E-Learning resource reuse, based on bilingual ontology annotation and ontology mapping

Abstract

Semantic annotation of e-Learning resources is very important for successful finding or recommendation of the most suitable ones for specific learning goals or learners. Significant research has done recently on usage of ontologies to improve learning, but most of developed ontologies are the only English language labelled and describe learning only from a specific point of view. Usage of bilingual and multilingual ontologies for resource annotation could make interlingual content delivery and reuse in e-learning more effective. It also can make learning content adaptable for a much wider audience. In this paper, we present an approach for the annotation of e-Learning resources, based on a mapped system of bilingual ontologies. We propose a knowledge-based flexible and easily extensible knowledge model and discuss how knowledge-based system, implemented this model can be used for comparison of resources, using ontology mapping. As e-Learning is complex domain that mixes pedagogy, psychology, scientific and presentation subdomains, modelling this domain is very difficult tack. We believe that relatively independent modelling of all the subdomains and specifying relations between them is the most promising approach. Our ontological model aims to ensure strict separation of different type knowledge, used in the learning process (pedagogical from domain-specific, general from domain-specific, linguistic from semantically–rich). This can simplify the ontology building process, ontology reuse, ontology evaluation, and also comparison of e-Learning systems, annotated by ontologies, following this