Learning Tutorial Rules Using Classification Based On Associations

Authors:
Xin Lu;Barbara Di Eugenio;Stellan Ohlsson
Affiliations:
Department of Computer Science, University of Illinois at Chicago, USA;Department of Computer Science, University of Illinois at Chicago, USA;Department of Computer Science, University of Illinois at Chicago, USA
Venue:
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Year:
2007

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Abstract

Rules have been showed to be appropriate representations to model tutoring and can be easily applied to intelligent tutoring systems. We applied a machine learning technique, Classification based on Associations, to automatically learn tutorial rules from annotated tutoring dialogues of a human expert tutor. The rules we learn concern the tutor's attitude, the domain concepts to focus on, and the tutor moves. These rules have very good accuracy. They will be incorporated in the feedback generator of an Intelligent Tutoring System.