The Research Of Agent-Based Distance Tutoring System And Student Model

Web-based Distance Education, employing the network as its channel of learning and teaching, is a kind of brand-new Internet application. However, a majority of web-based distance tutoring systems are devoid of intelligence and self-adaptation. Among most of new techniques, Agent technique is particularly suitable for web-based distance tutoring system to improve its shortcomings. Agent, bearing autonomy, sociability, reactivity, and pre-activeness, is a software entity, and able to stand in for other users or programs to complete work on its own initiative. In a word, using Agent technique can increase the interest of teaching content and the color of personalization, ameliorate teaching effect and enhance intelligence and self-adaptation of tutoring system. After analyzing the deficiencies of traditional web-based distance tutoring system models, this paper proposes an agent-based distance tutoring system model. The model is made up of six modules and each module includes a few agents. Utilizing the cooperative mechanism among agents, the model realizes knowledge exchange and share among the modules and shapes a lay-structure multi-agent system. Utilizing agent's intelligent reasoning ability, the model can learn characteristics of student's personality, adaptively build a sort of teaching strategy which adapts to student, intelligently organize teaching process and lead student to study better and to exert more potential. In addition, the designing ideas of the model not only bring a leading role of teacher into play but also fully reflect cognitive main body of student. The key module in the model mentioned above is student model, which is basis for other modules to well work. However, now most of related researches are too complex to realize or easily implement but have little reasoning ability. Aiming at this kind of condition and combining the projects that the author has made in the field of distance education, the paper puts forward a multi-agent student model. The model involves the traits from four aspects of student and each aspect has an agent to reason its traits. By improving on Sherlock II method and adopting concept map and fuzzy theory, the author raises a new kind of reasoning way for every agent in the student model. These ways not only hold relatively good reasoning ability but also are easily realized. Moreover, the ways discussed in the paper are in possession of expansibility and can be generally used. By introducing the student model into student self-testing system, the author gets aseries of tables which show that the testing system with the student model takes on self-adaptation and can exactly infer student's cognitive level. And the tables demonstrate that the ways in the student model are feasible and correct. Therefore, the scheme discussed in the paper has strongly practical worthiness.