ODELO: an ontology-driven model for the evaluation of learning ontologies

Abstract

Trying out or updating an existing learning ontology and providing evaluation tools to assess its quality are essential steps before putting an e-learning system online. Ontology evaluation is a crucial task and it is usually the output of an automatic process. This paper proposes an ontology-driven model, called Ontology-Driven model for the Evaluation of Learning Ontologies (ODELO), for the evaluation of ontologies representing learning resources with respect to syntactic, semantic, pragmatic, social and cohesion metrics. Syntax deals with the formal relations between signs (e.g., words, phrases, sentences) and the production of new ones. Semantics is the study of the relationships between the system of signs and their meanings. Pragmatics is the study of natural language understanding. Social metrics reflect the fact that software agents and ontologies coexist and communicate in communities. Ontology cohesion metrics refer to the degree of relatedness of ontology classes. ODELO is a deductive evaluation model that identifies the elements of ontological quality for learning ontologies. In this paper we propose a framework for assessing the quality of learning ontologies, which constitute the basis for intelligent educational Adaptive Hypermedia (AH) systems. We introduce a new pragmatic quality metric for assessing the quality of learning ontologies.