Dissonance in Student Learning Patterns: when to ...

Studies in Higher Education Volume 28, No. 1, 2003

Dissonance in Student Learning Patterns: when to revise theory? JAN VERMUNT & ALEXANDER MINNAERT Leiden University, the Netherlands

This study focuses on the issue of theoretically incongruent learning patterns found among subgroups of students. The longitudinal study was done among first year university students in a student-oriented learning environment. Students completed the Inventory of Learning Styles (ILS) twice, once in the first, and once in the third trimester. This inventory assesses learning strategies, learning orientations and learning conceptions. Students’ learning patterns in the third trimester were far more dissonant than in the first trimester. Data for two subgroups of students were analysed separately. Both groups showed learning patterns dissonant from theory, especially in the relations between orientations and conceptions on the one hand, and learning strategies on the other hand. This raises the question that, when dissonant patterns are observed among groups of students that do not conform to what is expected theoretically, when is it necessary to revise theory and when can real dissonance be confirmed? After revising theory, dissonant patterns may disappear, because they no longer deviate from what can be expected theoretically.

ABSTRACT

Introduction Phenomena of Dissonance in Students’ Way of Learning The phenomenon of what is now referred to as dissonance in students’ learning patterns has its origins in an individual difference study by Meyer (1991). This study drew attention to patterns of learning engagement that were essentially theoretically uninterpretable. In particular, the expected and theoretically coherent linkages between learning conceptions, intentions, motives and processes failed to appear in a recognisable form. For certain subgroups of students, it was the case in a number of individual difference studies that he conducted that aspects of learning patterns that are theoretically incongruent with one another were actually empirically connected (Meyer, 1991, 2000). Vermunt and Verloop (2000) reviewed studies that used the Inventory of Learning Styles (ILS) as a research instrument for evidence of dissonance in learning patterns. The ILS is a self-report inventory that covers four learning components: processing strategies, regulation strategies, learning conceptions and learning orientations (see Table I). Vermunt (1998) found four qualitatively different learning patterns that take the inter-individual variability in student learning into account and reflect the nature of relatively stable, but modifiable, constructs: undirected, reproduction-directed, meaning-directed and applicationdirected learning. The undirected learning pattern is characterised by an experienced lack of regulation, an ambivalent learning orientation, and a learning conception in which great value is attached to the learning support that fellow students and teachers can provide. This pattern resembles Meyer and Cleary’s (1997) disorganised study orchestration. The reproductiondirected learning pattern is characterised by the use of a surface, stepwise approach to ISSN 0307-5079 print; ISSN 1470-174X online/03/010049-13  2003 Society for Research into Higher Education DOI: 10.1080/0307507032000031127

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J. Vermunt & A. Minnaert TABLE I. Description of ILS-scales

ILS-scale Processing strategies Deep processing

Surface (stepwise) processing

Concrete processing

Regulation strategies Self-regulation External regulation Lack of regulation Learning orientations Certificate directed Vocation oriented Self-test directed Personally interested Ambivalent orientation Learning conceptions Intake of knowledge Construction of knowledge Use of knowledge Stimulating education Co-operation

ILS-subscales; item example

Relating & structuring/Critical processing “I try to discover the similarities and differences between the theories that were dealt with in the course” “I draw my own conclusions on the basis of the data that were presented in the course” Memorising & rehearsing/Analysing “I memorise definitions as exactly as possible” “When I have to study a chapter from a book I will work through that chapter item by item and study each item separately” Concretising & personalising “I try to interpret everyday life events by thinking of the knowledge I had acquired in the course” “After each paragraph I try formulate the learning content in my own words to test my learning progress” “I study according to the instructions given in the study materials or provided by the teacher” “I notice that it is difficult for me to determine whether I master the subject matter sufficiently” “The main goal I pursue in this subject area is to pass exams” “I have chosen this subject area because it prepares me for the type of work I am highly interested in” “I want to prove myself that I am competent of studying in higher education” “I am only studying to enrich myself” “I am afraid this study curriculum is too demanding for me” “To me learning is seeing that I can reproduce the facts presented in the course” “To test my progress, I ought to answer questions that were made up by myself” “To me learning means to acquire knowledge that is applicable in everyday life” “The teacher has to encourage me to put separate elements into a whole” “I prefer to work on assignments in a collaborative manner”

