ABOUT USABILITY IN LEARNING INTELLIGENT COLLABORATIVE SYSTEMS Loredana Mocean*, Robert Andrei Buchmann*
Abstract: Intelligent collaborative learning systems are widely considered a subset of collaborative systems employed in organizations where computer assisted training is applied. This paper approaches some usability concerns related to a previously presented learning system based on the RDF and ontological modeling of e-learning content and processes. Our studies try to integrate knowledge models expressed as RDF with interaction design in a learning context. Direct feedback is individualized for test subjects and learning-related tasks, especially form-filling and concept acquisition. Key words: RDF, OWL, learning, usability JEL Classification: C88
1. Introduction Usability is the attribute of a software product of being easy to learn, to use and reuse, robust against usage errors and exceptions, pleasant and efficient from the user point of view. Usability depends on a number of factors such as the way and the degree to which the application functionality meets the user requirements and the way in which the navigational flow corresponds to the user’s expectances. The benefits of implementing a usability strategy in any software project are presented in fig. 1 (adapted after TreeWorks). *
BabeĹ&#x;-Bolyai University, Faculty of Economics and Business Administration, Cluj-Napoca, Romania. E-mail addresses: loredana.mocean@econ.ubbcluj. ro, robert.buchmann@econ.ubbcluj.ro.
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Figure 1. The benefits of implementing a usability strategy Cost reduction • Long term costs • Support costs • Training costs • Development costs
Reflects on
End-users • Increased productivity • Increased success • Task accomplishment • Increased satisfaction
Our paper proposes a user experience channeling system based on underlying RDF assertions for the content of a learning system in order to provide a reciprocal interaction style and identify in an adaptive way the concepts that are problematic for the advancement of each student, due to concept prerequisite causality. 2. Related works The fundamental and applicative research field approached in this paper is subordinated to modern trends of encompassing architectural models in quality models. Several software quality models have been established and all of them regard usability as an essential factor for software acceptance and validation. Various approaches to the notion of usability trigger a need for an actionable definition in the context of integration with the quality domain. The McCall model groups quality factors in three categories – usage, revision and transition, with usability being the main factor in the first category (Noșca, 2003). The Boehm model is one of the first quality software models in which usability appears as a software quality attribute. The model provided by Standard ISO/IEC 912 proposes a set of six quality attributes: functionality, reliability, usability, performance, maintainability, portability. By analizying the mentioned models and some of the more recent ones (ex. Dromey şi Grifith, SATC, Kano) usability appears to be a priority in the software product development processes. Although a great deal of usability research was published on the subject, the niche of collaborative learning systems has less involvement from 98
usability specialists, at least in an integrating manner, meant to design interaction based on the relationships stored in a knowledge repository. In paper written by Karam et al. (2010) authors present a public usability study that provides preliminary results on the effectiveness of a universally designed system that conveys music and other sounds into tactile sensations and they say “Designing and implementing an interactive system that offers universal access to music, sound, and entertainment to a diverse range of users poses many challenges”. Other authors (Liem et al., 2010) present some research in the field of ICT and state that “ICT has become an essential tool in education, employment, lifestyle, and recreation. Most people rely on ICT products both in their daily routine, as well as for more specialized activities, but are very important to study the usability of these systems”. Another important paper presents some aspects about online learning. “As distance education becomes more common, the need arises to recognize that a growing number of those who take advantage of the increased educational opportunities are disabled. In recognizing this development, institutions of higher education must consciously make the decision to proactively incorporate accessibility standards and guidelines into their course rooms, coursework, and course materials so that all have comparable opportunities to contribute effectively to the educational process”, say the author (Parisseau, 2010). Banergee (2005) states that “Instructional design influences accommodation decisions by establishing the channels of interaction and communication within the course, as well as the degree of accessibility of information, and the options for technical adaptation.” Most usability studies have a goal of measuring and quantifying user interaction, or optimizing it through interface design decisions. Our paper proposes a knowledge-driven interaction system determining the learning flow in a manner adaptive to the evolution of the student results and learning processes. 3. The proposed model In this paper we continue the research regarding an application model proposed in Mocean, Buchmann & Ciaca (2010), by touching 99
