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Record: 1 Title: Awareness of cognitive strategies: The relationship between university students' metacognition...

Authors: ROMAINVILLE, MARC Source: Studies in Higher Education. Sep94, Vol. 19 Issue 3, p359. 8p. 1 Diagram.

Document Type: Article Subjects: METACOGNITION COGNITION ACADEMIC achievement Abstract: Presents an exploratory research about first­year university students' metacognition. Examination of the way university students describe, judge and justify their cognitive strategies; Relationship between students' metacognition and academic performance; Measurement of students knowledge of cognitive processes and cognitive results; Factors affecting metacognition.

ISSN: 0307­5079 Accession Number: 9411182663 Database: Professional Development Collection RESEARCH NOTE

Awareness of Cognitive Strategies: the relationship between university students' metacognition and their performance ABSTRACT This study is part of an exploratory research project on first­year university students' metacognition.

Using data from structured interviews, the investigation examines the way university students describe, judge and justify their cognitive strategies. This paper explores in particular the relationship between students' metacognition and their academic performance. In a sample of 35 economics students, a relationship was found between performance and some students' metacognitive knowledge characteristics. In particular, it was found that high achieving students seem to be aware of more cognitive rules and to evoke metacognitive knowledge about cognitive processes and cognitive results more frequently (for instance, justification of a cognitive rule by an anticipated cognitive result). Their metacognitive knowledge also seemed more structured and hierarchically organised; for instance, high achieving students describe more frequently their cognitive strategy as a complex sequence including several relationships (temporal, alternative, etc.). A cluster analysis also unfolded five metacognitive profiles: these profiles associate different performance levels with students ' metacognitive knowledge characteristics, their learning conception and their attribution modes. This paper concludes with a discussion on the implications of the results for 'learning to learn' programmes. It is suggested that the main objective of these programmes should be to foster students' reflection on their own learning.

Introduction One of the most frequent criticisms levelled at continental universities is the failure rate at the end of the first year.

This is often considered as wasteful, both societally and individually. As a consequence, there has been considerable research to improve understanding of the difficulties students face by investigating students' experiences of learning in higher education (Entwistle & Ramsden, 1983; Marton & Saljo, 1984; Bowden, 1986; Entwistle, 1991; Meyer & Watson, 1991). Even if 'to learn' is not synonymous with 'to succeed' (e.g. some students succeed at university without the acquisition of lasting knowledge), these studies have demonstrated the existence of a relationship between differences in the quality of learning (conception of learning, approaches, http://web.b.ebscohost.com/ehost/delivery?sid=2eeb859a­fe09­459a­8789­092493cb4bfe%40sessionmgr101&vid=1&hid=101&ReturnUrl=http%3a%2f%2fweb.…

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orientation, etc.) and differences in outcome. However, these studies have also suggested that the effectiveness of students' strategies depends on the context of learning and on the learner's own characteristics (e.g. academic environments, learning style) (Kirby, 1984; Laurillard, 1984; Entwistle, 1987; Pask, 1988; Ramsden, 1984, 1988).

It is on this basis that the hypothesis of our study depends, namely that university students must be able to manage their own cognitive strategies in order to succeed. They must be able to adapt the strategies to their personal characteristics and to the context of their learning. A first stage in this process is probably that students must be aware of their cognitive strategies and be able to describe and criticise them. In this context, the research reported in this paper explores the potential relationship between students' performance and their capacity to talk about, describe and criticise their cognitive strategies. The focus of this study is not the cognitive strategies of students themselves but rather the way they can talk about them and construct them as problematic entities. It is, therefore, this part of student's metacognition that this study attempted to explore. Its principal aims are the following: 1. to build a typology of university students' metacognitive knowledge of their cognitive strategies; 2. using the typology to analyse the following aspect of the student's metacognition: what is the nature of the knowledge students have about their own cognitive strategies and the factors which influence them? and 3. to explore the hypothesis that a positive relationship exists between students' metacognition and their cognitive efficiency, i.e. is there a relationship between reflecting on cognitive strategies and having better cognitive efficiency?

