Hamm-Lippstadt University of Applied Sciences (GERMANY)
About this paper:
Appears in: INTED2024 Proceedings
Publication year: 2024
Pages: 2298-2304
ISBN: 978-84-09-59215-9
ISSN: 2340-1079
doi: 10.21125/inted.2024.0634
Conference name: 18th International Technology, Education and Development Conference
Dates: 4-6 March, 2024
Location: Valencia, Spain
Teaching fundamentals of business process management (BPM) means first of all to support students to develop a structured view on business activities and an understanding of relationships of different tasks, which are necessary to implement and execute business processes. Business processes (BP) themselves can generally be defined as a sequence of tasks related to each other to achieve business goals (See Weilkiens et al. (2016), sec 3.1, for definition and characteristics of BP.). BPM with its elements analysing, modeling, and optimisation of business processes is a complex subject, and, for the conveyance of content, basic knowledge about business administration is required. In view of business process modeling, one crucial objective is to equip students with the skills to use modeling languages like Business Process Model and Notation (BPMN) or event-driven process chains (EPC) for a graphical representation of business processes and a basis for optimisation.

One promising new approach to support students’ acquisition of knowledge is embedding generative artificial intelligence (AI) to the learning process. Generative AI can then e.g. be used to produce text, images or videos (See Kanbach et al. (2023), p. 2.). With respect to BPM this is twofold, because on the one hand as the usage of AI in companies evolves (See e.g. Kanbach et al. (2023) for generative AI or Bharadiya (2023) for AI in general.), resulting changes have to be analysed and integrated in business processes. On the other hand, looking at universities and schools, generative AI leads to major changes in teaching and learning, including in the field of computer science, in particular in learning programming (See e.g. Brett et al. (2023), Lau/Guo (2023) or Ramazan et al. (2023)).

This contribution analyses the opportunities and challenges using generative AI in teaching BPM, in particular business process modeling. The target group are undergraduate students in a bachelor’s degree program focused on business administration. The application comprises the teaching content starting with classification of a business process, identification of possible participants of the process, analysis of goals and process structure and last, but not least, creating a graphical representation of processes using the modeling notation BPMN.

The principal questions are:
How can generative AI tools be used to support knowledge building and transfer?
What influence will this have on students’ competencies?
How will teaching content change in the long-term using generative AI?
Business process management, business process modeling, BPMN, generative artificial intelligence, genAI.