Agent-Based E-Learning Course Recommendation: Matching Learner Characteristics with Content Attributes
Nikos Manouselis, Demetrios G. Sampson · International Journal of Computers and Applications · 2003
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.