Abstract:
This article explores the requirements for a process-oriented quality management system (QMS) at German higher education institutions and examines the potential of artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT, to support process modeling and quality assurance. It addresses the growing importance of data-driven management systems amid increasing regulatory demands, rising process complexity, and diverse stakeholder expectations. The paper outlines core components of process-based QMS, common implementation challenges, and how AI-powered tools can enhance efficiency, knowledge integration, and curriculum development. An empirical analysis investigates ChatGPT’s use for generating BPMN models, highlighting technical limitations and conceptual challenges, while reflecting on its transformative potential in higher education.
Über die Autor*innen:
- Anastasia Hermann,
Prof. Dr., Prorektorin Qualität der Lehre und Professorin für Personalmanagement, IU Internationale Hochschule - Thomas Knöpfle
Dr., Manager für Qualität und Prozesse, IU Internationale Hochschule - Janina Belz
Stellvertretende Leitung Zentrales Akademisches Qualitätsmanagement und Qualitätsmanagementbeauftragte, IU Internationale Hochschule