The Study Conceptual Framework In the psychological literature, the concept of metacognition has two distinct dimensions. It refers both to the knowledge that human thinkers have about their own cognition and to the regulation of it (Lawson, 1984; Forrest­ Pressley et al., 1985; Weinert & Kluwe, 1987; Gombert, 1990). These components are connected; on the one hand, the metacognitive knowledge should be seen as a source of influence upon regulation and, on the other hand, it is a result of regulation that we become conscious of our cognition. However, some theoretical and methodological points (e.g. difference in consciousness between process of regulation and knowledge) distinguish them.

This study explores the first dimension of metacognition, i.e. students' metacognitive knowledge. This knowledge is the result of deliberate reflection upon their own cognitive activity and can be analysed through students' verbal reports. More particularly, the metacognitive knowledge explored by this research is the knowledge that students have articulated about their cognitive strategies and the factors that influence them (cf. metalearning, Biggs, 1984, 1986).

Sample In this exploratory study, semi­structured interviews were conducted with first­year economics students taking a history course at the University of Namur. A non­proportional stratified sampling was used according to students' marks at a previous test. For each of the seven possible grades awarded by the teacher, five students were selected randomly, giving an overall sample of 35 students (16 females and 19 males).

Interview An interview schedule was devised and pre­tested. This schedule was divided into four parts: three items concerning students' conceptions of learning; 30 items concerning the students' metacognitive knowledge about cognitive strategies used to manage their learning; three items to explore the way in which students explain their results on the test (attribution); and three items to review students' reactions to their initial performance at university (test). http://web.b.ebscohost.com/ehost/delivery?sid=2eeb859a­fe09­459a­8789­092493cb4bfe%40sessionmgr101&vid=1&hid=101&ReturnUrl=http%3a%2f%2fweb.…

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Coding System Interviews were recorded and then transcribed. A coding system was devised. In total, the coding system includes 65 categories for 16 axes. A comprehensive description of each category and a coding algorithm may be found in Romainville (1993). The general aim of the coding system was to describe the characteristics of metacognitive knowledge conveyed by students and the relationships established within them. For instance, it aimed to answer the following questions: 1. for the knowledge of the student's cognitive strategies: ­­can the student describe the rules underlying his/her strategy? If so, what are they? ­­are the purposes of the rule specified? If so, what kind of purposes are they? ­­is the rule judged by the student?

2. for the knowledge of the factors which influence cognitive strategies: ­­does the knowledge relate to their personal features as 'thinkers' (e.g. their cognitive styles)? Does it relate to the learning situation (e.g. task demands)? ­­is the knowledge abstract?

3. for relationships between knowledge: ­­how do students justify their choice (analysis of 'chain' relationships between a strategy and a variable)?

The coding system was tested by seven judges. The rules of coding were specified operationally. An inter­rater reliability was calculated: ratings fluctuated between 76% and 92%.

Two other coding grids were also developed. The first one was used to code the students' conception of learning.

Six categories, inspired by the work of Saljo (Marton & Saljo, 1984; Entwistle, 1988), have been defined. They represent different steps within a continuum from a conception centred on reproduction to a conception of learning as a personal construction of meaning. Another one, inspired from attribution theory (Weiner, 1974 and more specifically for higher education, Clifford, 1986; Van Overwalle & De Metsenaere, 1990) provides a method of coding the way students explain their performance.

The research reported here is based on student's retrospective verbal accounts. Indeed, data collected were only a part of students' metacognitive knowledge about their strategies: the knowledge they were able to put into words or the knowledge they wanted or thought they wanted to verbalise during interview. The research tools (e.g. the interview schedule which encourages a metacognitive attitude) probably created new metacognitive knowledge or at least influenced the quantity, the quality and the kind of metacognitive knowledge that students verbalised. Therefore, the data collected here do not fully reflect or represent the students' metacognitive knowledge. In fact, data are both accounts of previous knowledge and new knowledge produced by the research device.

Results The focus of this report is on findings related to the third aim of the research. As the study was of an exploratory nature, the findings merely indicate a number of aspects of students' metacognition that could be connected to their performance.

