Reasoning about learning object metadata for adapting SCORM courseware

In this work the problem of selecting and composing learning resources in the Semantic Web is considered. The starting point is the SCORM framework, used for the representation of learning objects. A proposal is done for describing a learning resource at the knowledge level, in terms of prerequisites and knowledge supplied, in order to enable the use of automated reasoning techniques (like planning) thus achieving forms of adaptation taken from the field of adaptive educational hypermedia. The description of learning strategies at the knowledge level opens the way to Semantic Web scenarios where learning resources are distributed over the network and reasoning systems can automatically select and compose them on-the-fly according to the user’s needs. The advantages are an increase of reuse of the resources and a greater openness.