Cited By
View all- Pirrone RPilato GRizzo RRusso G(2005)Learning path generation by domain ontology transformationProceedings of the 9th conference on Advances in Artificial Intelligence10.1007/11558590_37(359-369)Online publication date: 21-Sep-2005
Applying Demand Analysis of a Set of Test Problems for Developing Adaptive Courses
Abstract
Knowledge space theory was already applied for building adaptive testing and training systems which contain test and training problems including their prerequisite structure, and which offer explanations and help for solving these problems. Normally, however, lessons prepare students for solving problems.In this paper, we present a method for systematically structuring an adaptive eLearning course containing test problems as well as lessons. This method is based on knowledge space theory extended by component-wise representation of problems and on applying demand analysis. A course developed with such a method can be fed into an adaptive tutoring system, realized, e.g., within the adaptive tutoring system RATH.
- Applying Demand Analysis of a Set of Test Problems for Developing Adaptive Courses
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Published In
December 2002
ISBN:0769515096
Copyright © Copyright (c) 2002 Institute of Electrical and Electronics Engineers, Inc. All rights reserved.
Publisher
IEEE Computer Society
United States
Publication History
Published: 03 December 2002
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View all- Pirrone RPilato GRizzo RRusso G(2005)Learning path generation by domain ontology transformationProceedings of the 9th conference on Advances in Artificial Intelligence10.1007/11558590_37(359-369)Online publication date: 21-Sep-2005