N. Yabuki, Masaya Furukawa, M. Tobita, Kenichi Matsuoka
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引用次数: 1
Abstract
【Abstract】 Although recent CAI (Computer Aided Instruction) systems are generally advanced and improved by the use of rich "help" and visual aid, the problem that students often do not know what they do not understand has not been solved yet since the systems still treat students as a mass but not as individuals. In this research, we propose an intelligent agent-based CAI system, which identifies student's uncomprehending points adequately by comparing the knowledge of the student and the global knowledge system of a particular domain, and by sensing the student's interactions with the CAI system. We have developed a prototype system based on the proposed model for undergraduate level course of steel structures and investigated the feasibility.
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