Learning activity sharing and individualized recommendation based on dynamical correlation discovery

Authors:
Xiaokang Zhou;Jian Chen;Qun Jin;Timothy K. Shih
Affiliations:
Graduate School of Human Sciences, Waseda University, Tokorozawa, Japan;Graduate School of Human Sciences, Waseda University, Tokorozawa, Japan;Graduate School of Human Sciences, Waseda University, Tokorozawa, Japan;Dept. of Computer Science & Information Engineering, National Central University, Taoyuan, Taiwan
Venue:
ICWL'12 Proceedings of the 11th international conference on Advances in Web-Based Learning
Year:
2012

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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.