Discovering Social Network to Improve Recommender System for Group Learning Support

Abstract

We refer to a new generation of web technologies such as social networking to address a recommender system that emphasize online collaborative learning. We propose an approach for improving recommender system through exploiting the learners note taking activity. We maintain that notes' features can be exploited by collaborative learning systems in order to enrich and extend the user profile and improve personalized learning. Thus our approach stresses collaborative note as a new and powerful kind of feedback and as a way to infer learner profiles. The experiment results show that our approach is effective. In this paper, we consider to construct a group learning environment, relying on learners' learning histories to reveal learner preferences and automatically identify learning materials that learners may learn. We propose an approach for discovering social network through exploiting the learners' activities of note taking and the content of notes. Discovering social network from collaborative notebook can be integrated to user profiles and thereby enhances recommender system for group learning.