A Cognitive Model of New Data on Human Problem Solving Essay

A Cognitive Model of New Data on Human Problem Solving Essay

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A Cognitive Model of New Data on Human Problem Solving

I. Project Description

Cognitive modeling is the creation of models which resemble and explain the way in which humans do things. What makes them so interesting to me is the process though which cognitive scientists go in order to create these models. Cognitive scientists often use a generative theory in creating such models. A generative theory is a theory that explains a set of empirical observations by actually generating them (as opposed to just summarizing them or characterizing them with equations or logic). Thus, a generative theory has to be executable, like a computer program or a "recipe".

The system on which I'm basing my work is named Cascade (VenLehn, Jones & Chi, 1991). Cascade was originally developed to explain the cognitive mechanisms involved in the self-explanation effect (Chi et al., 1989; Fergusson-Hessler & de Jong, 1990; Pirolli & Bielaczyc, 1989). Simplifying a bit, the effect shows that people learn more effectively by studying examples when they are careful to explain to themselves as many steps of the example as they can. Students who do not carefully explain worked out example steps do not perform as well on subsequent problems. Cascade models the potential learning mechanisms that cause this effect.

I now wish to apply the Cascade model to a new problem domain and a new set of psychological data. Originally, Cascade was written to solve problems in Newtonian physics, the domain used in Chi et al.'s study. Since Cascade was first created additional psychological research has been done in other problem domains. Due to the versatility of Cascade, applying the Cascade model to other problem domains would be beneficial. In the fall of 2000 I...


... middle of paper ...


...nnual Conference of the Cognitive Science Society.

Newell, A., & Simon, H. A. (1972). Human Problem Solving. New Jersey: Prentice-Hall Inc.
Pirolli, P., & Bielaczyc, K. (1989). Empirical analyses of self-explanation and transfer in learning to program. In G. M. Olson & E. E. Smith (Eds.), Proceedings of the Eleventh Annual Conference of the Cognitive Science Society (pp. 450-457). Hillsdale, NJ: Lawrence Erlbaum.

Renkl, A., Atkinson, R. K., & Maier, U. H. (2000). From studying examples to solving problems: Fading worked-out solution steps helps learning. In L. R. Gleitman & A. K.

Joshi (Eds.), Proceedings of the Twenty-Second Annual Conference of the Cognitive Science Society (pp. 393-398). Mahwah, NJ: Lawrence Erlbaum.

VanLehn, K., Jones, R. M., & Chi, M. T. H. (1991). A model of the self-explanation effect. Journal of the Learning Sciences, 2, 1-59.

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