Abstract
In this study, we concentrate on learning activity sharing and individualized recommendation based on dynamical user correlations, in order to support and facilitate the web-based learning process integrated with social streams. A user correlation-based learning activity model is built to demonstrate the relations among user, learning task and learning activity. Based on these, an integrated method is proposed to provide a target user with the possible learning activity as the next learning step, which is expected to enhance the learning efficiency. Finally, design of a Moodle-based prototype system is discussed.
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Zhou, X., Chen, J., Jin, Q., Shih, T.K. (2012). Learning Activity Sharing and Individualized Recommendation Based on Dynamical Correlation Discovery. In: Popescu, E., Li, Q., Klamma, R., Leung, H., Specht, M. (eds) Advances in Web-Based Learning - ICWL 2012. ICWL 2012. Lecture Notes in Computer Science, vol 7558. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33642-3_21
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DOI: https://doi.org/10.1007/978-3-642-33642-3_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33641-6
Online ISBN: 978-3-642-33642-3
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