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A Recommender System for Videos Suggestion in a SPOC: A Proposed Personalized Learning Method

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Big Data and Smart Digital Environment (ICBDSDE 2018)

Part of the book series: Studies in Big Data ((SBD,volume 53))

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Abstract

Adaptivity, personalization and recommendation techniques are classic solutions recommended by many specialists for providing successful learning experiences by offering suitable adaptation that satisfy the learning preferences and meet heterogeneous characteristics of users. In the present paper, we propose a video recommender system across a Small Private Online Course (SPOC). We adopt a hybrid recommendation technique which consists on analyzing users’ video behavior while enrolling into a SPOC, estimating their interest in videos, finding learners with similar profile and finally recommending target user the same videos in which similar users are interested in. The proposed approach consist first on capturing and analyzing user’s video clickstream in order to construct a user profile with an implicit way to infer user’s interest in videos. Second, the unsupervised K-Means clustering algorithm is used to group users with similar video behavior into clusters. Finally, videos from similar profiles that could meet user’s interest can be recommended.

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Author information

Authors and Affiliations

  1. Laboratory of Technological Information and Modelisation (LTIM), Faculty of Sciences Ben M’Sik, University Hassan II, Casablanca, Casablanca, Morocco

    Naima Belarbi, Abdelwahed Namir & Habib Benlahmar

  2. Laboratory of Sciences, Information, Communication and Education Technology (LAPSTICE), Faculty of Sciences Ben M’Sik, Casablanca, Morocco

    Nadia Chafiq

  3. Observatory of Research in Didactics and University Pedagogy (ORDIPU), University Hassan II, Casablanca, Casablanca, Morocco

    Mohammed Talbi

  4. Laboratory of Analytical Chemistry and Physical Chemistry of Materials, Faculty of Sciences Ben M’Sik, Casablanca, Morocco

    Mohammed Talbi

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  1. Naima Belarbi
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  2. Nadia Chafiq
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  3. Mohammed Talbi
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  4. Abdelwahed Namir
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  5. Habib Benlahmar
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Correspondence to Naima Belarbi .

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Editors and Affiliations

  1. Faculty of Sciences and Techniques, Department of Computer Science, Moulay Ismail University, Errachidia, Morocco

    Yousef Farhaoui

  2. Department of Computer Science, Hassan II University, Casablanca, Morocco

    Laila Moussaid

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Belarbi, N., Chafiq, N., Talbi, M., Namir, A., Benlahmar, H. (2019). A Recommender System for Videos Suggestion in a SPOC: A Proposed Personalized Learning Method. In: Farhaoui, Y., Moussaid, L. (eds) Big Data and Smart Digital Environment. ICBDSDE 2018. Studies in Big Data, vol 53. Springer, Cham. https://doi.org/10.1007/978-3-030-12048-1_12

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