A Framework for Recommender System to Support Personalization in an E-Learning System
Zameer Gulzar, A. Leema, Department of Computer Applications, B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, India
IJWLTT Volume 13, Number 3, ISSN 1548-1093 Publisher: IGI Global
This article describes how nowadays, the learner-centered approach is becoming more and more popular by providing liberties to the learner to choose and study courses of interest. The common problem which persists among the researchers is that they do not exactly point out which subject or coursework which would be suitable for them from their research standpoint. This is because it is very important for researcher scholars to acquire knowledge and skills that will help them to do research in an efficient and effective way. Because of the availability of a wide variety of choices among courses, researchers can be in an uncomfortable situation making a decision about which courses would be more appropriate for them. In such kinds of conditions, a recommender system can be helpful in decision making to choose some suitable courses according to interest and requirements. This article proposes a framework which is novel and convenient for any learning system by integrating various techniques together within this framework.
Gulzar, Z. & Leema, A. (2018). A Framework for Recommender System to Support Personalization in an E-Learning System. International Journal of Web-Based Learning and Teaching Technologies, 13(3), 51-68. IGI Global.