learning (analysing, memorising), an external regulation strategy (letting one’s own learning processes be regulated by external sources), a learning conception in which learning is viewed as the intake of knowledge, and a learning orientation toward testing one’s capabilities and gaining certificates. The use of a deep processing strategy (relating, structuring, critical processing), self-regulation of one’s own learning processes, a learning conception in which learning is seen as constructing one’s own knowledge, and a personally interested learning orientation define the meaning-directed learning pattern. The last two patterns resemble the reproducing and meaning orientations in the work of both Biggs (1987) and Entwistle (1992). The application-directed learning pattern combines an elaborative, concrete approach (concretising, applying), a conception of learning in which the use of knowledge is stressed,

Dissonance in Learning Patterns 51 and a vocational orientation. This resembles the active professional orientation found by Lonka and Lindblom-Yla¨nne (1996). Patterns as described above have been found in several studies with large groups of higher education students. They represent the ‘normal’ patterns that are readily interpretable from a theoretical point of view. Vermunt and Verloop (2000) reviewed studies in which deviating patterns of loadings of ILS scales were found in order to determine whether these patterns could be viewed as indications of dissonance in students’ learning patterns; that is, exhibited disintegrated or non-congruent patterns of relationships among learning components were examined. Five phenomena of dissonance could be identified: lack of differentiation within learning components; lack of integration between learning components; incompatibility of learning strategies, conceptions and orientations; missing learning style elements; and a lack of distinct application-directed learning. Lack of differentiation within learning strategies, learning conceptions and learning orientations means that students do not see the difference between various ways of processing learning materials, different ways of regulating one’s own learning, different views on learning, and various motives for learning. A disintegration between the learning strategies students use and their learning conceptions and orientations means that the learning activities students undertake are not in line with their views on learning and their learning motives and goals. Conception, motive and actions are not congruent. Incompatibility of learning components may mean that opposing forces are working within the same students in their adaptation to the learning environment. The phenomenon of missing elements of learning styles means that some students learn according to a ‘bare’ version of the style and omit essential elements of it. The lack of a clear, distinct application-directed learning style is a phenomenon that is often observed. In most student learning research, this dimension is not recognised as a distinct one, but as an element of meaning-directed learning. Often, however, these studies are done with first year students (Vermunt & Verloop, 2000). Dissonance in student learning, then, may be exhibited as the absence of linkages among learning conceptions, orientations and strategies that theoretically should be there, or as the presence of relationships among these learning components that theoretically should not be there. Learning Patterns in an Innovative, Student-oriented Learning Environment Redesigning the university learning environment in line with the aims of process-oriented instruction runs into a variety of difficulties for teachers as well as for students (see Volet et al., 1995; Vermunt & Verloop, 1999). These difficulties seem almost inherent in educational innovation. They include misconceptions about learning strategies, orientations and conceptions, resistance to change, effort avoidance by students and by their teachers, a lack of long-term policy, a dissonance between curriculum, teaching and assessment, and the educational threshold between secondary and higher education. To evaluate the process of educational innovation towards more process-oriented education (that is, a student-oriented learning environment), fine-grained, longitudinal studies of students’ stability and change in learning patterns are required. The goal of a student-oriented learning environment is to create change in the belief system of students and to cause a change towards a more meaning-oriented approach. From an epistemological point of view, this goal comes into conflict with the presumed and apparent stability of students’ learning ‘styles’. Moreover, this goal may be in disharmony with theoretically congruent learning patterns once ‘incongruent’ or ‘dissonant’ learning patterns emerge due to the aims of educational innovation. The term ‘learning “styles” ’

