the parleunet-project: problems with the validation of socio-constructivist design principles in...

The ParlEuNet-project: problems with thevalidation of socio-constructivist design

principles in ecological settings

Geraldine Clarebout*, Jan Elen

Centre for Instructional Psychology and Technology, University of Leuven, p/a Naamsestraat 98,

B-3000 Leuven, Belgium

Abstract

Current proposals for the design of technologically supported learning environments areheavily influenced by socio-constructivist ideas about learning and instruction. While

numerous general ideas have been brought forward, there is a lack of clear empirical tests ofthese ideas. In this contribution such an empirical test is presented and discussed. First, theinstructional design principles and their operationalisation in the ParlEuNet-project are

presented. Next, the design and outcomes of an empirical study are discussed. It washypothesised that students’ epistemological beliefs, metacognitive skills and instructionalbeliefs would evolve by working in a rich technological, problem-based collaborative learn-

ing environment. Secondly, it was hypothesised that by participating in the project, students’beliefs and skills would develop in the direction of that learning environment. The firsthypothesis was partly confirmed; however the second was not, students’ beliefs and skillschanged in a direction opposite to the one expected. The contribution concludes with an

attempt to explain these unexpected results. # 2001 Elsevier Science Ltd. All rights reserved.

1. Introduction

Instructional design aims at generating indications about optimal relationshipsbetween learner-related and instruction-related variables in view of the attainmentof instructional and/or learning goals. In instructional design research at least two

Computers in Human Behavior 17 (2001) 453–464

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* Corresponding author. Tel.: +32-16-326550; fax: +32-16-326542.

E-mail addresses: [email protected] (G. Clarebout), [email protected].

ac.be (J. Elen).

approaches can be identified (Elen, 1999). A first approach starts with some funda-mental ideas about learning and instruction. These ideas are translated into designprinciples, which are then used to actually design and develop a concrete learningenvironment. An investigation of such an environment provides some evidenceabout the validity of the principles and indirectly about the theoretical ideas theseprinciples are derived from. A second approach does not take theoretical principlesas a starting point but actual activities in concrete settings. The effects of concretelearning environments are studied and gradually some more overarching principlesare generated. Finally, corroboration of these principles is looked for in funda-mental theories about learning and instruction. Whereas the first approach addres-ses the theory-practice gap from a theoretical vantage point, the second approachtakes actual practice as its starting point.

In this contribution, a study is presented in which the first approach was adopted.Starting from socio-constructivist ideas about learning and instruction, a number ofdesign principles were identified. These principles were used, as part of the ParlEu-Net-project, to design and develop a concrete and innovative learning environment.In addition to anecdotal evidence about the implementation of the learning envir-onment in an ecological setting, a survey-study was carried out as well to investigatethe effects more systematically.

2. The ParlEuNet-project, an instantiation of socio-constructivist design principles

Current literature on learning and instruction stresses the socio-constructivistnature of learning. The theoretical premise that learners, being at the core of theirown learning processes, construct their own knowledge in interaction with an envir-onment that is primarily socio-cultural (Billet, 1996), has important consequencesfor the selection of learning tasks and for the role of both learners and instructors.This theoretical vantage point highlights the importance of a number of designprinciples that all aim at implementing a student-centred learning environment.

1. A socio-constructivist learning environment aims at encouraging students todevelop higher-order reasoning skills rather than the memorisation of facts. Inview of this goal, learners are by preference confronted with authentic ill-structured tasks. In order to solve this kind of problem or, in other words, toreach adequate solutions, learners have to investigate the problem or learningtask from different perspectives (Spiro, Feltovich, Jacobson, & Coulson, 1988).The authenticity of the task is required as to ensure learners to be sufficientlymotivated and to increase the probability that learning results can also beapplied in real life.

