Abstract
E - learning is one of important tools, which can help to improve self-directed learning habits of students. Current students are not satisfied e – learning systems yet because they provide identical study materials to students regardless of their intellectual levels. Conventional methods for inferring user’s academic level cannot infer their academic level without explicit students’ information. The requirement of the explicit information can be unpleased by students. To solve this problem, we develop a study level reasoning system to estimate the student’s academic level using the implicit students’ watching behaviors such as rewinding and skipping during watching the lecture videos. In the experimental section, we demonstrate how our method work using real students’ lecture watching history.
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Kim, J., Hwang, J., Kang, S., Heo, N. (2015). A Reasoning System for Predicting Study Level based on User’s Watching Behaviors. In: Selvaraj, H., Zydek, D., Chmaj, G. (eds) Progress in Systems Engineering. Advances in Intelligent Systems and Computing, vol 366. Springer, Cham. https://doi.org/10.1007/978-3-319-08422-0_39
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DOI: https://doi.org/10.1007/978-3-319-08422-0_39
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08421-3
Online ISBN: 978-3-319-08422-0
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