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stems from a more traditional approach towards learning and refers to habitual, trait-type and style-like learning patterns dealing with components of processing strategies, regulation strategies, learning orientations and mental learning models or epistemologies about learning. Therefore, the generic term of ‘learning patterns’ is used in this study to encompass the different views on the nature and conceptual status of learning styles, learning orientations and learning approaches. Although the modifiability of student learning patterns in higher education is generally agreed upon, these patterns seem quite resistant to change (Busato et al., 1998). Vermetten et al. (1999a) demonstrated that the components of these learning styles do not always appear as relatively stable underlying constructs. In the longitudinal study of Vermetten et al. (1999b), significant changes in learning strategies of first year students between the first and third semester in higher education (within the context of a student-oriented learning environment) were found. Students more frequently reported the use of deep and concrete processing strategies, and self-regulation strategies after the third semester. The belief that learning is the intake of knowledge was less reported after the third semester. Surprisingly, there are few studies that deal with the invariance of factor structures of student learning patterns over time. Vermetten et al. (1999b) compared the pattern matrices of new students and advanced students and found reasonable agreement between the factor solutions. In this research, however, a cross-sectional design was used. Therefore, an appropriate test of factorial invariance was not possible due to differences in cohort characteristics and in the learning context (for example, curriculum, learning goals and teaching qualities). The issue of factorial invariance over time is addressed in the present study in relation to the emergence of dissonant learning patterns. The focus of the present study, then, is on the invariance of, and the dissonance in, student learning patterns within the context of an innovative, student-oriented learning environment, and, in particular, on the degree of ‘fit’ between the theoretically expected patterns and the empirically identified patterns. Three research questions are thus addressed: • Are student learning patterns within the context of a student-oriented learning environment theoretically congruent or not? • Are student learning patterns within the context of a student-oriented learning environment invariant over time? • When do theoretically dissonant learning patterns lead to the revision of theory and when can they be confirmed as being valid? Method Participants and Educational Setting First-year students in the social sciences took part in an innovative, student-oriented learning environment project. These students were confronted with independent learning tasks and individualised task-specific feedback. All university teachers of these students were invited to collaborate in this project. Independent learning tasks were incorporated in a majority of courses during the whole first year and students were required to study a reasonable amount of literature on their own. To guide students’ learning strategies, each of the collaborating teachers formulated tasks, problems and questions related to their own course. These questions or problems were designed to evoke and maximise students’ problem-solving strategies: namely, linking prior knowledge to the problem given, developing search strategies, enhancing goal-oriented selection of information, and evaluating the information in

Dissonance in Learning Patterns 53 accordance to the problem given. Students handed in the product of their learning processes to each of the teachers. The product took the form of a written paper. Some of the teachers provided students with individualised (written and oral) feedback about the task(s), others returned the papers with text-specific feedback and devoted some teaching time to highlight the major or most typical mistakes, pitfalls and shortcomings. Students were told that the marks on their independent learning tasks would not influence the final examination results in either a positive or negative way. The literature remained, however, as obligatory course material. All of the students received personal study advice about their learning strategies, orientations and conceptions immediately after they first completed the Inventory of Learning Styles (Vermunt, 1995). This procedure was crucial because many students fail to estimate appropriately their own learning strategies, orientations and conceptions. The feedback provided students with a more objective estimation of their strengths and weaknesses in their learning patterns. Finally, 244 new students (218 female and 26 male) in the social sciences participated in this research project. In addition, 14 randomly chosen students (13 females and 1 male) were interviewed twice during the academic year (second and third trimester).

