Abstract
The ACT Programming Tutor helps students as they complete short programming exercises. The tutor is constructed around an ideal student model consisting of several hundred production rules. This model allows the tutor to solve exercises along with the student and serves as an overlay model of the student’s knowledge. As the student completes exercises, the tutor maintains an estimate of the probability that student has learned each rule, based on a two-state learning model. These estimates are employed to guide remediation. This paper assesses the predictive validity of this modeling process, and examines the implications for the rules in the ideal student model.
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© 1993 Springer-Verlag Berlin Heidelberg
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Corbett, A.T., Anderson, J.R. (1993). Student Modeling in an Intelligent Programming Tutor. In: Lemut, E., du Boulay, B., Dettori, G. (eds) Cognitive Models and Intelligent Environments for Learning Programming. NATO ASI Series, vol 111. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-11334-9_13
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DOI: https://doi.org/10.1007/978-3-662-11334-9_13
Publisher Name: Springer, Berlin, Heidelberg
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