2. In a socio-constructivist environment, the primary role of the teacher is to actas a facilitator of the learning process. The teacher is no longer the lecturerwho distributes knowledge and wisdom but a preferential interlocutor for thelearners. The facilitation of the learning process implies the use of a variety ofinstructional methods such as modelling, coaching and scaffolding (Jonassen,

454 G. Clarebout, J. Elen /Computers in Human Behavior 17 (2001) 453–464

1996; Mandl & Prenzel, 1991; Roblyer, Edwards, & Havriluk, 1997). Supportis directed not only towards the acquisition of domain-specific knowledge butalso towards the development of motivation and metacognition.

3. The learner, from a socio-constructivist perspective, is no longer a passive lis-tener, but the main actor in the learning environment. The kind of activitiesexecuted by a learner determines what is learned by the learner (Pressley, Bor-kowski, & Schneider, 1989; Simons, 1990; Snow & Swanson, 1992). Whichactivities the learner is able and/or willing to engage in and whether they areactually directed towards the instructional goals, depend on a variety of lear-ner-related variables such as prior knowledge and motivation.

4. A purely technology-driven approach has never been found to be successful(Clark, 1994; Clark & Sugrue, 1990). In a socio-constructivist learning envir-onment information and communication technologies (ICT) are used as aproblem-solving tool to solve a learning task. More precisely, it offers possibi-lities for broadening the concept of knowledge construction. It enables accessto information and communication with peers spread all over the world.Moreover, ICT can help to bring about some help to execute the learningtasks.

5. Given the assertion that learning implies interaction with a socio-culturalenvironment, the importance of collaborative learning is self-evident. Commu-nication while collaborating helps to make learners’ thoughts explicit and to getin contact with a variety of perspectives. Through collaborative learning, lear-ners broaden their horizon, are induced to consider various perspectives and areconfronted with new cognitive and metacognitive strategies (Schunk, 1991).

In line with specifications for instructional design research (Elen, 1994, 1995), aunique learning environment was designed and developed in the ParlEuNet-projectby considering the specific referent system. The learning environment was the resultof systematically applying the previously mentioned principles to the referent sys-tem. Snow and Swanson (1992) proposed a framework for describing such a referentsystem. Using this framework the main features the ParlEuNet-learning environ-ment can be described as follows (for a detailed description: see Elen & Clarebout,1998):

1. Rich technological environment: learners have access to a wide variety ofinformation and communication tools. Learners have free access to the Inter-net, printer, scanner, and a dedicated database as information tools and e-mail,telephone, fax, videoconferencing, and a dedicated tool to exchange documentsas communication tools.

2. The content in the ParlEuNet project is not linked to a specific discipline. Thecontent relates to a multidisciplinary problem area. Learners get an open task.Together with peers they have to prepare a policy document on mobility for amember of the European Parliament.

3. Learning in the ParlEuNet-project occurs in a problem-based and collaborativeenvironment. Students acquire knowledge while engaging in problem-solving

G. Clarebout, J. Elen /Computers in Human Behavior 17 (2001) 453–464 455

processes. Moreover, learning is not a solitary action but the outcome of acollaborative effort.

4. Learners collaborate with some peers from their own school and throughmeans of ICT with groups of peers from schools in two other countries.

5. Learners are secondary school pupils between 15 and 17 years old from fivedifferent European countries. These students are used to a traditional instruc-tional approach with a teacher standing in front of the class and deliveringinformation to the students either directly or through interactive discussionswith the students.

3. Effect of the implementation of the I.D.-model on learner characteristics

Innovative learning environments are designed and implemented because they aresupposed to better fit the actual learning needs and to result in valued learning out-comes. In addition to the acquisition of domain knowledge, the development ofappropriate epistemological beliefs (Schommer, 1994), instructional beliefs (Elen &Lowyck, 1999) and metacognitive strategies (Shuell, 1992) is currently also favouredand aimed at. All different types of outcomes are regarded to be important in aknowledge intensive society. Pupils need to value ICT and collaborative learning, tohave sophisticated epistemological beliefs and well-trained metacognitive strategies.These beliefs and skills will enable them to remain flexible and keep pace with tech-nological and scientific developments.

