Modelling Individual Differences in Students' Learning Strategies

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Journal of the Learning Sciences






Taylor & Francis

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Learners employ a wide variety of strategies when faced with learning and problem solving in a new domain. The focus of this research is on learners' strategies when studying and explaining instructional materials to themselves prior to problem solving. In the first part of the article, we present results from an empirical study in which the learning and self-explanation strategies of subjects studying instructions embedded in a hypertext environment were contrasted with those from subjects learning with more standard, linear instruction. In the hypertext environment, instruction could be browsed in a nonlinear fashion, and the instructional examples were annotated with explanatory elaborations that students could choose to view. We present a Soar computational model that accounts for results from the study. A particular emphasis of the model was on capturing strategy differences between individual subjects. The general modeling approach involved coupling a model of individual subjects' interaction strategies with opportunities for action supported by the interfaces of the instructional environments. Specifically, by setting parameters, the model was fit to individual subject data. Analyses of subjects' simulations contribute several new results for understanding individual differences in strategy use and their role in learning. We show that clusters of subjects identified through analyses of model parameters continued to exhibit similar behaviors during subsequent problem solving, suggesting that the clusters corresponded to genuine strategy classes. Furthermore, these clusters appeared to represent general strategies that were, in some sense, adaptive to the task.


Note that Mimi Recker was a research scientist at Georgia Institute of Technology when she worked on this article, and published as Margaret M. Recker.
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