Essay A Cognitive Model of New Data on Human Problem Solving

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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,
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In doing so I would learn the existing Cascade model well in addition to gaining extensive knowledge about the new problem domain.

The first step in this project is a task analysis (Newell & Simon, 1972). In this step we take the problem in Renkl et al.'s study and figure out exactly what the correct procedure is in solving the problems. This is one of the most critical steps in doing this project as we must correctly identify each piece of the solution of the problem. One of the goals of a good cognitive model is to accurately solve the problem as a real person would solve it; we don't want to just solve it as best we can. The result of the CTA will be a target knowledge base summarizing expert knowledge for this domain.

While working on the task analysis we would also work on prototyping one of the examples. During prototyping we will provide Cascade with the knowledge to solve one of the problems so we can work out the kinks in our knowledge representation.

After task analysis is complete we move on to the Prolog translation. This is the part of the project where I actually work with computers. Here I will take the existing Cascade system and "rip out" all of the Newtonian physics knowledge and replace it with the target knowledge probability. Given the complexity of the domain at hand, this should not be a
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