In the study presented here the effects of the ParlEuNet-environment on domainknowledge, epistemological beliefs, instructional beliefs and metacognitive strategieswere investigated. As a first hypothesis all these student characteristics were expec-ted to change after the project. Moreover, a second hypothesis was tested, namelythat beliefs of students would develop in the direction of the learning environment,i.e. students’ beliefs would become more favourable to problem-solving approachesand collaboration, and that metacognitive strategies get fostered by this environ-ment. Finally, it was also expected that students would acquire specific task-relatedknowledge.

3.1. Research design

Six schools participated (n=124). They were split in two groups of three schoolsthat worked independently. All students worked in small groups of six within theirclassroom and collaborated with two other groups from two other countries. After 8weeks, working 4 h a week on the project, each group of 18 students were expectedto deliver one integrated policy document.

A classical pre-test, post-test design was used. A questionnaire was administeredright before the start of the project and immediately after. It consisted of 12 ques-tions on epistemological beliefs, 20 questions on instructional beliefs (eight aboutproblem-based collaboration, 12 about the technology), eight questions on meta-cognitive strategies, and 16 task-related knowledge questions.


For assessing epistemological beliefs, an existing questionnaire (Schommer, 1990)was used. Schommer herself was asked to select the 12 most relevant items out of the63 items-long original questionnaire. As Schommer identifies four categories,namely (1) certain knowledge, (2) fixed ability, (3) simple knowledge, and (4) quicklearning, she was asked to select three questions for each category.

Instructional beliefs and metacognitive strategies were investigated with a newlyconstructed instrument. For the instructional beliefs the main aspects of the newlearning environment (e.g. problem-based learning, use of technology) were taken toconstruct items. Inspired by relevant literature (Corno & Mandinach, 1983; Shuell,1992; Vermunt, 1992) four main categories were chosen to measure metacognitivestrategies: (1) orientation and planning, (2) correction, (3) reflection, and (4) self-feedback.

For all new constructed questions a counter question was provided and a four-point uni-polar Likert-type scale was used. For the epistemological beliefs the ori-ginal scale was taken, which is a five-point bi-polar Likert-type scale.

For the questions addressing task-related knowledge, official publications fromthe European Parliament and the European Union (http://europa.int.eu) were used.

3.2. Analysis

Data analysis started with a test of normality that revealed normal distribution forall questions. Next, a principal component analysis was performed to identify thenumbers of components. Based on these results a factor analysis was done with apre-specified number of factors. The results of this factor analysis were used toconstruct scales (see also Clarebout & Elen, 1999; Clarebout, Elen, & Lowyck,2000). Only items with loadings >|0.50| and loading on one factor only were con-sidered. Items with a negative factor load were recoded (e.g. from 1=totally dis-agree to 5=totally agree). For the task-related knowledge questions a scale wasconstructed by summing the correct answers to the different questions, resulting in amaximum score of 16. In a third step, the resulting scales were used in a repeatedmeasurement analysis of variance to identify significant differences between pre- andpost-test for the different dependent variables (epistemological and instructionalbeliefs, metacognitive skills). School group was also included in this analysis as abetween subjects factor. For the knowledge questions, a univariate analysis of var-iance was done, as not exactly the same questions were asked in the post-test.

All analysis were performed with the statistical package for the social sciences(SPSS#8).

3.3. Results

In this section, results are described. First, instructional beliefs are discussedwhich pertain to problem-based collaboration and the use of technology. Next,epistemological beliefs are addressed. The results section is completed by the pre-sentation of the results with respect to metacognitive strategies and task-relatedknowledge.


3.3.1. Instructional beliefs3.3.1.1. Instructional beliefs about problem-based collaboration. Principal componentanalysis revealed a one component solution (eigenvalue >1; inspection of the screeplot) explaining 43.33% of the total variance. A factor analysis, presupposing onefactor, resulted in five items, loading |0.50|. A scale was constructed with these itemsand labelled ‘perceived efficiency and attractiveness of problem-based collabora-tion’. The reliability of the resulting scale (Cronbach Alpha) is 0.82.

