Personalized E-learning Recommender System to Adjust Learners’ Level
Brief Paper
ID: 54937
Abstract: Personalized e-learning has often been linked to recommender systems, because to be able to personalize a teaching process it is essential to consider the specificities of each learner. The use of recommender systems has thus developed in education, and a lot of research work is beginning to take an interest in it, taking advantage of the automatisms offered by the online learning environment. Our work fits into this context, and tries to use a hybrid recommendation system to be able to offer a teaching that is adapted to the needs and specificities of the learners.
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