Agent based student modeling in distributed CBR based intelligent Tutoring system

Student modeling is a key component in any Intelligent Tutoring System (ITS). In today's distributed computing environment, the tutoring system can take advantage of networking to utilize the model for a student for students from other similar group. In the present paper we present a methodology where using Case Based Reasoning (CBR), the ITS provides student modeling for online learning in a distributed environment with the help of agents. The paper describes the approach, the architecture, and the agent characteristics for the student modeling in the ITS. This concept can be deployed to develop ITS where the tutor can author and the students can learn locally whereas the ITS can model the students' learning globally in a distributed environment. The advantage of such an approach is that both the learning material (domain knowledge) and students' model can be globally distributed thus enhancing the efficiency of ITS with reducing the bandwidth requirement and complexity of the system.