Instruments All of the students completed the ILS twice, once in the first and again in the third trimester. The ILS is a 120-item self-report questionnaire, especially developed for utilisation in higher education and has been proven to be a reliable and construct valid diagnostic instrument (see Vermunt, 1998). The questionnaire is a self-report instrument; students are asked to report about their habitual way of learning and beliefs about learning. The ILS generates scales for processing strategies (deep, surface or stepwise, and concrete processing), for regulation strategies (self-regulation, external regulation, and lack of regulation), for learning orientations (certificate directed, vocation oriented, self-test directed, personally interested, and ambivalent orientation), and for learning conceptions (intake of knowledge, construction of knowledge, use of knowledge, stimulating education, and cooperation). The learning strategies items are scored on a five-point Likert scale, ranging from (1) ‘I never or hardly ever did this’ to (5) ‘I (almost) always did this’. For the learning orientations and learning conceptions, scores ranged from (1) ‘I completely disagree’ to (5) ‘I completely agree’.

Design and Procedures In this study, a longitudinal within-subjects research design is used to analyse and interpret student learning patterns over time. Concerning the first research question, separate principal component analyses were performed on the total group of students to compare the theoretically expected learning patterns with the (congruent or dissonant) learning patterns at Time 1 and Time 2. Hence, invariance testing with LISREL (Jo¨reskog & So¨rbom, 1993) was performed to evaluate the invariance of (congruent or dissonant) learning patterns over time. Changes over time in learning strategies, orientations and conceptions are reported by means of within-subject effect sizes. Two ‘regular’ subgroups of students, namely, a group of students with a low profile and one with a high profile of mathematics in secondary education, were analysed separately to identify theoretically (in)congruent learning patterns. To go beyond the actual understanding of the quantitative data, some qualitative data stemming from the in-depth interviews are also considered.

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J. Vermunt & A. Minnaert TABLE II. Varimax-rotated three factor solutions of the ILS-scales for the total group of freshmen by Time* Time 1 ILS-scale (reliability) Processing strategies Deep processing ( ⫽ .85) Surface processing ( ⫽ .72) Concrete processing ( ⫽ .67) Regulation strategies Self-regulation ( ⫽ .79) External regulation ( ⫽ .65) Lack of regulation ( ⫽ .72)

F1

F3

.78

F1

F2

F3

.81 .77

.62

.75

.69

.76

.85 .73

.58 .64

.44

Learning orientations Certificate directed ( ⫽ .69) Vocation oriented ( ⫽ .62) Self-test directed ( ⫽ .83) Personally interested ( ⫽ .52) Ambivalent orientation ( ⫽ .81) Learning conceptions Intake of knowledge ( ⫽ .68) Construction of knowledge ( ⫽ .71) Use of knowledge ( ⫽ .80) Stimulating education ( ⫽ .84) Co-operation ( ⫽ .84) % of variance explained Cumulative %

F2

Time 2

.42 .60

.40 .73 .53

.59 .40 .59

.55

.65 .73

.51

.62

.68

.72 .54 .42 .66 .41 17.16 14.83 14.21 18.25 14.17 12.37 17.16 31.99 46.20 18.25 32.42 44.79

* factor loadings lower than .40 omitted

Results Dissonance in Student Learning Patterns over Time Table II presents the varimax-rotated factor solution of the group of 244 students in social sciences at Times 1 and 2. Based on the scree-test and the proportions of variance explained, three factors were extracted for Time 1 and for Time 2. At Time 1, a meaning-oriented learning pattern (factor 1), a reproduction-oriented learning pattern (factor 2), and an ‘undirected’ learning pattern (factor 3) are in line with theoretical expectations. However, some aspects of dissonance are also present: there is a lack of a distinct application-directed learning pattern, a lack of differentiation in the ‘certificate-directed’ learning orientation (substantial cross-loadings on two factors), and an incompatible ‘self-test-directed’ learning orientation (which was expected to exhibit a substantial loading on the reproduction-oriented instead of on the undirected learning pattern). The factor solution for Time 2 is substantially different in comparison to the one for Time 1, and also so in terms of the theoretically expected pattern. The first factor seems invariant over time and may still be interpreted as a meaning-oriented learning pattern. There is again the lack of a distinct application-directed learning pattern. Factors two and three are not in line with theory or with the factor solution at Time 1. The third factor could be interpreted as a combination of reproduction-oriented features exhibited as an undirected learning pattern comprising surface processing, external regulation, lack of regulation,

