2014). Disruptive Behavior in School (master's thesis). (L. Duesund, Ed.). University of Oslo. Steidle, A., Hanke, E.-V., & Werth, L. (2013). In The Dark We Cooperate: The Situated Nature of Procedural Embodiment. Social Cognition, 31(2), 275–300. https://doi.org/10.1521/soco.2013.31.2.275 Tanner, C. (2009). Effects of school design on student outcomes. Journal of Educational Administration. 47(3), pp. 381 – 399. https://doi.org/10.1108/09578230910955809. Taylor, L.H., Sucov, E.W. and Shaffer, D.H. (1975). Office Lighting and Performance. IJD+A. Vol. 5 (No.5). pp. 30-36. Toftum, J., Wargocki, P., & Clausen, G. (2011). Indeklima i skoler— Status og konsekvenser. FOA-Fag og arbejde. UVM (Danish Ministry of Education). (2013). Agreement between the Danish Government (the Social Democrats, the Social- Liberal Party and the Socialist People’s Party), the Liberal Party of

p. 277

Denmark and the Danish People’s Party on an improvement of standards in the Danish public school (primary and lower secondary education). Børne- og Undervisningsministeriet. http://eng.uvm.dk/-/media/filer/uvm-eng/pdf/13/131007folkeskolereformaftale-eng-red--2-.pdf?la=en UVM (Danish Ministry of Education). (2014). Improving the Public School. Danish Ministry of Education. Retrieved from https://www.uvm.dk//media/filer/uvm/publikationer/engelsksprogede/2014improving-the-public-schools.pdf Van Mil, I. W., Iversen, A., Osterhaus, W., Garcia Alvarez, M., Petersen, S., & Jeong, C-H. (2018). Light at eye level is a means to create energy savings and space for learning, focus and concentration: Research Report for the Danish Electricity Research Fund (ElForsk). https://elforsk.dk/sites/elforsk.dk/files/media/do kumenter/2018-11/349_062_slutrapport.pdf

Quality. Journal of the Illuminating Engineering Society. 30. P 124-140. https://doi.org/10.1080/00994480.2001.10748341. Veitch, J., & Newsham, G. (1996). Determinants of Lighting Quality II: Research and Recommendations. Villumsen, K., & Møldrup, M. S. (2013). Indeklima og fagligt udbytte: En analyse af sammenhængen mellem elevernes oplevelse af indeklima og fagligt udbytte i grundskolen. Dansk Center for Undervisningsmiljø (DCUM). Wargocki, P., & Wyon, D. (2007). The Effects of Moderately Raised Classroom Temperatures and Classroom Ventilation Rate on the Performance of Schoolwork by Children (RP-1257). HVAC&R Research, 13(2), 193–220. https://doi.org/10.1080/10789669.2007.10390951 Wertz, F.J., Charmaz, K., McMullen, L.M., Josselson, R., Anderson, R., McSpadden, E. (2011). Five ways of doing qualitative analysis. The Guilford Press. Wessolowski, N., Koenig, H., Schulte-Markwort, M., & Barkmann, C. (2014). The effect of variable light on the fidgetiness and social behavior of pupils in school. Journal of Environmental Psychology, 39, 101–108. https://doi.org/10.1016/j.jenvp.2014.05.001

References

Veitch, J. (2001). Psychological Processes Influencing Lighting

Winterbottom, M., & Wilkins, A. (2009). Lighting and discomfort in the classroom. Journal of Environmental Psychology, 29(1), 63–75. https://doi.org/10.1016/j.jenvp.2008.11.007 p. 278

Woolner, P., & Hall, E. (2010). Noise in Schools: A Holistic Approach to the Issue. International Journal of Environmental Research and Public Health, 7(8), 3255–3269. https://doi.org/10.3390/ijerph7083255 Zhong, C.-B., Bohns, V. K., & Gino, F. (2010). Good Lamps Are the Best Police. Psychological Science, 21(3), 311–314. https://doi.org/10.1177/0956797609360754

References

Imke Wies van Mil is a professional architectural lighting designer. Her professional background combined with a personal motivation drove her to investigate how artificial lighting can be applied in contemporary educational environments to benefit pupils’ learning. The research presented in this thesis was conducted as an industrial PhD in collaboration with architectural practice Henning Larsen and the Royal Danish Academy - Architecture, Design, Conservation. The research investigates the potential of artificial lighting in learning environments to improve the conditions for undisturbed learning. Disturbances in class are found to be predominantly caused by pupils themselves, typically manifested as noise. A quieter learning environment may be achieved by discouraging pupil behaviours that cause disruptions. Preceding research has established that artificial lighting in learning spaces has an impact on pupils beyond making things visible. For example, lighting affects pupils’ mood, motivation and social interactions, which in turn impacts behaviour and learning performance. Through a design intervention in a live school environment, this research has established that artificial lighting can be purposely utilised in contemporary learning spaces to reduce the occurrence of disturbing behaviours during class and improve the conditions for undisturbed learning.

Artificial Lighting Design for Primary Learning Environments

Articles inside

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8. DISCUSSION

2 LEARNING SPACES AND PUPIL BEHAVIOUR

1. INTRODUCTION