Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/88272
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Type: Conference paper
Title: Evaluating a general model of adaptive tutorial dialogues
Author: Weerasinghe, A.
Mitrovic, A.
Thomson, D.
Mogin, P.
Martin, B.
Citation: Lecture Notes in Artificial Intelligence, 2011, vol.6738 LNAI, pp.394-402
Publisher: Springer Berlin Heidelberg
Issue Date: 2011
Series/Report no.: Lecture Notes in Computer Science; vol. 6738
ISBN: 9783642218682
ISSN: 0302-9743
1611-3349
Conference Name: 15th International Conference on Artificial Intelligence in Education (28 Jun 2011 - 2 Jul 2011 : Auckland, New Zealand)
Statement of
Responsibility: 
Amali Weerasinghe, Antonija Mitrovic, David Thomson, Pavle Mogin, Brent Martin
Abstract: 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.
Keywords: adaptive tutorial dialogues
constraint-based tutors
Ill-defined tasks
well-defined tasks
Rights: © Springer-Verlag Berlin Heidelberg 2011
DOI: 10.1007/978-3-642-21869-9_51
Appears in Collections:Aurora harvest 2
Computer Science publications

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