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ERIC Number: EJ860432
Record Type: Journal
Publication Date: 2009
Pages: 13
Abstractor: As Provided
Reference Count: 25
ISSN: ISSN-1436-4522
Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval
Khribi, Mohamed Koutheair; Jemni, Mohamed; Nasraoui, Olfa
Educational Technology & Society, v12 n4 p30-42 2009
In this paper, we describe an automatic personalization approach aiming to provide online automatic recommendations for active learners without requiring their explicit feedback. Recommended learning resources are computed based on the current learner's recent navigation history, as well as exploiting similarities and dissimilarities among learners' preferences and educational content. The proposed framework for building automatic recommendations in e-learning platforms is composed of two modules: an off-line module which pre-processes data to build learner and content models, and an online module which uses these models on-the-fly to recognize the students' needs and goals, and predict a recommendation list. Recommended learning objects are obtained by using a range of recommendation strategies based mainly on content based filtering and collaborative filtering approaches, each applied separately or in combination. (Contains 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