A Recommender Model in E-learning Environment

Abstract

Various researches in E-learning mainly focused on improving learner achievements based on learner profile. Explosive growth of distance learning has caused difficulty of locating appropriate learning objects for learner in this environment, and it becomes relatively widespread learning method for learner. In this paper, an innovative learning approach is proposed by using recommender system to address this challenge. Based on this tool, a learning model is designed to achieve personalized learning experiences by selecting and sequencing the most appropriate learning objects. Moreover, some experiments were conducted to evaluate the performance of our approach. The result reveals suitability of using recommender system in order to support online learning activities to enhance learning.