A Personalized e-Learning System Based on GWT

With the development of Internet technology, information resource is being spread widely, thus the issue of information overload formed. It becomes more difficult for users to retrieve their needed information from so enormous information space. To solve the issue of information overload, recommender system emerges as the times require. This paper presents the personalized e-Learning system using Collaborative Filtering Recommender Algorithm based on clustering of items. And the system will be implemented based on GWT with the advantages that developers can use only one language to develop web application. By the solution of GWT, the function of personalized information recommendation of e-Learning system will be achieved and personalized information will be recommended to users to help them improve learning efficiency. The results show that the solution of GWT is more flexible and simple, reduce the development cycle and cost, improved the real-time requirement of e-Learning system.