Automatic Re-Organization of Group-Wised Web Courseware

With the increasing popularity of the Internet, there is a growing demand for web-based education, which allows students to study and learn at their own pace over the Internet. However in order to improve the teaching quality, such systems should be able to adapt the teaching in accordance with individual students’ ability and progress. Focusing on this objective, this paper proposes a new method to construct group-wised courseware by mining both context and structure of the courseware to build personalized Web tutor trees. To this end, the concept of Web tutor units and the notion of similarity are presented. Five algoriths, including the Naive Algorithm for tutor concept tree and the Level-generate Algorithm to generate Web tutor units of K+1 levels, are proposed. Experimental results are presented to demonstrate the effectiveness of the new method.