Overall, looking at the differences between the pre- and post-test and schoolgroup, it can be seen that both groups believe that problem-based collaboration isefficient with relation to the learning process and makes learning exciting (Table 1).

A decrease can be noticed for the score on the post-test. A repeated measurementanalysis of variance reveals this decrease to be significant (l=0.86, F(1,102)=16.77,p=0.00). No significant differences were found for school group.

These results show that the first hypothesis is confirmed. Indeed, students’ beliefschange after the project. However, the second hypothesis is not confirmed, thedirection of change is opposite to what was expected. It was expected that studentswould believe more in the efficiency of a problem-based collaborative learningenvironment.

3.3.1.2. Instructional beliefs about technology. Principal component analysis revealeda three component solution (eigenvalue >1). However, after inspection of the screeplot a one component solution that explains 37.42% of the total variance was optedfor. A factor analysis with a pre-specified factor resulted in seven items loading>|0.50| (n=7) a scale was constructed with a reliability (Cronbach Alpha) of 0.85,and labelled ‘perceived instructional power of technology’.

In Table 2, an overview is given of the different means of students on the scale forinstructional beliefs about technology. It can be seen that overall students believe inthe instructional power of technology.

Repeated measurement analysis of variance indicates, in addition to an interactioneffect of school group and test [l=00.88, F(1,94)=16.95, p=0.00 (Fig. 1)], maineffects for test [l=0.88, F(1,94)=13.17, p=0.00] and for school group[F(1,94)=6.72, p=0.01].

Table 1

Means for instructional beliefs about problem-based collaboration

Test School group (n) Mean (S.D.)

Pre-test 1 (43) 3.16 (0.65)

2 (59) 3.19 (0.47)

Total (102) 3.18 (0.55)

Post-test 1 (43) 2.96 (0.67)

2 (59) 3.10 (0.48)

Total (102) 3.04 (0.57)


From Fig. 1, it can be seen that it is especially school group 1 whose belief changesmostly after the project. In comparison to school group 2, this group believes sig-nificantly less in the instructional power of technology after the project.

3.3.1.3. Epistemological beliefs. Considering the underlying latent variables identi-fied by Schommer, a factor analysis was performed for the questions on epistemo-logical beliefs. The items corresponding with the four factors were different from theones identified by Schommer. Therefore, a principal component analysis was per-formed, which revealed four components (eigenvalue >1-criteria; inspection of thescree plot) explaining 54.44% of the total variance. Factor analysis with four factorsresulted in three remaining items loading >|0.50| on only two factors. These itemswere used to construct scales. A first scale, containing two items, was labelled ‘truthfor scientist’. The second scale, containing only one item, was labelled ‘effort pays’.The reliability of the scale was 0.56. For the second scale, a reliability test could notbe done as this scale contained one item only.

In general it can be noticed that the average student does not believe in truth forscientist, but does believe in the necessity of effort to learning (Table 3).

Repeated measurement analyses of variance for ‘truth for scientist’ revealed nosignificant difference between the pre- and post-test, nor between the two school

Table 2

Means for instructional beliefs about technology


Pre-test 1 (44) 3.41 (0.59)

2 (52) 3.48 (0.49)

Total (96) 3.45 (0.54)

Post-test 1 (44) 3.02 (0.67)

2 (52) 3.50 (0.53)

Total (96) 3.28 (0.64)

Fig. 1. Interaction effect for test and school group with relation to instructional beliefs about technology.


groups. For ‘effort pays’ a significant difference is found between the scores on thepre- and the post-test [l=0.94, F(1,107)=6.35, p=0.01]. This means that students’belief about the necessity of effort to learn something is significantly weakened.

This means that only for one scale of epistemological beliefs the first hypothesiswas confirmed, students belief in the necessity of work has changed after the project,however in a direction opposite to the one expected.

