Graph-Based Personalized Recommendation in Intelligent Educational Platforms: A Case Study in Engineering Education

Sofia Merino Costa, Rui Pinto, Gil Gonçalves

2025

Abstract

The fragmentation of digital learning materials in engineering education makes it difficult for students to find relevant content. This paper presents a graph-based recommender system integrated into an intelligent Knowledge Management System (KMS) to support personalized learning. Using Neo4j, the system models users, learning objects, and semantic relationships to generate contextualized recommendations across dashboard, module, and Learning Path (LP) views. Its scoring mechanism combines semantic similarity, interaction history, and graph proximity to provide adaptive, explainable suggestions. A mixed-methods evaluation with engineering students showed high alignment with user interests and positive perceptions of transparency and personalization. The system effectively transitioned from fallback to tailored recommendations as user interactions increased. Results highlight the potential of graph-based approaches to improve content relevance, discovery, and learner engagement in web-based educational platforms, in line with Education 5.0 principles.

Paper Citation

in Harvard Style

Costa S., Pinto R. and Gonçalves G. (2025). Graph-Based Personalized Recommendation in Intelligent Educational Platforms: A Case Study in Engineering Education. In Proceedings of the 21st International Conference on Web Information Systems and Technologies - Volume 1: WEBIST; ISBN 978-989-758-772-6, SciTePress, pages 439-446. DOI: 10.5220/0013830200003985

in Bibtex Style

@conference{webist25,
author={Sofia Costa and Rui Pinto and Gil Gonçalves},
title={Graph-Based Personalized Recommendation in Intelligent Educational Platforms: A Case Study in Engineering Education},
booktitle={Proceedings of the 21st International Conference on Web Information Systems and Technologies - Volume 1: WEBIST},
year={2025},
pages={439-446},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013830200003985},
isbn={978-989-758-772-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Web Information Systems and Technologies - Volume 1: WEBIST
TI - Graph-Based Personalized Recommendation in Intelligent Educational Platforms: A Case Study in Engineering Education
SN - 978-989-758-772-6
AU - Costa S.
AU - Pinto R.
AU - Gonçalves G.
PY - 2025
SP - 439
EP - 446
DO - 10.5220/0013830200003985
PB - SciTePress