its usability implications, by studying the capacity of the model to be understood, studied, used and attractive in the specific context. The general arhitectural model is descriped ĂŽn figure 2. And the main user interface structure in figure 3. Figure 2. The general architectural solution
Figure 3. One of the main windows, the window Username Professor
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Figure 4. The Course window
Figure 5. The Username window
The concept store doubles the application database, acting as a knowledge base which reflects learning relationships between concepts occurring within the learning content. The relationships taken into account fall in two categories: 101
yy Explicit natural relationships occurring between concepts due to their semantics; yy Explicited relationships (which are usually implicit) mapped on the understanding causality: a DependsOns transitive object property defines the understanding prerequisites for each concept. By loading a piece of content, a Python generated web page annotates the content with RDF in HTML attributes based on the relationships queried via SPARQL from the concept triplestore. The explicit natural relationships impact usability through the reading experience augmentation, while the understanding prerequisites are especially important in the evaluation process for question and answer generation. OWL restriction classes are used for grouping categories of enabled/enabling questions and answers and their concepts. A sample of the triplestore is expressed using the N3 notation (prefixes avoided for brevity): :Answer a owl:Class. :Question a owl:Class. :PossibleAnswer a owl:ObjectProperty; rdfs:domain :Question; rdfs:range :Answer. :AnswerText a owl:DatatypeProperty; rdfs:domain :Answer; rdfs:range xsd:string :QuestionText a owl:DatatypeProperty; rdfs:domain :Question; rdfs:range xsd:string. :Enables a owl:ObjectProperty; rdfs:domain :Answer rdfs:range :Question :SelectedAnswer a owl:ObjectProperty; rdfs:subClassOf _:x. _:x a owl:Restriction; owl:onProperty :Enables; owl:allValuesFrom :EnabledQuestion. :AnsweredQuestion a owl:Restriction; owl:onProperty :SelectedAnswer owl:someValuesFrom :Answer
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:DependsOn a owl:ObjectProperty; rdfs:domain :LearningConcept rdfs:range :LearningConcept :EvaluatedBy a owl:ObjectProperty; rdfs:domain :LearningConcept rdfs:range :Question :AcquiredConcept a owl:Restriction; owl:onProperty :DependsOn; owl:allValuesFrom :CorrectAnsweredConcept
The store is managed and queried through the RDFLib Python library in order to extract contextual semantics based on the current learning objects approached by the student. The semantics control the question flow (by making sure the content is not delivered unless the student acquires all prerequisite concepts). 4. Usability Criteria a. User Interface Design
As the paper below indicates (Romanescu & IvaĹ&#x;c, 2007), there are three solutions for interaction design in learning collaborative systems: reactive, proactive and reciprocal. The interaction levels are defined based on user actions: movement, navigation, investigation, selection, confirmation, elaboration. The reactive interaction occurs in the question-answer scenarios, as indicated by table 1. Proactive interaction emphasizes the constructive activity of the student, while reciprocal interaction implies elements of artificial intelligence in order to define a reciprocal adaptivity between the student and the system. b. Augmented readability and reading experience
Indicators taken into consideration are:: yy Fonts: attractive and highly readable (Georgia), with Unicode support; yy File types: text, pdf, audio, video, images, others; yy Paragraph layout, readable, spaced and mapped to the conceptual discourse; yy The help systems; 103
yy Color schemes, for improved accesibility; yy Contextual term dictionary for concepts occurring in courses. Of these elements the contextual term dictionary and the help system are optimized based on the learning activity of each student, and triggered by mouse events on annotated keywords from the content.
