The workshop begins with a central question: when does an AI assistant genuinely support teaching—and when does it not? Participants share AI-based solutions they have created or experimented with and analyse them together with colleagues, focusing on whether the feedback provided is relevant, whether the mode of use feels fair to students, and where ethical boundaries emerge. During the practical session, participants design an AI assistant for their own course that qualifies as a teaching assistant and can be used in a transparent and well-justified manner. Various tools (e.g. NotebookLM, HeyGen, GPTEdu) are explored to understand not only how to use them, but why—and whether—they should be integrated into teaching practice at all. The lecture component situates these practical experiences within a broader framework, addressing the role of AI in academic teaching, the boundaries of responsibility and authorship, and the importance of open dialogue with students when establishing agreements around AI use.
Target group: University teaching staff
Learning outcomes by the end of the training, participants will be able to:
- design an AI assistant for their course that qualifies as a teaching assistant;
- critically evaluate whether an AI assistant provides relevant and pedagogically sound feedback;
- engage in open dialogue with students about the scope and ethics of AI use in their course;
- create learning materials using NotebookLM, HeyGen, and GPTEdu;
- make informed decisions about whether—and in what form—such solutions should be used in their teaching.