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ERIC Number: EJ814053
Record Type: Journal
Publication Date: 2007
Pages: 22
Abstractor: As Provided
Reference Count: 25
ISSN: ISSN-1436-4522
Personalized Learning Objects Recommendation Based on the Semantic-Aware Discovery and the Learner Preference Pattern
Wang, Tzone I; Tsai, Kun Hua; Lee, Ming Che; Chiu, Ti Kai
Educational Technology & Society, v10 n3 p84-105 2007
With vigorous development of the Internet, especially the web page interaction technology, distant E-learning has become more and more realistic and popular. Digital courses may consist of many learning units or learning objects and, currently, many learning objects are created according to SCORM standard. It can be seen that, in the near future, a vast amount of SCORM-compliant learning objects will be published and distributed cross the Internet. Facing huge volumes of learning objects, learners may be lost in selecting suitable and favorite learning objects. In this paper, an adaptive personalized recommendation model is proposed in order to help recommend SCORM-compliant learning objects from repositories in the Internet. This model adopts an ontological approach to perform semantic discovery as well as both preference-based and correlation-based approaches to rank the degree of relevance of learning objects to a learner's intension and preference. By implementing this model, a tutoring system is able to provide easily and efficiently suitable learning objects for active learners. (Contains 1 table and 12 figures.)
International Forum of Educational Technology & Society. Athabasca University, School of Computing & Information Systems, 1 University Drive, Athabasca, AB T9S 3A3, Canada. Tel: 780-675-6812; Fax: 780-675-6973; Web site:
Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A