AAAI Publications, Twenty-Third IAAI Conference

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Learning a Skill-Teaching Curriculum with Dynamic Bayes Nets
Derek T. Green, Thomas J. Walsh, Paul R. Cohen, Yu-Han Chang

Last modified: 2011-08-04

Abstract


We propose an intelligent tutoring system that constructs a curriculum of hints and problems in order to teach a student skills with a rich dependency structure. We provide a template for building a multi-layered Dynamic Bayes Net to model this problem and describe how to learn the parameters of the model from data. Planning with the DBN then produces a teaching policy for the given domain. We test this end-to-end curriculum design system in two human-subject studies in the areas of finite field arithmetic and artificial language and show this method performs on par with hand-tuned expert policies.


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