Method for building recommender systems in e-learning

Authors

  • Thuy Ngoc Nguyen Faculty of Information Technology - Ho Chi Minh City University of Education
  • An Te Nguyen Informatics Center - Ho Chi Minh City University of Science

Corressponding author's email:

tapchikhgkdt@hcmute.edu.vn

Keywords:

e-Learning, adaptive system, personalized system, profile

Abstract

During recent years, research works related to adaptation in e-learning were based on profile. The adaptation is focused on the organization and presentation of learning resources which are appropriated to the capability and knowledge of each learner. Such an adaptive system however is not enough for learner in a virtual learning environment where communication between teacher and learner is very limited and where learner   is isolated from his virtual community and does not know how to conduct his study. Learner needs thus to be supported in e-learning more than in conventional learning environment.

This paper will present a method based on the UMeL model for building systems to provide several supports in e-learning: recommendations on topics to be learned, on learning method, on reading materials as well as on study group to be joined which are appropriate to each learner profile

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References

Brooks Christopher, Greer Jim, Melis Erica, Ullrich Carsten, Combining ITS and eLearning Technologies: Opportunities and Challeneges, The 8th Intl. Conf. on Intelligent Tutoring Systems (ITS’06), TAIWAN, 2006.

Brusilovsky Peter, Millan Eva, The Adaptive Web, Methods and Strategies of Web Personalization, LNCS 4321, Springer Verlag Berlin/Heidelberg, 2007.

Brusilovsky Peter, The Construction and Aplication of Student Models in Intelligent Tutoring Systems, Journal of Computer and System Sciences Internatinal, vol.32(1), 1994.

BurkeRobin,HybridWebrecommender systems, The Adaptive Web, Methods and Strategies of Web Personalization, LNCS 4321, Springer Verlag Berlin/Heidelberg, 2007.

Dương Văn Hải, Cải tiến phương pháp xây dựng đặc trưng cộng đồng, Luận văn thạc sĩ, ĐHKHTN TPHCM, 2009.

Harper Maxwell F., Sen Shilad, Frankowski Dan, Supporting Social Recommendations with Activity- Balanced Clustering, The 1st ACM Conf. on Recommender Systems 2007 (RECSYS’07), Minnesota, USA, 2007.

Henze Nicola, Nejdl Wolfgang, Logically Characterizing Adaptive Educational Hypermedia Systems, The International Workshop on Adaptive Hypermedia and Adaptive Web-based Systems (AH’03), 2003.

Huỳnh Thắng Được, Xây dựng đặc trưng cộng đồng trong hệ thống tư vấn thông tin, Luận văn thạc sĩ, ĐHKHTN TPHCM, 2010.

Kelly Diane, Teevan Jaime, Implicit Feedback for Inferring User Preference: A Bibliography, ACM. SIGIR Forum, vol. 37(2), 2003.

Le Duc Long, Nguyen An Te, Nguyen Dinh Thuc, Hunger Axel, Learner Profile supports interaction between objects in e-Learning System, The 7th European Conf. on e-Learning (ECEL’08), CYPRUS, 2008.

Le Duc Long, Nguyen An Te, Nguyen Dinh Thuc, Hunger Axel, Building learner profile in adaptive e-Learning systems, The 4th Intl. Conf. on e-Learning (ICEL’2009), Toronto, CANADA, 2009.

Le Duc Long, Nguyen An Te, Nguyen Dinh Thuc, Hunger Axel, A Survey of Applying User Profile in the Adaptive Instructional Systems, The 5th Intl. Conf. on e-Learning (ICEL’2010), Penang, MALAYSIA, 2010.

Le Thi Huyen, Le Duc Long, Nguyen An Te, Nguyen Dinh Thuc, An approach to evaluate the utility of features of learner profile in the Adaptive e-Learning System, Conf. on Cognition and Exploratory Learning in Digital Age (IADIS-CELDA 2009), Roma, ITALY, 2009.

Mödritscher Felix, Garcia-Barrios Victor Manuel, Gütl Christian, The Past, the Present and the future of adaptive e-Learning, The 8th Intl. Conference Interactive Computer Aided Learning (ICL2004), AUSTRIA, 2004.

Montaner Miquel, López Beatriz, De La Rosa Josep Lluís, A Taxonomy of Recommender Agents on the Internet, Artificial Intelligence Review vol. 19, Kluwer Publishers, 2003.

Nguyen An Te, Denos Nathalie, Berrut Catherine, Improving New User Recommendations with Rule-based Induction on Cold User Data, The 1st ACM Conf. on Recommender Systems (RecSys’07), Minnesota, USA, 2007.

Nguyen An Te, Denos Nathalie, Berrut Catherine, Modèle des espaces de communautés orienté vers la diversité de recommandations pour les systèmes de filtrage, Journal in Information Engineering Sciences: Information - Interaction - Intelligence (I3), 2007.

Nguyen An Te, Denos Nathalie, Berrut Catherine, Cartes de communautés pour l’adaptation interactive de profils dans un système de filtrage d’information, 23ème Congrès annuel de l’Informatique des Organisations et Systèmes d’Information et de Décision (INFORSID’05), Grenoble, FRANCE, 2005.

Nguyễn Duy Thành, Xây dựng mô hình ứng dụng đặc trưng cá nhân nhằm hỗ trợ sự thích nghi trong hệ thống đào tạo trực tuyến, Luận văn thạc sĩ, 2009.

Rashid Al Mamunur, Albert Istvan, Cosley Dan, Lam Shyong K., McNee Sean M., Konstan Joseph A., Riedl John, Getting to Know You: Learning New User Preferences in Recommender Systems, The 7th Intl. Conf. on Intelligent User Interfaces (IUI’02), California, USA, 2002.

Hệ đào tạo từ xa qua Internet – Trường ĐH Khoa học tự nhiên TPHCM, www.e- learning.vn

Published

29-06-2011

How to Cite

[1]
T. N. Nguyen and A. T. Nguyen, “Method for building recommender systems in e-learning”, JTE, vol. 6, no. 2, pp. 28–41, Jun. 2011.

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Research Article

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