Dissonance in Learning Patterns 55 ambivalent learning orientation, and the intake of knowledge as learning conception. The second factor is essentially defined in terms of only learning orientations (‘vocation oriented’, and ‘self-test directed’) and learning conceptions (‘intake of knowledge’, ‘use of knowledge’, ‘stimulating education’, and ‘cooperation’). This dissonant factor fails to exhibit integration with aspects of learning strategies. Within this (second) factor perspective, a female student explains this apparent dissonance during the in-depth interview as follows. All these independent learning tasks and the feedback on these papers are excellent to evaluate yourself so that you know whether you have learnt enough or not … but teacher feedback is insufficient to know how and when to study better. And to be honest, I don’t see how this will improve my work as an educational scientist dealing with mentally retarded children or with children having severe learning problems. Elements of the learning orientations ‘self-test directed’ and ‘vocational oriented’, as well as of the learning conception ‘use of knowledge’ and ‘stimulating education’, are explicitly mentioned by this student. Hence, this second factor is interpreted as a ‘belief’ factor, because it is mainly defined in terms of conceptions or beliefs about learning. Invariance testing with LISREL (Jo¨reskog & So¨rbom, 1993) was then performed to evaluate the invariance of the (dissonant) learning patterns over time. Three competing models concerning the level of invariance were tested (see Table III). The hypothesis of the invariance of variance–covariance matrices across time was not rejected. A goodness-of fit (GFI) value above 0.90, a ratio of chi-square to the number of degrees of freedom of 2 or less, a root mean square error of approximation (RMSEA) of about 0.05 or less and a reasonable probability of a close fit attest to a good fit of the model to the data (Browne & Cudeck, 1993). At this level of statistical interpretation, there seems to be no source of dissonance between Time 1 and Time 2. One might thus erroneously conclude that there are no sources of dissonance across time. It is possible, however, that dissonance may be exhibited at the level of the factor loadings rather than at the global level of differences between the variance–covariance matrices. In this case, testing the hypothesis of invariant factor loading patterns leads to the rejection of the model. The null hypothesis of invariant factor loadings and an invariant factor correlation matrix between the latent factors was also rejected. These findings thus confirm that sources of dissonance between Time 1 and Time 2 are present at the level of the factor loading patterns. In summary, the rejection of the invariance of factor loadings over time and the results of the principal component analyses indicate that student learning patterns were more dissonant in the third trimester (Time 2) than in the first trimester (Time 1). To understand the empirical and theoretical consequences of dissonance over time, two additional sources of information are considered; the first concerns changes over time in the scores on learning strategies, orientations and conceptions, and the second whether the factorial dissonance is also apparent in two ‘normal’ subgroups (instead of a normal and pathological subgroup) of students, e.g. in a group with a low and a high profile of (in this case) mathematics in secondary education. Changes over Time in the Underlying Constructs of Learning Patterns Within the context of a student-oriented learning environment, some changes in learning strategies, learning orientations and learning conceptions were noticed from the first to the third trimester. Changes are reported by means of within-subject effect sizes (d); that is, by the mean difference in scores, divided by the pooled standard deviation of the difference

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J. Vermunt & A. Minnaert TABLE III. Hypotheses of factorial invariance of the ILS-scales over Time

Competing models 1 Equivalence of variancecovariance matrix 2 Pattern of loadings invariant 3 Model 2 ⫹ invariant factor correlation matrix

p of close fit


2

df


2/df

GFI

RMSEA

196.36

136

1.44

.95

.03

.999

973.08 978.54

218 221

4.46 4.43

.80 .80

.09 .08

.000 .000

scores. For the total group of students, increases in ‘deep processing’ (d ⫽ 0.28), ‘concrete processing’ (d ⫽ 0.32) and ‘self-regulation’ (d ⫽ 0.38) are in line with the aims of a studentoriented learning environment; similarly so for decreases in ‘external regulation’ (d ⫽ 0.13), ‘lack of regulation’ (d ⫽ 0.15), and in ‘intake of knowledge’ (d ⫽ 0.29). The increase of ‘surface processing’ (d ⫽ 0.28) is, however, contrary to prior expectations.

