Abstract
In the first part of the chapter, we argue that the goal of formal education should be meaningful learning. Meaningful learning is necessarily social, collaborative, intentional, authentic, and active. The result of meaningful learning lies in its cognitive residue, the learner’ mental model.
In the second part of this chapter, we describe different components of individual mental models and collaborative mental models. Mental models are rich, complex, interconnected, interdependent, multi-modal representations of what someone or some group knows.
Perhaps the most effective means for fostering the development of mental models is the construction of computational models. We argue that modeling is an essential skill for all disciplines engaging students in meaningful learning. So, the third part of the chapter focuses on how technologies can be used to support students’ construction of their own models and theories of how phenomena work. Students can build models of domain knowledge, problems, systems, semantic structures, and thinking while studying. In addition to distinguishing between what is modeled, we also distinguish between kinds of modeling systems (deductive simulations, inductive simulations, qualitative causal models like expert systems, and semantic modeling tools), and their affordances for supporting the construction of mental models.
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References
Adams-Webber, J. (1995). Constructivist psychology and knowledge elicitation. Journal of Constructivist Psychology, 8(3), 237–249.
Confrey, J., & Doerr, H. M. (1994). Student modelers. Interactive Learning Environments, 4(3), 199–217.
DiSessa, A., & Abeson, H. (1986). Boxer: A reconstructible computational medium. Communications of the ACM, 29, 859–868.
Dole, J.A., Sinatra, G.M. (1998). Reconceptualizing change in the cognitive construction of knowledge. Educational Psychologist, 33, 109–128.
Durkheim, Émile. (1915) The Elementary Forms of the Religious Life. Translated by Joseph Ward Swain. New York and London: The Free press
Engeström, Y. (1987). Learning by expanding: An activity theoretical approach to developmental research. Helsinki, Finland: Orienta-Konsultit Oy.
Frederiksen, J. R., White, B. Y. (1998). Teaching and learning generic modeling and reasoning skills. Journal of Interactive Learning Environments, 55, 33–51.
Gentner, D., & Stevens, A.L. (1983). Mental models. Hillsdale, NJ: Lawrence Erlbaum Associates.
Johnson-Laird, P.N. (1983). Mental models: Towards a cognitive science of language, inference, and consciousness. Cambridge, MA: Harvard University Press.
Jonassen, D.H. (1997). Instructional design models for well-structured and ill-structured problem-solving learning outcomes. Educational Technology: Research and Development, 45(1), 65–95.
Jonassen, D.H. (2000). Computers as Mindtools for schools: Engaging critical thinking. Columbus, OH: Merrill/Prentice-Hall.
Jonassen, D.H. (2003). Using cognitive tools to represent problems. Journal of Research on Technology in Education, 35(3), 362–381
Jonassen, D.H., Beissner, K., & Yacci, M.A. (1993). Structural knowledge: Techniques for representing, conveying, and acquiring structural knowledge. Hillsdale, NJ: Lawrence Erlbaum.
Jonassen, D.H., & Henning, P. (1999). Mental models: Knowledge in the head and knowledge in the world. Educational Technology, 9(3), 37–42.
Jonassen, D.H., Howland, J., Moore, J., & Marra, R.M. (2003) Learning to solve problems with technology: A constructivist perspective, 2nd. Ed. Columbus, OH: Merrill/Prentice-Hall.
Jonassen, D.H. & Wang, S. (2003) Using expert systems to build cognitive simulations. Journal of Educational Computing Research, 28(1), 1–13.
Kraiger, K., & Salas, E. (1993, April). Measuring mental models to assess learning during training. Paper presented at the Annual Meeting of the Society for Industrial/Organizational Psychology, San Francisco, CA.
Larkin, J.H. (1983). The role of problem representation in physics. In D. Gentner & A.L. Stevens (Eds.). Mental models (pp. 75–98). Hillsdale, NJ: Lawrence Erlbaum Associates.
