Abstract
Web-based applications with very diverse learners fail because they fail to satisfy various needs. Some people use collaborative filtering methods to analyze learners’ profiles and provide recommendation to a new learners, but this methods provides false recommendations from beginners. We present a new method, which provides recommendations that depend on the credibility rather than the number of learners. We have designed, implemented, and tested what we call the Intelligent E-Course Agent (IECA). Our evaluation experiment shows that our approach greatly improves learners’ knowledge and therefore presents a course that is more closely related to their needs.
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Kiared, S.A., Razek, M.A., Frasson, C. (2006). The Pyramid Collaborative Filtering Method: Toward an Efficient E-Course. In: Ikeda, M., Ashley, K.D., Chan, TW. (eds) Intelligent Tutoring Systems. ITS 2006. Lecture Notes in Computer Science, vol 4053. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11774303_25
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DOI: https://doi.org/10.1007/11774303_25
Publisher Name: Springer, Berlin, Heidelberg
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