Learning Objects' Architecture and Indexing in WELSA Adaptive Educational System

Abstract

In this paper we present an intelligent way of organizing learning material in an adaptive educational hypermedia system. We describe the use of instructional metadata which facilitates both the detection of student learning style and the application of various adaptation techniques. The advantage of our approach is that it is independent of a particular learning style model. Furthermore, the author has to supply only the annotated learning content (the static description) while the adaptation logic (the dynamic description) is provided by the system. The approach is implemented in an adaptive educational system called WELSA and illustrated with a course module in the area of Artificial Intelligence.