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Personnalisation des MOOC par la réutilisation de Ressources Éducatives Libres

Abstract : For many years now, personalization in TEL is a major subject of intensive research. With the spreading of Massive Open Online Courses (MOOC), the personalization issue becomes more acute. Actually, any MOOC can be followed by thousands of learners with different educational levels, learning styles, preferences, etc. So, it is necessary to present pedagogical contents taking into account their heterogeneous profiles so that they can maximize their benefit from following the MOOC.At the same time, the amount of Open Educational Resources (OER) available on the web is permanently growing. These OERs have to be reused in contexts different from the initial ones for which they were created.Indeed, producing quality OER is costly and requires a lot of time. Then, different metadata schemas are used to describe OER. However, the use of these schemas has led to isolated repositories of heterogeneous descriptions which are not interoperable. In order to address this problem, a solution adopted in the literature is to apply Linked Open Principles (LOD) to OER descriptions.In this thesis, we are interested in MOOC personalization and OER reuse. We design a recommendation technique which computes a set of OERs adapted to the profile of a learner attending some MOOC. The recommended OER are also adapted to the MOOC specificities. In order to find OER, we are interested in those who have metadata respecting LOD principles and stored in repositories available on the web and offering standardized means of access. Our recommender system is implemented in the MOOC platform Open edX and assessed using a micro jobs platform.
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Submitted on : Thursday, July 26, 2018 - 11:20:07 AM
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Hiba Hajri. Personnalisation des MOOC par la réutilisation de Ressources Éducatives Libres. Autre [cs.OH]. Université Paris Saclay (COmUE), 2018. Français. ⟨NNT : 2018SACLC046⟩. ⟨tel-01849443⟩

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