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.