My research is situated at the intersection of AI in education, teacher professional development, and educational psychological assessment. It focuses on teachers’ AI-related technological pedagogical competences.

Artificial intelligence (AI) is widely regarded as one of the defining technologies for the future of teaching and learning. Whether AI actually supports learning processes, however, does not depend on technological possibilities alone, but on teachers’ professional competences to integrate AI into heterogeneous classroom contexts in pedagogically meaningful and adaptive ways that support learning.

Against this background, I investigate conditions for successful AI-integrated instruction from the perspective of teacher professional development. To this end, I develop theory-guided, scenario-based performance assessments that move beyond traditional self-report instruments and allow teachers’ AI-related technological pedagogical competences to be validly assessed in authentic instructional situations. For the scoring and analysis, I explore LLM-supported procedures that involve human expertise.

A further focus of my research lies in experimentally evaluated professional development approaches for fostering teachers’ AI-related competences in collaboration with teachers and school practice. Through my work, I aim to contribute to aligning the integration of AI in educational processes not with technological promises, but with empirical evidence, pedagogical responsibility, and the real support needs of teachers.