Dissonant Patterns Only Restricted to Deviant or Disintegrated Groups of Students? To evaluate whether the factorial dissonance is also apparent in two ‘normal’ subgroups, the data for two groups based on students’ profiles of mathematics in secondary education were analysed separately by means of principal component analysis. Table IV presents the varimax-rotated factor solution of the subgroup of 84 students in social sciences with a low profile of mathematics in secondary education. Based on the scree-test, the proportions of variance explained, and the psychological interpretability of the solution, three factors were extracted both for Time 1 and Time 2. Concerning the solution at Time 1, a meaning-oriented learning pattern (factor 1), an ‘undirected’ learning pattern (factor 2), and a reproduction-oriented learning pattern (factor 3) are—despite some aspects of dissonance—in line with the theoretical expectations. There is a notable lack of a distinct application-directed learning, a lack of common variance of the learning orientation ‘certificate directed’ with one of the learning patterns, an incompatible learning orientation ‘self-test directed’, and a lack of differentiation in the learning conception ‘intake of knowledge’ (substantial loading on two factors). The factor solution for the subgroup of 84 students in social sciences with a low profile of mathematics in secondary education for Time 2 is substantially different compared to the one for Time 1, as well as to the theoretically expected pattern. The first factor (meaning-oriented learning pattern) seems again invariant over time. The second factor (reproduction-oriented learning pattern) is congruent with the third factor in the solution at Time 1. Of note is the missing link of ‘lack of regulation’ with any of the factors. The third factor is of particular interest: this learning pattern is not only dissonant with the solution at Time 1, but also dissonant with theory. The dissonant ‘belief’ factor in this subgroup is equal to the dissonant ‘belief’ factor in the whole group, indicating the presence of dissonant learning patterns in the subgroup of students with a low profile of mathematics. Table V presents the varimax-rotated factor solution of the subgroup of 160 students in social sciences with a high profile of mathematics in secondary education. Based on the scree-test, the proportions of variance explained, and the psychological interpretability of the solution, three factors were once more extracted for Time 1 and Time 2. Concerning the solution at Time 1, the meaning-oriented learning pattern (factor 1) is almost in line with

Dissonance in Learning Patterns 57 TABLE IV. Varimax-rotated three factor solutions of the ILS-scales for the group of freshmen with a weak mathematics curriculum in secondary education by Time* Time 1 ILS-scale Processing strategies Deep processing Surface processing Concrete processing Regulation strategies Self-regulation External regulation Lack of regulation Learning orientations Certificate directed Vocation oriented Self-test directed Personally interested Ambivalent orientation Learning conceptions Intake of knowledge Construction of knowledge Use of knowledge Stimulating education Co-operation % of variance explained Cumulative %