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First of all, each descriptive variable of metacognition (e.g. amount of rules verbalised, amount of justified rules, hierarchy relations between rules...) was linked to a performance indicator: students' final marks on a history test.

These marks are strongly correlated with students' final marks means (0.88). Therefore, these marks seem to be a valid indicator of academic performance. Two statistical analyses were applied: a non parametric analysis of variance (the Kruskal­Wallis test) and a correlation analysis (coefficient r).

With respect to metacognitive knowledge of cognitive strategies, two significant positive relationships with performance were found: the quantity of knowledge and its structure: ­­high achieving students describe more rules; ­­high achieving students describe their strategies more often in terms of temporal sequence ('I do that after that') or as a complex structure of rules ('I do that but not that', see example below). Finally their metacognitive knowledge is better hierarchically organised: they break up their strategy into rules, their rules into subrules and so on.

I take note of important facts or I take note to complete a sentence of the book or when the teacher provides some details. But if he supplies too many examples, I select only one. (student A3, taking note, sequence of two alternative relations between three rules, follow­up by a restriction for the third rule) However, results also indicated that other metacognitive characteristics were not correlated with performance: high achievers did not describe their strategy more precisely: they did not specify more often the conditions and aims of their rules. The conditions governing the rules were no different and they did not judge their strategies more often.

If we turn to the metacognitive knowledge of factors which influence cognitive strategies, results show that quantity of knowledge is not correlated with performance: high achieving students do not take more factors into account when drawing up their cognitive strategies. Nor do they take a greater variety of factors into account. In the same way, knowledge abstraction is not correlated with performance: high achieving students' metacognitive knowledge is not more generalisable. Finally they do not justify their cognitive strategies any more frequently nor do they describe more often the effects of their strategies. However, the results also show some positive relationships: ­­high achieving students evoke metacognitive knowledge of cognitive process and cognitive results more frequently. Example: 'I don't memorise details, dates because even if I retain it at this moment, I will forget it later, student C3, rule 2 justified by anticipated cognitive result; ­­high achievers justify their strategies more frequently in the form of complex sequences of reasons connected to each other. Again it is the structure of metacognitive knowledge that distinguishes high from low achieving students.

Afterwards, a cluster analysis was used (Everitt, 1980). CLUSTAN package with Ward method was employed.

To begin with, the model presented in Fig. 1 will be described. Cluster analysis was executed on five variables: ­­conception of learning: each student has a learning conception attached to one category of the coding system's hierarchy (accumulation, surface study, deep study, applying, understanding, personal growth); ­­attribution: each student also tries to explain his/her performance with one of the four attribution modes described: external factors, non­intentional factors, amount of time spent to prepare examination or his/her learning strategies; http://web.b.ebscohost.com/ehost/delivery?sid=2eeb859a­fe09­459a­8789­092493cb4bfe%40sessionmgr101&vid=1&hid=101&ReturnUrl=http%3a%2f%2fweb.…

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­­metacognition (amount and structure): finally each student reports on metacognitive knowledge about his/her cognitive strategies. Two dimensions of this knowledge are taken into account: amount and structure; and ­­academic performance: indicators are average marks in the history examination.

Results showed a typology of five metacognitive profiles. For instance, profile I will be briefly described. These students have reported very little metacognitive knowledge. Moreover this knowledge is poorly structured. Their learning conception is centred on surface accumulation: to learn is to try to succeed at examination by reproducing facts or what they consider to be desired learning outcomes. Their score is very low. Their attributions concern non­intentional factors or amount of time factors. Interactive hypotheses can be formulated: seeing that these students do not believe that their cognitive strategies have an influence on their performance, they believe that it is not helpful to look to metacognitive activity. This inclination is reinforced by their learning conception: they consider learning as surface reproduction, a temporary compiling of isolated facts which become necessary because of the approaching examination. These features would be connected with poor performances that in return do not encourage metacognitive activity about cognitive strategies that lead to them. It seems thus that these variables interact with one another mutually to reinforce them: if students fail, it is more difficult for them to recognise that it is probably due to their own cognitive strategies: they will then be less inclined to analyse them and therefore will not be able to adjust them easily to a new learning context, etc. Qualitative analysis confirms that these students present a lack of academic involvement: they have not consulated their examination script, they have declared that they have not attempted any change in their cognitive strategies or that they have made only modifications in the time they allocate to study. In any case, their cognitive strategies are never critically examined.

