Hybrid recommendation approach in online learning environments

Abstract

Online learning environments (OLE) have provided learners with personalized content through the use of Recommendation Systems (RS). Some RS are based on a learner’s profile to offer content that matches his/her preferences, others consider the learner in a collective setting and offer him appreciated or popular content in his/her group. Our contribution consists of proposing a hybrid approach of RS which takes into account the learner’s preferences and the similarity of the learner with his/her group, to improve the relevance of the proposed contents.