EduCOR: An Educational and Career-Oriented Recommendation Ontology

TL;DR

EduCOR is a comprehensive ontology designed to enhance online learning platforms by enabling personalized, career-oriented recommendations based on user goals, psychological factors, and labor market needs.

Contribution

The paper introduces EduCOR, a novel ontology that unifies educational and career-oriented resource representation for personalized learning systems.

Findings

EduCOR demonstrates high coverage and adaptability across multiple open educational resource repositories.

The ontology effectively supports personalized learning path recommendations.

Application on the eDoer platform shows improved recommendation relevance.

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.