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Towards a serendipitous e-learning recommendation system / Zahra QARNOUF

Public ISBD Titre : Towards a serendipitous e-learning recommendation system Type de document : projet fin études Auteurs : Zahra QARNOUF, Auteur Langues : Français (fre) Catégories : BIG DATA Mots-clés : Recommender system, Serendipity, E-learning Index. décimale : mast 252/19 Résumé : Nowadays, we are witnessing a big growth of information especially in learning technology with the advent of Internet. Thus how to recommend appropriate course to improve students’ learning outcomes has become a daunting task. With this growth, a student’s choices have grown exponentially. As a result, recommender systems have been put in place to deal with this huge amount of information, as it is difficult for students to decide which courses to choose. Therefore, we rely on the social aspect of the learning experience, to propose an algorithm that injects serendipitous items within a recommendation system. The approach should help broaden students’ horizons and provide the unexpectedness often lacking in existing e-learning platforms. Towards a serendipitous e-learning recommendation system [projet fin études] / Zahra QARNOUF, Auteur . - [s.d.]. Langues : Français (fre) Catégories : BIG DATA Mots-clés : Recommender system, Serendipity, E-learning Index. décimale : mast 252/19 Résumé : Nowadays, we are witnessing a big growth of information especially in learning technology with the advent of Internet. Thus how to recommend appropriate course to improve students’ learning outcomes has become a daunting task. With this growth, a student’s choices have grown exponentially. As a result, recommender systems have been put in place to deal with this huge amount of information, as it is difficult for students to decide which courses to choose. Therefore, we rely on the social aspect of the learning experience, to propose an algorithm that injects serendipitous items within a recommendation system. The approach should help broaden students’ horizons and provide the unexpectedness often lacking in existing e-learning platforms.

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Code barre	Cote	Support	Localisation	Section	Disponibilité
mast 252/19	mast 252/19 ZAH	Texte imprimé	Unité des masters	Mast/19	Disponible