Social recommender approach for technology-enhanced learning

Abstract : 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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International Journal of Learning Technology, Inderscience, 2018, 13 (1), 〈10.1504/IJLT.2018.091631〉
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Soumis le : mercredi 23 mai 2018 - 10:42:52
Dernière modification le : lundi 4 juin 2018 - 08:33:31

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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, Inderscience, 2018, 13 (1), 〈10.1504/IJLT.2018.091631〉. 〈hal-01798108〉

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