F1

F2

Time 2 F3

.76

F1

F2

F3

.76 .78

.83

.64 .75

.78

.84 .81

.82

.49

.58 .48

.62

.71 .54

.52 .57

.63 .50 .62

.47

.73

.72

.40

15.66 35.92

.67 .54 .61 14.21 50.13

.62 .46

20.55 20.55

.60 .69 18.29 38.84

13.52 52.36

20.26 20.26

* factor loadings lower than .40 omitted

theoretical expectations, but the reproduction-oriented learning pattern (factor 2) and the ‘undirected’ learning pattern (factor 3) reveal many aspects of dissonance. Besides earlier mentioned aspects of dissonance, incompatible learning orientations and learning conceptions with the learning strategies were exhibited (for example, cooperation with surface processing and external regulation). At Time 2, the emergence of the dissonant ‘belief’ factor is striking. The dissonant ‘belief’ factor in this subgroup is neither identical with the dissonant ‘belief’ factor in the whole group, nor with the ‘belief’ factor of the subgroup with a low profile of mathematics. The main point of difference is the mutual exclusive inclusion of the learning conception ‘intake of knowledge’ (total group and low mathematics profile subgroup) or of the conception ‘construction of knowledge’ (high mathematics profile subgroup). One student expressed this belief in her own words: Although I like to work in small groups and to prepare assignments like this, the most crucial thing is to feel for yourself whether you like working in a group, or this group, and whether small group work improves understanding, insight and study effort or not. In summary, these findings indicate the presence of distinct, dissonant learning patterns in the subgroups of students with both a low and a high profile of mathematics in secondary education.

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J. Vermunt & A. Minnaert TABLE V. Varimax-rotated three factor solutions of the ILS-scales for the group of freshmen with a strong mathematics curriculum in secondary education by Time* Time 1 ILS-scale Processing strategies Deep processing Surface processing Concrete processing Regulation strategies Self-regulation External regulation Lack of regulation Learning orientations Certificate directed Vocation oriented Self-test directed Personally interested Ambivalent orientation Learning conceptions Intake of knowledge Construction of knowledge Use of knowledge Stimulating education Co-operation % of variance explained Cumulative %

F1

F2

Time 2 F3

.83

F1

F2

.79 .44

.66

.66

.63

.86

.82 .44

.42 .76 .44 .69 .49

.54 .41 .65 .50 .41

.80

.75 .64

.68 .44 15.82 33.61

.41

.48

.68 .73

17.79 17.79

F3

10.38 43.99

17.03 17.03

16.32 33.35

.42 .47 .60 .67 12.01 45.36

* factor loadings lower than .40 omitted

Conclusion and Discussion In focusing on theoretically incongruent patterns of learning the present study addressed three research questions: • Are student learning patterns within the context of a student-oriented learning environment theoretically congruent or not? • Are student learning patterns within the context of a student-oriented learning environment invariant over time? • When do theoretically dissonant learning patterns indicate a fine-tuning of theory and when do they represent valid dissonance? A longitudinal within-subject study was carried out among first year university students in a student-oriented learning environment. To assess students’ learning strategies, learning orientations, and learning conceptions, the Inventory of Learning Styles was administered in the first (Time 1) and in the third trimester (Time 2). Students’ learning patterns in the third trimester were far more dissonant than in the first trimester. The longitudinal data for the group of students with low and high profiles of mathematics in secondary education were analysed separately. Both groups showed learning patterns dissonant from theory, especially in the relations between orientations and conceptions on the one hand and learning strategies on the other hand. At Time 2, an interesting finding was the emergence of a dissonant ‘belief’ factor comprising learning conceptions and orientations that were not associated with learning strategies—a finding that begs further theoretical consideration.

