Roy Pea
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Roy Pea is David Jacks Professor of Education & Learning Sciences at Stanford University, School of Education, and Computer Science. His studies and publications in the learning sciences focus on advancing theories, research, tools and social practices of technology-enhanced learning of complex domains. He is also founder and Director of Stanford’s PhD program in Learning Sciences and Technology Design. He is a Fellow of the American Academy of Arts and Sciences, National Academy of Education, Association for Psychological Science, the American Educational Research Association, and the Center for Advanced Study in the Behavioral Sciences.
Roy Pea joins the Paris IAS in April 2026 for a one-month writing residency.
Research topics
STEM Learning; Computer-Supported Collaborative Learning; Virtual Learning Environments; Mobile Learning; AI in Education.
Defining new literacies and education practices for distributed intelligence in a Generative AI era
This project examines the implications of "distributed intelligence" in a Generative AI era for children’s learning goals and development of related competencies. Much of the life course agenda involves learning how to master and to design distributed intelligence employing the material, social, and symbolic resources outside one’s mind. Generative AI is an extraordinarily powerful new tool for achieving distributed intelligence, changing the division of labor between humans and machines, but with what implications for the aims of education and children's learning?
The research project critically analyzes and synthesizes valuable elements from concepts and frameworks that are being written about and studied empirically in relation to these emerging challenges and opportunities, such as "AI literacy", "critical computational literacy", "critical AI literacy", and "critical algorithmic literacy". For thinking about human learning and such literacies, it will examine what it means for learners to develop and sustain autonomy in the face of the widespread consequences of datafication and algorithms undergirding ubiquitous AI-driven information environments in society. Recommendations will be developed for fostering learner autonomy-supportive AI systems and advancing core elements of critical algorithmic literacies for education. This work encompasses philosophical, developmental, educational, learning sciences, AI, HCI, computer science, behavioral economics, STS, and policy literatures. We need to take a practice perspective to theorize, investigate, and promote emerging critical literacies encompassing Generative AI as new components of distributed intelligence for any person's cultural activities.
Key publications
Hannele Niemi, Roy Pea, Yu Lu. (Eds.). AI in Learning: Designing the Future. Springer Nature. Springer Nature, 2023.
Shuchi Grover, Roy Pea. "Computational thinking in K–12: A review of the state of the field". Educational researcher, 42(1), 38-43, 2013.
Roy Pea. "Practices of distributed intelligence and designs for education". In Gavriel Salomon (Ed.). Distributed cognitions (pp. 47-87). New York, Cambridge University Press, 1993.
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