Ontology for Automated Qualitative Analysis in Higher Education Course Evaluations

• Eulanda Maria Pedro Daniel Federal University of Rio Grande do Sul (UFRGS) http://orcid.org/0009-0002-1296-2533
• Leandro Krug Wives Federal University of Rio Grande do Sul (UFRGS) https://orcid.org/0000-0002-8391-446X
• Alexandra Lorandi Federal University of Rio Grande do Sul (UFRGS) https://orcid.org/0000-0002-9583-9399
• José Palazzo Moreira de Oliveira Federal University of Rio Grande do Sul (UFRGS) https://orcid.org/0000-0002-9166-8801

DOI: https://doi.org/10.5753/sbbd_estendido.2025.247564

Abstract

This work presents the development and application of ontology to represent teacher and student evaluation data in Computer Science courses. The proposal structures evaluation criteria, comments, scores, and sentiments extracted through Natural Language Processing (NLP). Using OWL and the Protégé tool, the ontological base was built with real data from a public university in southern Brazil. Sentiment analysis, performed with the LeIA model in Python, enabled the identification of patterns that support the improvement of educational quality. The approach proved effective in organizing and extracting educational knowledge.

Keywords: Ontologies, Qualitative Analysis, Higher Education, Evaluation

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