期刊名称：International Journal of Emerging Technologies in Learning (iJET)
印刷版ISSN：1863-0383
出版年度：2019
卷号：14
期号：01
页码：110-124
语种：English
出版社：Kassel University Press
摘要：In the present paper, we address to construct a structured user profile in a Small Private Online Course (SPOC) based on user’s video clickstream analysis. We adopt an implicit approach to infer user’s preferences and experience difficulty based on user’s video sequence viewing analysis at the click-level as Play, Pause, Move forward… the Bayesian method is used in order to infer implicitly user’s interests. Learners with similar clickstream behavior are then segmented into clusters by using the unsupervised K-Means clustering algorithm. Videos that could meet the individual learner interests and offer a best and personalized experienced learning can therefore be recommended for a learner while enrolling in a SPOC based on his videos interactions and exploiting similar learners’ profiles.
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