Accessing e-Learners' knowledge for personalization in e-Learning environment

Pao Hua Chou, Menq-Jiun Wu, Pi Hsiang Li, Kuang Ku Chen

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


e-Learning has become a trend in the world nowadays. However, most researches neglect a fundamental issue - the e-Learner 's prior knowledge on which the useful intelligent systems are based. This research employs the e-Learner's prior knowledge and mines his/her interior desire on appropriate target courses or materials as a part of a personalization process to construct the overall e-Learning strategy for education. This paper illustrates a novel web usage mining approach, based on the sequence mining technique applied to e-Learner's navigation behaviour, to discover patterns in the navigation of e-Learning websites. Three critical contributions are made in this paper: (1) using the footstep graph to visualize the e-Learner's click-stream data so any interesting pattern can be detected more easily and quickly; (2) illustrating a novel sequence mining approach to identify pre-designated e-Learner navigation patterns automatically and integrating a back-propagation network (BPN) model smoothly; and (3) applying the empirical research to indicate that the proposed approach can predict and categorize the e-Learners ' navigation behaviour with high accuracy.

Original languageEnglish
Pages (from-to)295-318
Number of pages24
JournalJournal of Research and Practice in Information Technology
Issue number4
Publication statusPublished - 2009 Nov 1

All Science Journal Classification (ASJC) codes

  • Software
  • Management Information Systems
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications

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