PLATFORM FOR RECOMMENDATIONS OF SELECTIVE EDUCATIONAL COMPONENTS USING THE ONTOLOGICAL METHOD
Keywords:
ontology, semantic model, historical dataAbstract
The paper proposes an approach to building a personalized recommendation system for elective academic components based on ontology. The developed ontology describes the relationships between students, courses, knowledge categories, preferences, and grades. A semantic model is used to compute the similarity between student profiles and course characteristics. The system also incorporates historical academic data and course ratings to generate adaptive learning recommendations. A mathematical model integrates content-based and collaborative filtering techniques to personalize learning paths in higher education.
References
Гасевич Д., Йованович Й., Хатала М. Ontologies for learning content: Extraction and automated knowledge modeling // Educational Technology & Society. – 2009. – Т. 12, № 4. – С. 27–39.
Тарус Дж. К., Ню З., Юсіф А. Гібридна система рекомендацій для e-learning на основі онтології та послідовного аналізу шаблонів // Future Generation Computer Systems. – 2017. – Т. 72. – С. 37–48. – DOI: https://doi.org/10.1016/j.future.2017.02.049.
Амане М., Айссауї К., Беррада М. ERSDO: E-learning Recommender System based on Dynamic Ontology // Education and Information Technologies. – 2022. – Т. 27. – С. 7549–7561. – DOI: https://doi.org/10.1007/s10639-022-10914-y.
