Research And Design Of Computer Assisted Instruction System Based On Data Mining

With the rapid development of computer technology and urgently needed for improving the quality of instruction, increasingly importance has been attached to the applying of Computer Assisted Instruction (CAI) system.Because of lots of flaw existing in traditional CAI system, the voices calling for remedying defects of CAI system, promoting it more intellectualized and individualized are increasingly rising, for a time, many kinds of new technologies are utilized to CAI system.This thesis provides a new method which applies data mining technology in CAI system, offers a complete set of processes for realizing this system. It gives a scientific method for the development of CAI system to intellectualization and individualization.For achieving our system aim, this thesis put forward a Chinese segmentation approach using dictionary created by ourselves. Using this method, it can extract knowledge point information automatically from text material such as test questions, courseware. Therefore, it is possible to realize intellectualization and individualization of our system.In order to meet the need of system, decrease the run time and storage space, this thesis improves FP-growth algorithm in association rules algorithm and provides complete frequency FP-tree algorithm. This algorithm doesn't need elements of items to sort according to the number of times they appear. By modifying the tree, it makes the tree contain frequent items only. A CAI system based on data mining is developed in our campus network. This system integrates practice, learning, testing and teaching evaluation. First of all, the system extracts information from text material of databank using Chinese segmentation approach with dictionary created by ourselves. Secondly, all operations such as practice, test and teaching evaluation are performed using knowledge point information. Using complete FP-tree algorithm, the system performs association analysis about the relations between knowledge point and test scores, knowledge point themselves, teachers and student's level of accomplishment, and then obtains results like as courses emphases, partial ordering relation between knowledge points, quality of teaching etc. Finally, it offers learning material for practices to realize individualized study in terms of practice results.