3.3.1.4. Metacognitive strategies. Principal component analysis revealed a one-com-ponent solution (eigenvalue >1-criterion; inspection of scree plot). They explainonly 38.24% of the total variance. The consecutive factor analysis with one factorresulted in three items. The scale was labelled ‘reflection’. The reliability (CronbachAlpha) of this scale was 0.62.

The descriptives in Table 4 show that in general students usually reflect on theirlearning activities while working on a task. Repeated measurement analysis of var-iance reveals no significant difference between the pre- and post-test for this scale.

Table 3

Means for epistemological beliefs

Scale Test School group (n) Mean (S.D.)

Truth Pre-test 1 (42) 2.83 (0.95)

2 (55) 2.77 (0.89)

Total (97) 2.80 (0.91)

Post-test 1 (42) 2.71 (0.98)

2 (55) 2.51 (0.86)

Total (97) 2.79 (0.91)

Effort Pre-test 1 (45) 3.96 (0.95)

2 (64) 3.81 (0.85)

Total (109) 3.87 (0.89)

Post-test 1 (45) 3.69 (1.10)

2 (64) 3.53 (0.93)

Total (109) 3.60 (1.00)

Table 4

Means for metacognitive skills

Scale Test School group (n) Mean (S.D.)

Reflection Pre-test 1 (44) 2.88 (0.61)

2 (61) 2.79 (0.64)

Total (105) 2.83 (0.63)

Post-test 1 (44) 2.83 (0.64)

2 (61) 2.69 (0.66)

Total (105) 2.75 (0.65)


3.3.1.5. Task related knowledge. From Table 5 it can be seen that the average stu-dent performs poorly on the knowledge test. The average score on the knowledgetest does not reach seven, while the maximum score is 16.

Analysis of variance showed no interaction effects. However, a main effect for testwas found [F(1,242)=57.83; p=0.00]. Students’ task-related knowledge decreasesfrom 6.73 to 4.78 after participation in the project.

4. Discussion and conclusion

The outcomes of the empirical test of socio-constructivist design principles showthat introducing a problem-based, collaborative and rich technological learningenvironment does result in changing various indicators of students’ learning.Instructional beliefs, some epistemological beliefs and students’ task-related knowl-edge have changed after the project. It can be concluded therefore that the firsthypothesis is confirmed. After participating in the project students’ belief in thepower of problem-based collaborative learning environments has changed. A similarresult was found for one school group for instructional beliefs about technology.With respect to epistemological beliefs, students’ ideas about the necessity of effortalso change. Finally, students’ task-related knowledge is also affected.

In contrast to the first hypothesis, the second one is not confirmed. The beliefs ofstudents and their metacognitive skills changed in the opposite direction thanhypothesised. Instead of becoming more in line with design principles that underpinthe environment, opposing beliefs seem to get fostered.

An explanation of these results can be looked for at various levels. For instance,some methodological comments could be made. It has already been indicated, forinstance, that some of the scales used in this research have a relatively low reliability.An intensive pre-testing of the questionnaire and constructive adaptations mighthave solved this problem (Ornstein, 1998). The low reliability of some scales mayresult in questioning the results themselves.

However, while certain scales do have a limited reliability and for some variablesno effect has been found, this study has also revealed a number of reliable outcomes.They all point towards contradicting the second hypothesis and, hence, call for a

Table 5

Means for the knowledge test


Pre-test 1 (57) 6.65 (1.86)

2 (66) 6.80 (2.04)

Total (123) 6.73 (1.95)

Post-test 1 (66) 4.42 (2.04)

2 (68) 5.04 (2.01)

