Agent-Based E-Learning Course Recommendation: Matching Learner Characteristics with Content Attributes
In this article an agent framework for discovery and recommendation of e-learning courses in agent-based learning environments is presented. In the context of this framework, a way to model and store the learner model and the content attributes metadata information using international specifications...
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Published in | International journal of computers & applications Vol. 25; no. 1; pp. 50 - 64 |
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Main Authors | , |
Format | Journal Article Conference Proceeding |
Language | English |
Published |
Anaheim, CA
Taylor & Francis
01.01.2003
Calgary, AB Acta Press Zürich |
Subjects | |
Online Access | Get full text |
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Summary: | In this article an agent framework for discovery and recommendation of e-learning courses in agent-based learning environments is presented. In the context of this framework, a way to model and store the learner model and the content attributes metadata information using international specifications and standards is studied, and two methodologies for constructing a matching mechanism to select courses most suited to the learner are introduced. These mechanisms are applied to the case of a learning community within the context of the NEMO project, and the results are discussed. |
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ISSN: | 1206-212X 1925-7074 |
DOI: | 10.1080/1206212X.2003.11441685 |