Samuel Greiff

Professor of Educational Psychology & Artificial Intelligence

Curriculum vitae


Department of Educational Psychology

Goethe-University Frankfurt


Artificial Intelligence in Education (AI Ed) represents a dynamic and burgeoning research field that explores innovative ways to enhance learning processes across different levels. Current research efforts look at the potential of AI to better understand educational processes and how AI can be integrated into existing educational systems.
On the micro-level, AI Ed caters to individual student needs by offering personalized learning experiences, adapting content, and providing real-time feedback and scaffolding, thereby fostering a more student-centric approach to education. At the meso-level, AI can aid teachers in individual classrooms or entire educational institutions in streamlining student support, administrative tasks, optimizing resource allocation, and enhancing operational efficiency, contributing to an overall improvement in the institutional ecosystem. On the macro-level, the employment of AI towards educational systems, for instance in large-scale assessments such as PISA and PIAAC,  facilitates data-driven policymaking, enabling education authorities to make informed decisions for large-scale improvements in curriculum design, teacher training, and infrastructure development.
Continuous exploration of AI's potential is poised to revolutionize education as we know it today. In this regard, I am involved in several projects related to AI Ed, such as OECD’s project on AI in Education or Alef Education. Alef Education develops a smart learning platform that integrates AI and data analytics to offer personalized and adaptive learning experiences for students, targeted support for tracking progress and flagging relevant support, and institutional monitoring of general developments of learning across different grade levels. I am excited to contribute to the highly volatile field of AI Ed with the aim to improve traditional teaching methods, making education more accessible, adaptive, and effective, and in addressing diverse learning needs.
As the field evolves, the interdisciplinary nature of AI Ed research involves collaboration among computer scientists, educators, psychologists, and policy experts. I have been fortunate to work on these topics with a number of great colleagues from across the globe like Ryan Baker, Gautam Biswas, Nia Dowell, Marjolein Fokkema, Dragan Gasevic, Art Graesser, Dirk Ifenthaler, Miguel Nussbaum, Valerie Shute, George Siemens, or Barbara Wasson (just a random list – please don’t feel excluded if we work together and I didn’t list you :-)).

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