Student modeling and mastery learning in a computer-based programming tutor
The ACT Programming Languages Tutor helps students as they write short computer programs. The tutor is constructed around a set of several hundred programming rules that allows the program to solve exercises step-by-step along with the student. This paper evaluates the tutor's student modeling procedure which employs an overlay of these programming rules. The tutor maintains an estimate of the probability that the student has learned each rule, based on the student's performance. These estimates are used to guide remediation and implement mastery learning. The predictive validity of these probability estimates for posttest and tutor performance is assessed.
KeywordsStudent Modeling Learning Probability Applicable Rule Extractor Function Programming Rule
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