Marie Hornberger

Dr. Marie Hornberger is a Researcher at the Department of Life Sciences Education within the School of Social Sciences and Technology at the Technical University of Munich (TUM). She has been working at TUM since 2022, focusing on AI literacy in higher education and teacher training in the field of artificial intelligence. Her research bridges psychology, education, and AI with practical applications for measuring and improving students' understanding of artificial intelligence.

Her primary research interests include:

• Development and validation of AI literacy assessment tools
• Higher education curriculum development for AI education
• Teacher training programs in artificial intelligence
• Psychological factors influencing AI adoption in educational settings
• International comparisons of AI literacy across educational systems

Dr. Hornberger's research program centers on creating reliable measurement instruments for AI literacy, with her team developing validated tests that work consistently across Germany, the UK, and the US. Her work examines how AI attitudes, interest levels, usage patterns, and foundational knowledge collectively shape students' confidence in working with AI technologies. She has made significant contributions to understanding the social and ethical dimensions of AI literacy beyond mere technical proficiency.

She is actively involved in several key research initiatives:

• Professional Learning Communities for Systematizing AI-Specific Study Programs at TUM
• Research Initiative Digital Education (RIDE), funded by the Joachim Herz Foundation
• Her doctoral project on measuring and promoting AI literacy in higher education
• KI-CP@TUM (AI Competence Project at TUM)

Dr. Hornberger regularly presents her findings at major educational research conferences including the Annual Conference of the Society for Empirical Educational Research in Germany, where she has shared insights on validating AI literacy tests for teacher training programs. Her collaborative work with international researchers demonstrates the growing importance of standardized approaches to measuring AI literacy across different cultural and educational contexts.