Total (134) 4.73 (2.03)


more in-depth analysis in view of the elaboration of design specifications. Twopositions can be taken to look for these underlying reasons. First, it could be saidthat something went wrong with the design and implementation of the environment.However, with relation to the design aspect, it seems difficult to argue that theproblems stem from an inadequate translation of fundamental conceptionsabout learning and instruction of socio-constructivism. On the contrary, socio-constructivist ideas were systematically applied while designing a problem-based,collaborative and rich technological environment. The environment as designed alsoprovided learners with opportunities to construct meaning while collaborativelyworking on an authentic task. Therefore, and in this line of thinking, the problemmost probably relates to the implementation of the designed environment. Indeed,anecdotal evidence suggests that the environment was not implemented as designed.First, not all technological tools functioned adequately, students could not getaccess to a dedicated database, which was the main information resource, and stu-dents could not easily e-mail with one another although a specific e-mail tool wasprovided. Moreover and in spite of teacher training, teachers who had to facilitatestudents by encouraging them to use their metacognitive skills, experienced difficul-ties in doing so. Teachers tried to solve all kinds of technical problems and did notreally know how to deal with a situation in which they were not in control, forexample in which students could access a wide variety of information. On top ofthis, the member of the European Parliament, who had to give the incentive forstudents to work on the task, and who made it an authentically realistic task, did notshow any recognition for the work of the students. Given these observations, itremains doubtful to formulate firm conclusions on the second hypotheses and cer-tainly on the validity of socio-constructivist design principles. One might even arguethat students’ beliefs did change in the direction of the environment, be it theimplemented environment and not the designed one.

Taking an alternative position, the complexity of the socio-constructivist learningenvironment in itself could be argued to have provoked the results. The socio-constructivist environment in which students were confronted might have been toocomplex to be handled constructively. Overall, students and teachers are used toworking in a traditional class situation. In the project, they got confronted with avariety of innovative elements (new technology, international collaborative work,etc.). Working on an ill-structured task in a completely different learning environ-ment than they were used to, might have made the task too difficult to deal with.This can be related to the curvi-linear relationship between task-difficulty andmotivation (Atkinson & Feather, 1966). When a task is either too easy or too diffi-cult, motivation decreases. Some of the changes found in this study, might reflectmotivational changes.

In the introduction, it has been highlighted that in this study a classical approachto instructional design was adopted. In line with such an approach the ParlEuNet-project aimed at testing design principles in an ecological setting. This approach hasnot been successful here. The outcomes highlight therefore the need for reconsider-ing this classic approach. Theoretically derived design principles commonly con-stitute a coherent whole. The underlying theories, however, are always limited in


scope. An ecological setting, on the other hand, is encompassing but often inco-herent. This makes pre-testing research instruments in similar situations as the targetsituation also very difficult.

In retrospect, it seems that any attempt to directly test theoretically derived designprinciples in an ecological setting is doomed to fail unless such a setting can be suf-ficiently controlled. This, however, would require more insight into the variables andtheir interrelations that are relevant with respect to promoting learning. How tosolve this dilemma is probably the great challenge for upcoming instructional designresearch.

Acknowledgements

Part of this research is sponsored by the European Commission ‘Targeted socio-economic research’, Directorate General XII, Science research and development,Directorate G, as part of the Joint Call for Educational Multimedia under contractnumber MM1022.

References

Atkinson, J. W., & Feather, N. T. (1966). A theory of achievement motivation. New York: Wiley.

Billet, S. (1996). Situated learning: bridging sociocultural and cognitive theorising. Learning and Instruc-

tion, 6(3), 263–280.

Clarebout, G., Elen, J., & Lowyck, J. (2000). Challenged by reality. Leuven: K.U.Leuven, C.I.P.&T.

Clarebout, G., & Elen, J. (1999). Surveys. In G. Clarebout, & J. Elen (Eds.), When instruments get con-

fused. Report on the methodology used in the experimentation phase of the ParlEuNet project. Leuven:

K.U.Leuven, C.I.P.&T.

Clark, R. E. (1994). Media will never influence learning. Educational Technology Research and Develop-

ment, 42(2), 21–29.

Clark, R. E., & Sugrue, B. M. (1990). North American disputes about research on learning from media.

International Journal of Educational Research, 14, 507–520.

Corno, L., & Mandinach, E. B. (1983). The role of cognitive engagement in classroom learning and

motivation. Educational Psychologist, 18(2), 88–108.

