Evaluating a General Model of Adaptive Tutorial Dialogues (2011)
Type of ContentConference Contributions - Published
PublisherUniversity of Canterbury. Computer Science and Software Engineering
AuthorsWeerasinghe, A., Mitrovic, A., Thomson, D., Mogin, P., Martin, B.show all
Tutorial dialogues are considered as one of the critical factors contributing to the effectiveness of human one-on-one tutoring. We discuss how we evaluated the effectiveness of a general model of adaptive tutorial dialogues in both an ill-defined and a well-defined task. The first study involved dialogues in database design, an ill-defined task. The control group participants received non-adaptive dialogues regardless of their knowledge level and explanation skills. The experimental group participants received adaptive dialogues that were customised based on their student models. The performance on pre- and post-tests indicate that the experimental group participants learned significantly more than their peers. The second study involved dialogues in data normalization, a well-defined task. The performance of the experimental group increased significantly between pre- and post-test, while the improvement of the control group was not significant. The studies show that the model is applicable to both ill- and well-defined tasks, and that they support learning effectively
CitationWeerasinghe, A., Mitrovic, A., Thomson, D., Mogin, P., Martin, B. (2011) Evaluating a General Model of Adaptive Tutorial Dialogues. Auckland, New Zealand: 15th International Conference on Artificial Intelligence in Education, 28 Jun-1 Jul 2011. Lecture Notes in Artificial Intelligence, 383-390.
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Keywordsadaptive tutorial dialogues; constraint-based tutors; ill-defined tasks; well-defined tasks
ANZSRC Fields of Research13 - Education::1303 - Specialist Studies in Education::130309 - Learning Sciences
13 - Education::1301 - Education Systems::130103 - Higher Education
13 - Education::1303 - Specialist Studies in Education::130306 - Educational Technology and Computing