Research on the personalized learning model for network teaching based on multi-agent

Network teaching is an effective way for studying. You can use only a PC connected to Internet, without the necessity of physical attendance at one place and time, so now network teaching is a popular method of learning. However, it still has challenges in supporting students´ learning activities in network teaching systems. For example, students can not receive immediate notification when the new knowledge is adding into network teaching system. To solve these problems we proposed a personalized learning model for network teaching. On the basis of sufficiently analyzing the necessity and feasibility for using the multi-agent technology to develop the personalized learning model for network teaching system, this paper proposes a three-layer structure of personalized learning model for network teaching based on multi-agent which includes client layer, personalized logic layer and data service layer with user feature base, method base and knowledge base. The feature of the model for network teaching is the personalized push, and that is achieved by using record agent, inform agent and feature agent. The system is implemented using Eclipse technology, and this paper also introduces the key problems of system implementation.