Conclusions: implications for the improvement of students' strategies How can we use the results as a base for improving learning strategies? More precisely, are 'learning to learn' programmes­­which try to emphasise students' awareness rather than teach study skills (see for instance, Gibbs, 1981; Smith, 1985; Martin & Ramsden, 1987; Romainville & Biasin, 1988; Weinstein, 1988)­­legitimated by the findings presented here?

According to the assumptions of this approach, the research showed that high achieving students are those who are particularly aware of their cognitive strategies and of the factors which influence them. Their metacognitive knowledge seems to be better structured and more centred on cognitive process. But can research on learning be prescriptive? In other words, can we give advice or guidelines according to the results of a descriptive research? At least three limitations must be noted. ­­A positive relationship between metacognition and performance was observed here in an exploratory study, in one subject in one university. Further studies must confirm it. ­­Correlational findings must not be assumed as a proof of cause­and­effect relationships. Correlation analysis expresses the degree to which metacognition and performance co­vary but does not indicate the direction: so ff it is partly because high achieving students evolve metacognitive activity that they succeed, it may also be because their cognitive activity is successful that they reflect more on it. ­­Constructing programmes from high achievers' characteristics is based on the assumption that if low achievers adopted the strategies of high achieving students, they should improve their cognitive efficiency. This assumption is doubtful. Studies have indeed shown that teaching expert strategies to novices is not effective mainly because novices do not make use of the knowledge required for their activation (Alexander & Judy, 1988).

These three restrictions suggest that the findings should be interpreted with caution. Only some points which should be explored in the training of student's strategies will be mentioned. http://web.b.ebscohost.com/ehost/delivery?sid=2eeb859a­fe09­459a­8789­092493cb4bfe%40sessionmgr101&vid=1&hid=101&ReturnUrl=http%3a%2f%2fweb.…

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Results suggest some areas in which students' metacognition could be strengthened. For instance, awareness of the aims of strategies in terms of cognitive processes and cognitive results should be trained during improvement programmes: what do students aim for with this cognitive rule? What kind of cognitive results do they expect from it? Results also show that a training programme should improve connections within metacognitive knowledge: why do students use this cognitive rule? Which order should they use them in? Are there alternative rules?...

Learning conceptions seem to be tied with metacognition: unsophisticated conceptions are more often connected to poor and instructured metacognitive knowledge (profiles 1 and 2). Our hypothesis is twofold: on the one hand, having a more sophisticated conception is probably a prerequisite of involvement in metacognitive activity and, on the other hand, to think about cognitive strategies and their effects is probably a good way to enrich learning conception.

The research has also shown that some low achieving students seem to be inclined to explain their performance by a lack of time spent on studying. The quality of learning strategies is never blamed (cf. profile 1). Moreover these students have taken on board only quantitative readjustments (example: studying a particular topic twice rather than once). Once more, the hypothesis here is a double one: on the one hand, to be aware that strategies qualitatively influence learning outcomes­­and therefore performance itself­­is probably a prerequisite of metacognition but, on the other hand, metacognitive training (for example, learning to describe the effects of strategies) should maybe induce attribution modifications. In any case, these aspects of students' reflection must be considered together.

Learning is such an individual and complicated activity that learners themselves should be able to wonder about its components and reflect on it, to become adaptable to new learning contexts. To describe, to judge and to justify their cognitive strategies is probably the first step in this process.

GRAPH: FIG. 1. Metacognition­performance relationship (profiles).

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By MARC ROMAINVILLE, Service de Pedagogie Universitaire, University of Namur Correspondence: Marc Romainville, Service de Pedagogie Universitaire, University of Namur, 61 Rue de Bruxelles, 5000 Namur, Belgium.

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