Identificação de pontos críticos na estrutura curricular do curso de Ciência da Computação da UFC utilizando mineração de processos

Abstract

Academic dropout is one of the main challenges faced by Higher Education Institutions, impacting both students’ trajectories and institutional efficiency. In this study, the Process Mining technique, specifically conformance analysis via replay, was used to investigate the curricular structure of the Computer Science program at UFC - Quixadá Campus. The curriculum modeling was conducted using Petri Nets, enabling a formal representation of students’ academic flows. By executing the replay on academic records, quantitative metrics were extracted, allowing the identification of student progression patterns and critical points that may influence dropout rates. Additionally, a web tool was developed for interactive visualization of the results, enabling detailed analyses by cohort and period. The findings highlight courses with the highest accumulation of academic non-conformities.