Intelligent Tutoring System Research And Development, Based On Data Mining Technology

The Intelligent Tutoring System (Intelligent Tutoring System,called ITS for short) is a knowledge-based teaching system that applicate the artificial intelligence technology, such as the expert systems, problem solving, machine learning and so on, to the computer teaching ,it has largely make up for the blind spots and blanks of the existing teaching system.The research object of this paper is the data mining technology based intelligent tutoring system, which can mine more or more valuable resources from variety of online intelligent tutoring systems to facilitate its application or restructuring them, use of data mining technology to enhance the services initiative of the intelligent tutoring system, and enrich the teaching resource library to the maximum extent, so the intelligent Tutoring system technology can better serve for the modern educational. In this paper, as the Apriori algorithm may produce a large number of candidate sets and may need to repeat scans the database to identify, this paper study and proposed an improved association rules mining method. First, find all frequent sets, the emergence frequency of these items sets should at least the same as the predefined minimum support degree. Then generate the strong associated rules by the frequency sets, these rules must satisfy the minimum support degree and credibility degree. Then use the frequency set find in step 1 to produce the desired rule to generate all the rules that only contain a collection sets of items, each rules only including one in its right..here we use the middle definition of the rules. Once these rules are generated, only those whose credibility degree are greater than the user-specified minimum confidence can stay. In order to generate all frequent sets, we used the recursive method.Based on this algorithm, we research and developed an application example-Elective course system. In this paper the course-selection system development based on J2EE platform is developed. The course-selection system adopts a three-layers construction: The first layer is the Customer Layer, which only needs to install browser to interact with customers; The second layer is the Service Layer, and it uses J2EE techniques. The service layer is divided into two parts (expression part and business-logic part). The expression part uses the JSP technique and the business-logic part uses the EJB technique, which can decrease combination of two layers and make assurance of expansibility and reliability for the system. The third layer is the Data Source Layer. It can use any relational databases. In this paper Mysql is used, and the second layer uses the JDBC to interact with the Data Source.