Elen, J. (1994). A framework for I.D.-research. In J. Lowyck, & J. Elen (Eds.), Modelling I.D.-research

(Proceedings of the first Workshop of the Special Interest Group on Instructional Design of EARLI)

(pp. 1–20). Leuven: K.U.Leuven.

Elen, J. (1995). Blocks on the road to instructional design prescriptions. Leuven: Leuven University Press.

Elen, J. (1999). Emergent practices in instructional design: a discussion. In J. Bustraan, & C. Terlouw

(Eds.), Systematic analysis of and reflection on ‘‘emergent practices of instructional design’’ (pp. 3–7).

Leiden: Plato.

Elen, J., & Clarebout, G. (1998). Learning about the European Parliament. Collaboration, problem-solving

and support in rich technological environments. Leuven: Centre for Instructional Psychology and

Technology.

Elen, J., & Lowyck, J. (1999). Metacognitive instructional knowledge: cognitive mediation and instruc-

tional design. Journal of Structured Learning and Intelligence System, 13(3-4), 145–169.

Jonassen, D. H. (1996). Computers in the classroom: mindtools for critical thinking. Englewood Cliffs, NJ:

Prentice Hall.

Mandl, H., & Prenzel, M. (1991). Designing powerful learning environments. A constructivist perspective.

In J. Lowyck, P. De Potter, & J. Elen (Eds.), Instructional design: implementation issues (Proceedings of

the I.B.M./K.U.Leuven Conference) (pp. 69–90). La Hulpe/Leuven: IBM/K.U.Leuven.


Ornstein, M. (1998). Questionnaire design. Current sociology, 46(4), 4–47.

Pressley, M., Borkowski, J. G., & Schneider, W. (1989). Good information processing: what it is and how

education can promote it. International Journal of Educational Research, 13, 857–867.

Roblyer, M. D., Edwards, J., & Havriluk, M. A. (1997). Integrating educational technology into teaching.

Upper Saddle River, NJ: Prentice-Hall.

Schommer, M. (1990). Effect of beliefs about the nature of knowledge and comprehension. Journal of

Educational Psychology, 85(3), 406–411.

Schommer, M. (1994). An emerging conceptualization of epistemological beliefs and their role in learning.

In R. Garner, & P. A. Alexander (Eds.), Beliefs about text and instruction with text (pp. 25–40). Hills-

dale, NJ: Erlbaum Associates.

Schunk, D. H. (1991). Learning theories: an educational perspective. New York: Merrill.

Shuell, T. J. (1992). Designing instructional computing systems for meaningful learning. In M. Jones, &

P. H. Winne (Eds.), Adaptive learning environments. Foundations and frontiers (NATO-ASI Series,

Series F: Computer and Systems Sciences 85 (pp. 19–54). Berlin: Springer-Verlag.

Simons, P. R. (1990). Transfervermogen (Rede uitgesproken bij de aanvaarding van de ambt van gewoon

hoogleraar in de interdisciplinaire onderwijskunde, in het bijzonder de onderwijsverbetering). Nijmegen:

Katholieke Universiteit Nijmegen.

Snow, R. E., & Swanson, J. (1992). Instructional psychology: aptitude, adaptation, and assessment.

Annual Review of Psychology, 43, 583–626.

Spiro, R. J., Feltovich, P. J., Jacobson, M. J., Coulson, R. L. (1988). Cognitive flexibility theory:

advanced knowledge acquisition theory in ill-structured domains. In Tenth annual conference of the

cognitive society (pp. 375–383). Hillsdale, NJ: Erlbaum Associates.

Vermunt, J. (1992). Leerstijlen en het sturen van leerprocessen in het Hoger Onderwijs: Naar procesgerichte

instructie en zelfstandig denken [Learning styles and coaching learning processes in higher education:

towards process-oriented instruction and autonomous thinking]. Doctoral dissertation, Katholieke

Universiteit Brabant. Lisse: Swets & Zeitlinger.


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