Adaptation in Educational Hypermedia Based on the Classification of the User Profile

This paper presents SEDHI – an adaptive hypermedia system for a web-based distance course. The system architecture includes three main modules: the Classification Module, the Student Module, and the Adaptation Module. SEDHI classifies the students according to profiles that were defined based on a statistical study of the course user and usage data, and adapts the navigation using the techniques of link hiding and link annotation. The results of an evaluation of the SEDHI prototype show the potential of the classification and adaptation approach.