EduCOR: An Educational and Career-Oriented Recommendation Ontology
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by
Eleni Ilkou, Hasan Abu-Rasheed, Mohammadreza Tavakoli, Sherzod Hakimov, Gábor Kismihók, Sören Auer, Wolfgang Nejdl
2021
Abstract
With the increased dependence on online learning platforms and educational
resource repositories, a unified representation of digital learning resources
becomes essential to support a dynamic and multi-source learning experience. We
introduce the EduCOR ontology, an educational, career-oriented ontology that
provides a foundation for representing online learning resources for
personalised learning systems. The ontology is designed to enable learning
material repositories to offer learning path recommendations, which correspond
to the user's learning goals, academic and psychological parameters, and the
labour-market skills. We present the multiple patterns that compose the EduCOR
ontology, highlighting its cross-domain applicability and integrability with
other ontologies. A demonstration of the proposed ontology on the real-life
learning platform eDoer is discussed as a use-case. We evaluate the EduCOR
ontology using both gold standard and task-based approaches. The comparison of
EduCOR to three gold schemata, and its application in two use-cases, shows its
coverage and adaptability to multiple OER repositories, which allows generating
user-centric and labour-market oriented recommendations.
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