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Article Dans Une Revue International Journal of Learning Technology Année : 2018

Social recommender approach for technology-enhanced learning

Résumé

The present work fits into the context of recommender systems for educational resources, especially systems that use social information. Based on the research results in the field of recommender systems, social networks and technology-enhanced learning, we defined an educational resource recommendation approach. We rely on social relations between learners to improve recommendation accuracy. Our proposal is based on formal models that generate three types of recommendation, namely recommendation of popular resources, useful resources and recently viewed resources. We developed a learning platform which integrates our recommendation models. In
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Dates et versions

hal-01798108 , version 1 (23-05-2018)

Identifiants

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Mohammed Tadlaoui, Karim Sehaba, Sébastien George, Azeddine Chikh, Karim Bouamrane. Social recommender approach for technology-enhanced learning. International Journal of Learning Technology, 2018, 13 (1), pp.61-89. ⟨10.1504/IJLT.2018.091631⟩. ⟨hal-01798108⟩
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