LORecommender is a recommendation approach for repositories of Learning Objects that adapts to the student profile.

The recommendation approach follows a cascade hybrid strategy that refines the decisions of a case-based recommender by using a collaborative one. We propose two alternatives case-based strategies. One of the case-based strategies acts in a reactive way and provides a high level of personalization. The second one lets include diversity in the proposals, and uses navigation-by-proposing, a simple conversational process that avoids posing direct questions and carries very little feedback overhead from the students’ perspective. The collaborative strategy lets refine recommendation results taking into account the learning community opinions.