Knowledge modeling for open adaptive hypermedia

Abstract

This paper proposes a knowledge modeling approach for adaptive, open corpus hypermedia systems. Our approach towards adaptive, open corpus hypermedia is based on interpreting standard metadata of learning objects. For each corpus of documents integrated into the open adaptive hypermedia system (OAHS) we are calculating subgraphs of the ontology for estimating the user's knowledge with respect to this corpus. This enables the OAHS to understand the knowledge contained in learning materials, to make estimations about an individual user's knowledge state and to learn the prerequisite knowledge required for learning objects from given structures in the materials. © 2002 Springer-Verlag Berlin Heidelberg.