Synopsis Paper: PhD Symposium

Higher education has long faced the challenge of integrating technological developments into teaching and learning. With generative AI, a new challenge emerges: AI does not merely provide or distribute content, but can intervene directly in knowledge construction, task completion or reflection processes, while also supporting learning through personalised pathways and dialogic interaction, and redistributing cognitive activity within a broader socio-technical system (Giannakos et al., 2024; Hutchins & Klausen, 1996; Stadler et al., 2024). Precisely because generative AI can intervene in central learning processes, it becomes increasingly important for students to remain active agents of their own learning by initiating, regulating, and evaluating learning in self-directed ways. At the same time, current research suggests that AI-supported learning requires pedagogical guidance in order to avoid superficial engagement, reduced mental effort, or merely performance-oriented gains without meaningful learning (Deng et al., 2025; Stadler et al., 2024).