@inproceedings{169d3a710d4c4a83a9f3937117e2381d,
title = "Process Mining on Curriculum-Based Study Data: A Case Study at a German University",
abstract = "On their trajectory through educational university systems, students leave a trace of event data. The analysis of that event data with a process lens poses a set of domain-specific challenges that is addressed in the field of Educational Process Mining (EPM). Despite the vast potential for understanding the progress of students and improving the quality of study programs through process mining, a case study based on an established process mining methodology is still missing. In this paper, we address this gap by applying the state-of-the-art process mining project methodology (PM2 ) in an EPM case study with a focus on student trajectory analysis at a German university. We found that process mining can create actionable items to improve the quality of university education. We also point out domain-specific challenges, like handling reoccurring exams (retaken after failing) for future research in EPM. Finally, we observe insights of some value in our case.",
keywords = "Case study, Curriculum mining, Educational Process Mining",
author = "Richard Hobeck and Luise Pufahl and Ingo Weber",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s).; International Workshops on EDBA, ML4PM, RPM, PODS4H, SA4PM, PQMI, EduPM, and DQT-PM, held at the International Conference on Process Mining, ICPM 2022 ; Conference date: 23-10-2022 Through 28-10-2022",
year = "2023",
doi = "10.1007/978-3-031-27815-0_42",
language = "English",
isbn = "9783031278143",
series = "Lecture Notes in Business Information Processing",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "577--589",
editor = "Marco Montali and Arik Senderovich and Matthias Weidlich",
booktitle = "Process Mining Workshops - ICPM 2022 International Workshops, Revised Selected Papers",
}