Building a Recommender Agent for e-Learning Systems
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The paper describes a model for recommendations in learning scenarios which has been designed from empirical findings following usability and accessibility criteria. This model supports course designers in describing recommendations and presents additional information to the user to explain why the recommendation has been provided. A prototype of a recommender system based on this model has been integrated in an open source standard-based learning management system. The main goal of the recommender is to improve the learning efficiency. Examples of recommendations defined with this model are provided. Moreover, a users' experience is reported.