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DC Field | Value | Language |
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dc.contributor.author | DJEBARNIA, NOUR EL ISLEM | - |
dc.date.accessioned | 2022-10-13T10:51:18Z | - |
dc.date.available | 2022-10-13T10:51:18Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | http://dspace.univ-guelma.dz/jspui/handle/123456789/13243 | - |
dc.description.abstract | In recent years, information and communication technologies have undergone rapid changes and developments to facilitate access to information anytime and anywhere. Today, access to information is gaining in importance and the development of technological possibilities has changed the nature of the learning environment. In this work, we focus on a more well-known type of learning, computer-assisted collaborative learning. This mode of learning offers learners the opportunity to communicate, collaborate, etc. one of the major problems of this system encountered by users is the overload of educational data. Recommender systems have been proposed to solve this type of problem. Our work is part of the context of a recommendation system for educational resources in a computer-assisted collaborative learning system. This recommendation is based on the social relationships between learners and many other factors. To validate this new recommendation approach, a learning system was developed called RR-LEARNER (Resources Recommendation for LEARNER). This platform adopts the proposed recommendation method and offers several features to learners. Keywords: Learning, Recommender systems, Collaborative computer-assisted learning, educational resources. | en_US |
dc.language.iso | fr | en_US |
dc.publisher | université de guelma | en_US |
dc.subject | E-learning, système de Recommandation, Recommandation des ressources, Profils des apprenants | en_US |
dc.title | Un système de recommandation des ressources en se basant sur les profils des apprenants | en_US |
dc.type | Working Paper | en_US |
Appears in Collections: | Master |
Files in This Item:
File | Description | Size | Format | |
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DJEBARNIA_NOUR EL ISLEM_F5.pdf | 7,88 MB | Adobe PDF | View/Open |
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