Reactive
Sequential Content structuring
Proactive
Sequential Structured Content structuring
Reciprocal
Structured Logical structuring
Chat Free answer Step by step presentation Sequential Designer navigation using Next/ Back buttons Free course selection Predefined answers Designer Radio options Student Check boxes Menus Dialogue Mixed controls Context Student based feedback Nonsequential navigation
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Feedback
Control
Implementation elements
Design
Interaction type
Table 1. Interaction types and their characteristics
Learning by indication Adequate tests
Learning by exercising Adequate tests
Learning by discovery Adequate tests
c. Navigation
The model takes into consideration the three aspects of the didactic act – teaching, learning and evaluation. The following elements are improved by the semantic annotations: yy Application map, due to the complexity of the modules, reduces the sense of loss in the application; yy Paging and Scrolling, from students task analysis, we conclude that they prefer paging; the information quantity is larger and pages can be mapped on the content chapter/section structure;. yy Minimized page delay: pages that load fast are preferable, based on file formats that are portable, compressed, with download acceleration tools; yy Well structured menus; yy Navigational element exteriorization, for avoiding accidental access to noncontextual commands; yy Display of guiding messages. d. Security
Any threat to a learning collaborative system is a threat to the quality and efficiency of the educational and evaluation act. The security developer must take into consideration the requirements presented in Table 2 (adapted after Oprea et al., 2002). 5. Usability tests The RDF-driven forms were tested with 2 sets of 12 subjects who passed preliminary tests with similar grades – one using the augmented interface, one using the nonaugmented interface. The tests was implemented in the computer rooms of Faculty of Economics and Business Administration. AutoIt scripts have been used to implement and measure reference tasks (shortest paths to accomplish a learning task, without taking into consideration the actual concept acquisition process). Task analysis for subjects was developed and compared to the reference tasks and the non-augmented interaction sets for the same tasks. 105
Table 2. Security requirements for a performant learning collaborative system Requirement
Purpose
Privacy
Protecting information against unauthorized access (courses, evaluations)
Integrity
Protecting information against accidental or unauthorized updating or loss
Availability
Precision
Accuracy
Implementation Identifying and authenticating users Access control Hierarchical classification of integrity levels
Identifying and authenticating users Access control Hierarchical classification of integrity levels Domain separation Providing answers Connecting to all authorized redundant requests resources with minimal costs Task discontinuation plan for system fails Providing correct Implementing answers to content validation requests protocols Providing useful Implementing up data to date content, correlated with user requirements
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Details Access level User privileges (read, write, download etc.) Decomposition of the system in objects, subjects and operations User privileges for authenticated and unauthenticated users Identifying and labelling data for integrity assurance Distributed access hardware and software platform
Learning content quality assurance Learning content quality assurance
The results was collected and processed within the help of Microsoft Office Tools Package and Data Tools Package from Microsoft Excel. An improvement of 9-15% was measured in the speed with which the augmented interface channeled the learning process through a series of training, questions and answer exercises. 6. Conclusions Usability improvements based on the underlying knowledge content is an innovative and emergent field of research. Both the user and the system get useful hints and information in a reciprocal adpativity regime. Ease of use can be measured by various usability indicators but other mechanisms are needed to really improve the learning process, by identifying precisely the understanding difficulties and adapting the interaction transitions flow based on this knowledge. This paper proposed a system that implements such a mechanism using a triplestore that supplements the regular leraning content management system. References 1. Banergee, M., “In Distance education and accommodations for students with learning disabilities: Implications for postsecondary service providers”, http://www.resourceroom.net/older/distance_ ed.asp. 2. Dromey, R. G. (1996), “Cornering the Chimera”, IEEE, January. 3. Fenton, N. (1990), “Deriving Structurally Based Software Measures”, Software Systems Journal, pp. 177-187. 4. Karam, M., Branje, C. et. al. (2010), “Comparing Computer Versus Human Data Collection Methods for Public Usability Evaluations of a Tactile-Audio Display”, Journal of Usabiliy Studies, vol. 5, issue 4. 5. Liem, A. et al. (2010), “Moving Towards an All-Encompassing Universal Design Approach in ICT”, Journal of Usabiliy Studies, vol. 5, issue 4. 6. Mocean, L., Buchmann R., Ciaca M. (2010), “Learning Intelligent Collaborative Systems”, Rev. Economy Informatics, vol. 10. Nr.1, 2010. 7. Mocean, L., Ciaca M., “About Modeling The ERP Systems”, Journal Studia Universitatis Babes-Bolyai Oeconomica, no. 54 issue 1, pp. 78-86.
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8. Morar G., Muntean C., Tomai N. (2010), “An Adaptive M-learning Architecture for Building and Delivering Content based on Learning Objects”, Economy Informatics Journal, vol. 10, no. 1. 9. Noşca, Gh. (2003), “Analiza comparată a modelelor calităţii software”, Rev. Informatica Economică, nr. 4. 10. Oprea, D., Airinei D., et al. (2002), Sisteme informaţionale pentru afaceri, Polirom. 11. Parisseau, C. (2010), „Online Learning: Designing for All Users”, Journal of Usabiliy Studies, vol. 5, issue 4. 12. Romanescu A., Ivaşc C. (2007), Condiţii psihopedagogice în elaborarea softului educaţional, Conferinţa Naţională a Învăţământului virtual. 13. Trăuşan-Matu, Ş. (2009), Interacţiunea conversaţională în sistemele colaborative pe Web, Ed. Matrix Rom, Bucureşti. 14. http://www.tree.ro/ro/strategie-white-papers/probleme-de-uzabilitate.
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