We conduct research on the intersection between digital entrepeneurship, digital ecosystems, and organizing data and knowldedge. We will provide multiple courses that help to explain changes on firm- and ecosystem levels using multiple theories and methodologies. Our teaching is usually highly interactive and builds upon concepts of blended learning, oftentimes 'flipping the classroom'. It is important to us to not only reflect latest findings of information systems research with our students but also to work together on applying that knowledge.

We are implementing a new policy to ensure transparency and clarity in the creation of student works, especially those involving Large Language Models (LLMs) like GPT. This policy applies to all works, including seminar papers, thesis, and project reports, and is designed to foster academic integrity, rigor, and replicability in your research.

Key Changes:

1. All works must present a clear and transparent account of the methods and tools used in their creation. This includes documenting any use of AI or LLMs in the process.
2. When LLMs are used, students are required to submit the complete chat history. This includes both the prompts given to the LLM and its responses. Students should ensure that they use a single chat session, save it in its entirety, and send it separately along with their work. This will provide a comprehensive record of how the work was generated.
3. In the methods chapter of your work, there must be a specific sub-chapter detailing the tools and methods used to support your writing and study. This is to ensure that all methods, including AI-based tools, are fully explained and their role in the creation process is clear.