Chris Piech
Mehran Sahami
Daphne Koller
Steve Cooper
Paulo Blikstein
ABSTRACT
Despite the potential wealth of educational indicators expressed in a student's approach to homework assignments, how students arrive at their final solution is largely overlooked in university courses. In this paper we present a methodology which uses machine learning techniques to autonomously create a graphical model of how students in an introductory programming course progress through a homework assignment. We subsequently show that this model is predictive of which students will struggle with material presented later in the class.
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Index Terms
- Modeling how students learn to program
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