Lehrer, R., & Schauble, L. (2000). Modeling in mathematics and science. In R. Glaser (Ed.) Advances in instructional psychology: volume 5. Educational design and cognitive science (pp. 101–159). New Jersey: Lawrence Erlbaum.
Lippert, R. C. (1988). An expert system shell to teach problem solving. Tech Trends, 33(2), 22–26.
McGuinness, C. (1986). Problem representation: The effects of spatial arrays. Memory & Cognition, 14(3), 270–280.
Mellar, H., Bliss, J., Boohan, R., Ogborn, J., & Tompsett, C. (1994). Learning with artificial worlds: Computer-based modeling in the curriculum. London: Falmer Press.
Penner, D.E., Giles, N.D., Lhrer, R., & Schauble, L. (1997). Buildig functional models: designing and elbow. Journal of Research in Science Teaching, 34(2), 125–143.
Ploetzner, R., & Spada, H. (1998). Constructing quantitative problem representations on the basis of qualitative reasoning. Interactive Learning Environments, 5, 95–107.
Ploetzner, R., Fehse, E., Kneser, C., & Spada, H. (1999). Learning to relate qualitative and quantitative problem representations in a model-based setting for collaborative problem solving. Journal of the Learning Sciences, 8(2), 177–214.
Rips, L.J. (1986). Mental muddles. In M. Brand & R.M. Harnish (Eds.), The representation of knowledge and beliefs (pp. 258–286). Tuscon, AZ: University of Arizona Press.
Salomon, G., Perkins, D.N. & Globerson, T. (1991). Partners in Cognition: Extending Human Intelligence with Intelligent Technologies. Educational Researcher, 20(3), 2–9.
Schank, R.C. (1994). Goal-based scenarios. In R.C. Schank & E. Langer (eds.), Beliefs, reasoning, and decision making: Psycho-logic in honor of Bob Abelson. Hillsdale, NJ: Lawrence Erlbaum.
Schwartz, J.L., & Yerulshalmy, M. (1987). The geometric supposer: Using microcomputers to restore invention to the learning of mathematics. In D. Perkins, J. Lockhead, & J.C. Bishop (Eds.), Thinking: The second international conference (pp. 525–536). Hillsdale, NJ: Lawrence Erlbaum Associates.
Schwarz, C.V., & White, B. (2005). Metamodeling Knowledge: Developing Students’ Understanding of Scientific Modeling. Cognition and Instruction, 23(2), 165–205.
Schwarz, C.V., & White, B.Y. (in press). Developing a model-centered approach to science education. Journal of Research in Science Teaching.
Shavelson, R.J. (1972). Some aspects of the correspondence between content structure and cognitive structure in physics instruction. Journal of Educational Psychology, 63, 225–234.
Spector, J. Michael; Christensen, Dean L; Sioutine, Alexei V; McCormack, Dalton (2001) Models and simulations for learning in complex domains: Using causal loop diagrams for assessment and evaluation, in: Computers in Human Behavior. Vol 17(5–6) Sep–Nov 2001, 517–545
Taylor, H.A., & Tversky, B. (19920. Spatial mental models derived from survey and route descriptions Journal of Memory and Language, 31, 261–292.
van der Veer, G.C. (1989). Individual differences and the user interface. Ergonomics, 32(11), 1431–1449.
Vosniadou, S. (1999). Conceptual change research: The state of the art and future directions In W. Schnotz, S. Vosniadou, & M. Carretero (Eds.), New perspectives on conceptual change (pp. 1–13). Amsterdam: Pergamon.
White, B. (1993a). ThinkerTools: Causal models, conceptual change, and science education. Cognition and Instruction, 10(1), 1–100.
Wittgenstein, L. (1922). Tractatus logico-philosophicus. London: Routledge.
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Jonassen, D.H., Strobel, J. (2006). Modeling for Meaningful Learning. In: Hung, D., Khine, M.S. (eds) Engaged Learning with Emerging Technologies. Springer, Dordrecht. https://doi.org/10.1007/1-4020-3669-8_1
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