Dissonance in Learning Patterns 59 In the present study, substantial changes in students’ learning patterns within the first year of higher education were found. Congruent with the longitudinal results of Vermetten et al. (1999a), a substantial increase in learning strategies such as deep processing, concrete processing and self-regulation was found, as well as a decrease in the learning conception in which learning is viewed as the intake of knowledge. Given the goals of a more studentoriented learning environment, these results are promising. The presence, however, of so many distinct phenomena of dissonance necessitates the need for educational guidance and counselling to overcome dissonance. Although gender differences were beyond the scope of this study (due to the low frequency of male students in this project), studies have brought to the fore the presence of gender-related differences in learning patterns in higher education (Severiens & Ten Dam, 1996; Minnaert, 1999). Studies by Meyer et al. (1994) and Meyer (1995) were among the first to examine invariance of correlation structure across gender. Much previous work has focused on gender in location terms, i.e. mean scale scores. Meyer (1995) showed that a common set of items produced variation within the gender groups that was different between the groups in terms of both correlation and covariance structure. He argued that we should construct gender-sensitive models of student learning. Minnaert (1999) found differences not only with respect to single variables (e.g. female students reported significantly more strategic learning strategies and external regulation strategies than male students), but also with respect to patterns of relationships between learning variables. Differences were also found with respect to facilitating and inhibiting effects of motivational aspects on the use of learning strategies (fear of failure played a more detrimental role on self-regulatory strategies for female students than for male students). Gender differences with respect to perceptions of and beliefs about the learning context may well provide a more thorough understanding of learning patterns dissonant from theory. There are no other studies that we know of that looked at dissonance in gender terms and this is clearly an underexplored research question. The important point here is that dissonance emerges in structural terms as well as location parameters, but it is the former, given the aforementioned work that reports gender-based structural differences, that may help us explain some of the variation in dissonance. One specific dissonant pattern found in the present study was the ‘belief’ factor, characterised by high loadings of almost all learning conceptions and two learning orientations, and the absence of loadings from learning strategies in the third semester. A similar factor is reported by Ajisuksmo and Vermunt (1999) in a study based on Indonesian university students; a factor that they interpreted as a ‘passive-idealistic learning pattern’. Boekaerts et al. (1997) have also found strong forms of this lack of integration between conceptions and strategies among junior secondary school students. Given the fact that most studies among university students show strong relations between learning conceptions, orientations and strategy use, Vermunt and Verloop (2000) suggest that these results may point towards a developmental phenomenon: as learners become more experienced, there is a progressive integration of their learning conceptions, orientations and strategies. In other words, what people do to learn converges with their views about, and motives for, learning. And there may be cultural differences in the interrelations between these learning components. In this study, students coming from secondary education and entering university at first showed learning patterns similar to those that are usually found. Then, after three semesters of an innovative, student-oriented way of teaching, they showed much more dissonance in their learning patterns. It is known from other studies that, when students stay in a familiar and stable learning environment, the integration between their learning components usually increases (see, for example, Vermetten et al., 1999b). Does this theory now require revision? Perhaps the findings of the present study can be explained as follows. Students coming

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J. Vermunt & A. Minnaert

from traditional secondary education experienced a period of friction between their learning conceptions, orientations and strategies and those that this innovative, student-oriented type of teaching tried to foster (Vermunt & Verloop, 1999). In this situation, there is pressure on students to change their learning patterns in a more constructive direction. However, perhaps not all learning components change at the same time or at the same rate. It is quite possible that at first students begin to question their beliefs about learning and the task division between students and teachers in student-oriented education, at the same time behaving in the same way that they are used to do. Their crystallised learning conceptions become less clear, and there is a period of relative confusion in which the linkage between thoughts and actions is less strong. Once this period of confusion passes and there is again a clear differentiation between different learning conceptions, learning strategies may follow a similar development, and the linkages between conceptions and strategy use strengthen. If this is true, the period of dissonance may be very adaptive and necessary for change and growth as a learner. If this is the case, a revision of theory is called for. The phenomenon described above is no longer a dissonant phenomenon in the sense of deviation from normality, but what has been obviously missing in our theory; namely, an account of how learning patterns may develop and change over time. Disentangling views and actions may be a necessary condition for change and development, and the different learning components may change at different moments and at different rates. The period of dissonance that is possibly induced by these developments is normal, adaptive and necessary. Once the theory has been revised in this way, the phenomenon of dissonance, or at least some otherwise disturbing aspects of it, become part of the theory rather than something outside it. Correspondence: Jan Vermunt, Leiden University, ICLON – Graduate School of Education, PO Box 9555, NL-2300 RB Leiden, the Netherlands; e-mail: [email protected]

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