In the co-taught course Learning and Knowledge Sharing (5th semester, BA level), students are required to design and conduct an empirical investigation throughout the semester. The focus is on knowledge organisation, knowledge sharing, and/or learning within a specific, self-selected organisation or context, which serves as the empirical case. To support this case-based inquiry, previous iterations of the course have introduced a range of thematic sessions addressing key methodological concerns: What constitutes a well-formulated research question? What is a research design, and how is data collection managed? Which analysis methods are appropriate? How should findings be presented? 

In the current iteration, we have chosen to integrate structured activities in which students engage with AI as both a collaborative partner and methodological tool across various phases of the research process. These include iterative refinement of research questions, literature discovery, initial drafting of interview guides, and document analysis. Central to these activities is an iterative and reflective engagement with AI-generated outputs, where students are encouraged to critically assess the relevance and validity of the output, and to experiment with prompting strategies to enhance the quality and applicability of the results. 

This webinar presents the design of these AI activities and shares preliminary insights from both teacher and student perspectives with a focus on pedagogical implications and methodological considerations.