Detection of learning styles from learner's browsing behavior during e-learning activities

Abstract : One of the bases of adaptation and learning tracking is the learner’s modeling. Research in this field, or more generally in the field of user modeling, was sustained mainly on the detection of features related to the user’s knowledge, interests, goals, background, and individual traits [3]. We are interested in this last aspect, in particular the identification of the learning style. In this paper, we propose an approach for the learner’s activity perception on an e-learning platform to identify the user’s learning styles from observable indicators related to their learning path and interactions.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01302142
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Submitted on : Wednesday, April 13, 2016 - 3:40:59 PM
Last modification on : Thursday, March 21, 2019 - 1:10:01 PM

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Nabila Bousbia, Jean-Marc Labat, Amar Balla. Detection of learning styles from learner's browsing behavior during e-learning activities. Proceeddings of the 9th International Conference on Intelligent Tutoring Systems, Jun 2008, Montreal, Canada. pp.740-742, ⟨10.1007/978-3-540-69132-7_95⟩. ⟨hal-01302142⟩

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