Recommender System based on Learner Knowledge and Opining using Data Mining Techniques in Synchronous E-Learning Environment

Abstract

Learners are often getting uncertainty by the flow of information and have trouble in selecting the material to learn that satisfies their requirements and interests. It is the fact that the learners „learning interest, and behaviour changes over the time and subject to subject. It is very important, thus, to know learner preferences and what problem he/she faces during the programme. In this paper, our aim to address a novel framework for an e-learning recommender system that used data mining techniques to find learner preferences and requirements from their opinion. Make a more relevant relationship between learner and his/her preferences. Proposed framework is based on opinion and the knowledge level of learner.