An Intelligent Tutoring System for Entity Relationship Modelling
International Journal of Artificial Intelligence in Education
The Effect of Explaining on Learning: a Case Study with a Data Normalization Tutor
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
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Self-explanation is an effective teaching/learning strategy that has been used in several intelligent tutoring systems in the domains of Mathematics and Physics to facilitate deep learning. Since all these domains are well structured, the instructional material to self-explain can be clearly defined. We are interested in investigating whether self-explanation can be used in an open-ended domain. For this purpose, we enhanced KERMIT, an intelligent tutoring system that teaches conceptual database design. The resulting system, KERMIT-SE, supports self-explanation by engaging students in tutorial dialogues when their solutions areerroneous. We plan to conduct an evaluation in July 2002, to test the hypothesis that students will learn better with KERMIT-SE than without self-explanation.