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OntoSBehaviour: An Ontology of Students’ Behaviours at Institutions of Higher Learning

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Electronic Government and the Information Systems Perspective (EGOVIS 2023)

Abstract

Students who enter Universities, came from different demographics, cultural and socio-economic backgrounds. These factors contribute to the students’ adjustment in the new environment and academic success. Institutions of higher education need automated systems to predict manage and monitor students’ behaviours to aid academic success. However, students’ behaviours in higher education institution environments have not yet been formalized to enable machine understanding for automated processing. To address this shortcoming, this study has developed an ontology of students’ behaviours at institutions of higher learning, namely, OntoSBehaviour. Data was collected from secondary sources including websites, published research articles and reports, related taxonomies and ontologies, and various theories that describe human behavior. The collected data was used to formalized the OntoSBehaviour ontology in logic-based syntaxes. The OntoSBehaviour ontology was further implemented in a machine readable form in Web Ontology Language (OWL) and successfully evaluated for consistency and competency with the HermiT reasoner and SPARQL queries within Protégé. The resulting OntoSBehaviour ontology is a formal machine readable representation of students’ behaviours that can be leveraged in web-based applications to provide higher education institutions with relevant data for the automatic prediction, planning, management and monitoring of students’ academic activities and performance to aid their academic success.

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Correspondence to Jean Vincent Fonou-Dombeu .

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Ramnanan, M., Fonou-Dombeu, J.V. (2023). OntoSBehaviour: An Ontology of Students’ Behaviours at Institutions of Higher Learning. In: Kö, A., Francesconi, E., Asemi, A., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Electronic Government and the Information Systems Perspective. EGOVIS 2023. Lecture Notes in Computer Science, vol 14149. Springer, Cham. https://doi.org/10.1007/978-3-031-39841-4_3

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  • DOI: https://doi.org/10.1007/978-3-031-39841-4_3

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