A Personalized CAI Courseware System

The network-based CAI (Computer Assisted Instruction) courseware system, Compared with the traditional one, has its advantages and disadvantages. After give an introduction to the ongoing development of distance learning and E-learning. This paper combined a hierarchical Level-Generate algorithm with the Data Mining theory, to provide the students with a personalized courseware system by building a CAI courseware tree. With courseware tree, the system can recommend useful materials to each student based on the performance of individual student. If the system computes the personality of each student, the complexity is higher and hard to implement. Thus, mining on students is necessary. Using Hamming distance theory, students were clustered into different groups based on the courseware they accessed.