Learning Links: reusable assets with support for vagueness and ontology-based typing

Existing approaches to ontological support in courseware are focused on the annotation of hypermedia nodes or contents, while links are described only by classifying them into a set of predefined types. In this work, we describe the concept of Learning-Link as an independent and reusable learning resource that can be annotated with terms defined in a link ontology. The computational semantics of that ontology, combined with fuzziness to specify graded relations, enables the implementation of extended adaptive behaviors that entail inferences and approximate reasoning.