Abstract
For promoting the development of students’ problem representations by collaborative design the learning activity for the network-based synchronous environment Collaborative Virtual Workplace was designed. Two biology and chemistry related problem situations were presented to 21 biology and 18 chemistry class students of different schools. Students’ activity was scaffolded by an online tutor. The analogous problem situation was solved individually in the pre- and post-test. The process of design on whiteboard tool and the textual conversation on chat tool were recorded and the content was analysed from log-files. Based on the individuals’ external problem representations and the interactions recorded on whiteboards, the theoretical framework for the analysis of problem representations in science was created. According to this, the development of students’ problem representations must be supported on the dimensions of the ontological “objects” and “events” category components of mental models at the levels of everyday, scientific and scientific symbolic explanations. It was found that the collaborative modelling activity in the synchronous network environment caused the shift in students’ individual problem representations towards more complete and scientifically valid mental models.
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References
Chi, M. T. H. (1992). Conceptual change within and across ontological categories: Examples from learning and discovery in science. In R. Giere (Ed.), Cognitive models of science. Minnesota Studies in Philosophy of Science, 15, (pp. 129–187). Minneapolis: University of Minnesota Press.
Chi, M. T. H., Slotta, J. D., deLeeuw, N. (1994). From things to processes: A theory of conceptual change for learning science concepts. Learning and Instruction, 4, 27–43.
Chi, M. T. H. (1997). Creativity: Shifting across ontological categories flexibly. In T. B. Ward, S. M. Smith, J. Vaid (Eds.), Creative thought: An investigation of conceptual structures and processes (pp. 209–234). Washington, DC: American Psychological Association.
Derry, S. J. (1996). Cognitive schema theory in the constructivist debate. Educational Psychologist, 31(3/4), 163–174.
Johnson-Laird, P. N. (1983). Mental models: Towards a cognitive science of language, inference, and consciousness. Cambridge: Cambridge University Press; Cambridge, MA: Harvard University Press.
Johnstone, A. H. (1991). Why is science difficult to learn? Things are seldom what they seem. Journal of Computer Assisted Learning, 7, 75–83.
Jonassen, D. (1995). Operationalizing mental models: Strategies for assessing mental models to support meaningful learning and design-supportive learning environments. In J. L. Schnase & E. L. Cunnius, (Eds.), Proceedings of CSCL’ 95 (pp. 182-186).
Mortimer, E. (1995). Conceptual change or conceptual profile change? Science and Education, 4, 267–285.
Niedderer, H., Goldberg, F., Duit, R. (1991). Towards learning process studies: A review of the Workshop on Research in Physics Learning. In R. Duit, F. Goldberg & H. Niedderer (Eds.), Research in Physics Learning: Theoretical Issues and Empirical Studies (pp. 10-28). IPN, Kiel.
Norman, D. A. (1983). Some observations on mental models. In D. Gentner & A. L. Stevens (Eds.), Mental Models (pp. 7–14). Hillsdale, New Jersey: Erlbaum.
Paivio, A. (1986). Mental representations: a dual coding approach. New York, NY: Oxford University Press.
Pressley, M., Hogan, K., Wharton-McDonald, R., Mistretta, J., Ettenberger, S. (1996). The challenges of instruction that supports student thinking. Learning Disabilities Research and Practice, 11(3), 138–146.
Reiner, M., Slotta, J., Chi, M., Resnick, L. (2000). Naive physics reasoning: a commitment to substancebased conceptions. Cognition and Instruction, 18, 1–34.
Roth, W. M. (2001). Modelling design as situated and distributed process. Learning and Instruction, 11, 211–239.
Slotta, J. D., Chi, M. T. H., Joram, E. (1995). Assessing students’ misclassifications of physics concepts: An ontological basis for conceptual change. Cognition and Instruction, 13, 373–400.
Suthers, D. D. & Hundhausen, C. D. (2001). Learning by constructing collaborative representations: An empirical comparison of three alternatives. In P. Dillenbourg, A. Eurelings, K. Hakkarainen (Eds.), European Perspectives on Computer-Supported Collaborative Learning, Proceedings of the First European Conference on Computer-Supported Collaborative Learning (pp. 577-584). Universiteit Maastricht, Maastrict, the Netherlands, March 22-24, 2001.
Zhang, J. (1991). The interaction of internal and external representations in a problem solving task. In Proceedings of the 13th Annual Conference of Cognitive Science Society (pp. 954–958). Hillsdale, NJ: Lawrence Erlbaum Associates.
Zhang, J. & Norman, D. A. (1994). Representations in distributed cognitive tasks. Cognitive Science, 18, 87–122.
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Pata, K., Sarapuu, T. (2003). Framework for Scaffolding the Development of Problem Representations by Collaborative Design. In: Wasson, B., Ludvigsen, S., Hoppe, U. (eds) Designing for Change in Networked Learning Environments. Computer-Supported Collaborative Learning, vol 2. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-0195-2_25
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DOI: https://doi.org/10.1007/978-94-017-0195-2_25
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-6321-2
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