Beyond Traditional Learning: The LLM Revolution in BPM Education at University

Marzena Grzesiak; Krzysztof Kluza; Natalia R. Potoczek; Leszek Szała

doi:10.1007/978-3-031-70445-1_29

Beyond Traditional Learning: The LLM Revolution in BPM Education at University

Abstract

Large Language Models (LLMs) significantly impact higher education, requiring changes in educational processes, especially in Business Process Management (BPM) practical exercises. The research aims to evaluate the effectiveness of LLMs in BPM education to determine if LLMs can supplement educators. The study involved 33 master’s degree students. Students’ works were manually evaluated and compared to LLM-generated responses. Results highlight the effectiveness and limitations of LLMs in supporting BPM education, revealing discrepancies between human and AI assessments. Our findings indicate that LLMs like ChatGPT-3.5 and ChatGPT-4o can aid BPM education, but their performance and reliability differ from traditional human grading. The findings underscore LLMs’ potential to offer additional perspectives and reduce educators’ workload. However, LLMs should be supplementary tools, not replacements for traditional methods. This exploration contributes to understanding the transformative role of LLMs in reshaping educational methodologies. Future research should consider larger samples and a broader range of tasks to validate and extend these findings.