Ontology for Educational Recommendation System in an Immersive Environment

• Yuri O. Magalhães UECE
• Ana Luiza B. P. Barros UECE
• Robson G. F. Feitosa UECE
• Thiago L. Matos UECE
• Claudio Fortier IREDE
• Antônio B. Serra IREDE
• Gustavo A. L. Campos UECE

DOI: https://doi.org/10.5753/eniac.2025.11842

Abstract

Educational Recommendation Systems (ERS) face challenges in evaluating student behavior and performance, aiming to generate personalized learning suggestions. This paper proposes an ontology designed to support ERS in immersive learning environments. The ontology models key elements such as student interactions, learning materials, and competencies. As part of the validation process, an automatic script was developed to generate ontology instances, and SPARQL queries were executed to simulate interaction scenarios. The results include the defined ontology taxonomy and a demonstration of how its structure can represent adaptive learning contexts.

References

Bobadilla, J., Ortega, F., Hernando, A., and Gutiérrez, A. (2013). Recommender systems survey. Knowledge-based systems, 46:109–132.

Bouihi, B. and Bahaj, M. (2017). An ontology-based architecture for context recommendation system in e-learning and mobile-learning applications. In 2017 International Conference on Electrical and Information Technologies (ICEIT), pages 1–6.

Felder, R. M. and Silverman, L. K. (1988). Learning and teaching styles in engineering education. Engineering Education, 78:674–681.

George, G. and Lal, A. M. (2019). Review of ontology-based recommender systems in e-learning. Computers & Education, 142:103642.

Gligorea, I., Cioca, M., Oancea, R., Gorski, A.-T., Gorski, H., and Tudorache, P. (2023). Adaptive learning using artificial intelligence in e-learning: A literature review. Educ. Sci., 13:1216.

Gruber, T. R. (1995). Toward principles for the design of ontologies used for knowledge sharing? International Journal of Human-Computer Studies, 43(5):907–928.

Hey, T., Tansley, S., and Tolle, K. (2009). The fourth paradigm: Data-intensive scientific discovery.

Morgado, L., Torres, M., Beck, D., Torres, F., Almeida, A., Simões, A., Ramalho, F., and Coelho, A. (2022). Recommendation tool for use of immersive learning environments. In 2022 8th International Conference of the Immersive Learning Research Network (iLRN), pages 1–8.

Musen, M. A. (2015). The protégé project: a look back and a look forward. AI Matters, 1(4):4–12.

Noy, N. F., McGuinness, D. L., et al. (2001). Ontology development 101: A guide to creating your first ontology.

Park, D. H., Kim, H. K., Choi, I. Y., and Kim, J. K. (2012). A literature review and classification of recommender systems research. Expert systems with applications, 39(11):10059–10072.

Peng, H., Ma, S., and Spector, J. M. (2019). Personalized adaptive learning: an emerging pedagogical approach enabled by a smart learning environment. Smart Learning Environments, 6:9.

Rawat, B. and Dwivedi, S. K. (2017). An architecture for recommendation of courses in e-learning system. Int. J. Inf. Technol. Comput. Sci.(IJITCS), 9(4):39–47.

Ricci, F., Rokach, L., and Shapira, B., editors (2022). Recommender Systems Handbook. Springer-Verlag New York Inc., 3rd edition.

Sakr, A. and Abdullah, T. (2024). Virtual, augmented reality and learning analytics impact on learners, and educators: A systematic review. Education and Information Technologies, pages 1–50.

Silva, F. L. d., Slodkowski, B. K., Silva, K. K. A. d., et al. (2023). A systematic literature review on educational recommender systems for teaching and learning: research trends, limitations and opportunities. Educational Information Technology, 28:3289–3328.

Sin, Z. P., Jia, Y., Wu, A. C., Zhao, I. D., Li, R. C., Ng, P. H., Huang, X., Baciu, G., Cao, J., and Li, Q. (2023). Towards an edu-metaverse of knowledge: Immersive exploration of university courses. IEEE Transactions on Learning Technologies.

Staab, S. and Studer, R., editors (2009). Handbook on Ontologies. International Handbooks on Information Systems. Springer-Verlag Berlin Heidelberg.

Stancin, K., Poscic, P., and Jaksic, D. (2020). Ontologies in education – state of the art. Education and Information Technologies, 25:5301–5320.

Tarus, J. K., Niu, Z., and Mustafa, G. (2018). Knowledge-based recommendation: a review of ontology-based recommender systems for e-learning. Artificial Intelligence Review, 50(1):21–48.