Educational process mining aims at leveraging data generated during students’ learning processes to extract evidence-based insights supporting the continuous improvements of educational programs. In this work, we showcase the application of educational process mining techniques to analyze students’ careers at an Italian university, focusing on their progression and outcomes. The study uncovers trends in compliance with curriculum requirements, exam-taking patterns and graduation times. Predictive models are then employed to elucidate the impact of different factors, e.g., the number of exams passed during the first year, on graduation times. These findings provide insights for educational institutions seeking support mechanisms to improve students’ success rates.
Evidence-Based Student Career and Performance Analysis with Process Mining: A Case Study / Potena, Domenico; Genga, Laura; Basta, Annalisa; Mercati, Chiara; Diamantini, Claudia. - 503 LNBIP:(2024), pp. 349-360. [10.1007/978-3-031-56107-8_27]
Evidence-Based Student Career and Performance Analysis with Process Mining: A Case Study
Potena, Domenico;Diamantini, Claudia
2024-01-01
Abstract
Educational process mining aims at leveraging data generated during students’ learning processes to extract evidence-based insights supporting the continuous improvements of educational programs. In this work, we showcase the application of educational process mining techniques to analyze students’ careers at an Italian university, focusing on their progression and outcomes. The study uncovers trends in compliance with curriculum requirements, exam-taking patterns and graduation times. Predictive models are then employed to elucidate the impact of different factors, e.g., the number of exams passed during the first year, on graduation times. These findings provide insights for educational institutions seeking support mechanisms to improve students’ success rates.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
