Fuzzy Logic and Data Mining for e-Learning Personalization

K.K. Loo and B. Cheung (PRC)

Keywords

: e-Learning, fuzzy logic, rule-based system, association rule mining.

Abstract

The SmartTutor system is a HKU SPACE research and development product for e-learning. Since the first release in 2001, SmartTutor has served more than six thousand learners for various subjects. With the im minent official launch of the HKU SPACE e-Learning Services Centre, empowered by Hewlett-Packard Hong Kong Limited, a big increase in user population is an ticipated in near future. SmartTutor is an innovative online learning plat form for deployment of e-courses. One of the func tionalities that differentiates SmartTutor from other online learning platforms is that, applying fuzzy logic, rule-based inferencing and data mining technologies, SmartTutor can identify the weaknesses of a learner in an e-course and advise the learner how to do revi sion efficiently. In this paper, we give a technical report on how we integrate these technologies in SmartTutor, as well as the theoretical background in our design, to achieve personalization in e-learning.

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