About

Roy Pea is the David Jacks Professor of Education and Learning Sciences at Stanford University, serving in the School of Education, and holds a courtesy appointment in Computer Science. He has been the Director of the H-STAR Institute at Stanford. 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 Co-Director and Co-PI of the NSF-funded LIFE Center, which aimed to develop and test principles about the social foundations of human learning in both informal and formal environments, with the goal of enhancing human learning from infancy to adulthood. Roy Pea is also the founder and Director of Stanford’s PhD program in Learning Sciences and Technology Design. His work includes co-authoring the 2010 National Education Technology Plan for the US Department of Education, and editing influential books such as Mirrors of Minds, Video Research in the Learning Sciences, Learning Analytics in Education, The Routledge Handbook of the Cultural Foundations of Learning, and AI in Education. Additionally, he is a co-author of the National Academy of Sciences books How People Learn and Planning for Two Transformations in Education and Learning Technology. Pea is a Fellow of the American Academy of Arts and Sciences, the National Academy of Education, the Association for Psychological Science, the American Educational Research Association, the Center for Advanced Study in the Behavioral Sciences, and the International Society of the Learning Sciences, of which he was the inaugural Fellow and served as President from 2004-2005. His research focuses on the social and technological foundations of learning, emphasizing the development of theories, tools, and social practices that support complex learning in diverse environments.

Research topics

• Sociology
• Psychology
• Computer Science
• Political Science
• Cognitive science
• Pedagogy
• Systems engineering
• Law
• World Wide Web
• Internal medicine
• Philosophy
• Epistemology
• Medicine
• Engineering
• Multimedia
• Human–computer interaction
• Medical emergency
• Public relations
• Physical therapy
• Data science

Selected publications

• DraftMarks: Enhancing Transparency in Human-AI Co-Writing Through Interactive Skeuomorphic Process Traces

  2026-04-13

  articleOpen access

  As generative AI becomes part of everyday writing, questions of transparency and productive human effort are increasingly important. Educators, reviewers, and readers want to understand how AI shaped the process. Where was human effort focused? What role did AI play in the creation of the work? How did the interaction unfold? Existing approaches often reduce these dynamics to summary metrics or simplified provenance. We introduce DraftMarks, an augmented reading tool that supports readers in interpreting how text was constructed with AI through familiar physical metaphors. DraftMarks employs skeuomorphic encodings such as eraser crumbs to convey the intensity of revision, and masking tape or smudges to mark AI-generated content, simulating the process within the final written artifact. By using data from writer-AI interactions, DraftMarks’ algorithm computes various collaboration metrics and writing traces. Through a formative study, we identified computational logic for different readership, and evaluated DraftMarks through a Prolific study for its effectiveness in assessing AI co-authored writing.

  PublisherDOI

• AI in the Writing Process: How Purposeful AI Support Fosters Student Writing

  ArXiv.org · 2025-06-25

  preprintOpen access

  The ubiquity of technologies like ChatGPT has raised concerns about their impact on student writing, particularly regarding reduced learner agency and superficial engagement with content. While standalone chat-based LLMs often produce suboptimal writing outcomes, evidence suggests that purposefully designed AI writing support tools can enhance the writing process. This paper investigates how different AI support approaches affect writers' sense of agency and depth of knowledge transformation. Through a randomized control trial with 90 undergraduate students, we compare three conditions: (1) a chat-based LLM writing assistant, (2) an integrated AI writing tool to support diverse subprocesses, and (3) a standard writing interface (control). Our findings demonstrate that, among AI-supported conditions, students using the integrated AI writing tool exhibited greater agency over their writing process and engaged in deeper knowledge transformation overall. These results suggest that thoughtfully designed AI writing support targeting specific aspects of the writing process can help students maintain ownership of their work while facilitating improved engagement with content.

  PublisherOA PDFDOI

• In memoriam - Nora Sabelli: Master orchestrator of grant programs and mentor for advancing the interdisciplinary learning sciences field

  Journal of the Learning Sciences · 2025-01-01

  articleCorresponding

  On Friday, September 6, 2024, the learning sciences field lost a giant in Dr. Nora Sabelli, 87 years old, a personal mentor to many researchers and an inspiration to so many learning scientists and STEM leaders. Nora’s first professional career was as a computational chemist, and later she became a passionate leader in research for improving STEM education. Nora’s time as a senior program officer at the National Science Foundation’s (NSF) Education and Human Resources (EHR) directorate was legendary; she was a force of nature who reshaped funding priorities for stronger science and a stronger connection of science to education practice.

  PublisherDOI

• How AI Companions shape learner’s socio-emotional learning and metacognitive development

  AI & Society · 2025-11-28

  articleOpen accessSenior author

  AI Companions, powered by large language models, are increasingly embedded in learners’ daily lives. Originally designed for entertainment and wellness, these systems are now used by students to regulate stress, reflect on themselves, and support their studies. Yet little is known about how learners experience these tools or what outcomes they associate with their use. To address this gap, we conducted a retrospective survey of 1,006 adult learners who had used the AI Companion Replika for at least 1 month. Participants reported on self-awareness, stress regulation, exam preparation, help-seeking behaviors, communication with others, and perceived extensions of self. Findings indicate that many learners use Replika as a low-friction, always-available support that can facilitate emotional regulation, self-reflection, and study practices. Others described changes in communication patterns and help-seeking, with mixed implications for social and academic relationships. These results suggest that AI Companions may intersect with core domains of socio-emotional learning, metacognition, and learner agency, raising both opportunities and challenges for educational practice and research.

  PublisherOA PDFDOI

• AI in the Writing Process: How Purposeful AI Support Fosters Student Writing

  Lecture notes in computer science · 2025-01-01 · 3 citations

  book-chapter
  PublisherDOI

• Script&Shift: A Layered Interface Paradigm for Integrating Content Development and Rhetorical Strategy with LLM Writing Assistants

  ArXiv.org · 2025-02-15

  preprintOpen access

  Good writing is a dynamic process of knowledge transformation, where writers refine and evolve ideas through planning, translating, and reviewing. Generative AI-powered writing tools can enhance this process but may also disrupt the natural flow of writing, such as when using LLMs for complex tasks like restructuring content across different sections or creating smooth transitions. We introduce Script&Shift, a layered interface paradigm designed to minimize these disruptions by aligning writing intents with LLM capabilities to support diverse content development and rhetorical strategies. By bridging envisioning, semantic, and articulatory distances, Script&Shift's interactions allow writers to leverage LLMs for various content development tasks (scripting) and experiment with diverse organization strategies while tailoring their writing for different audiences (shifting). This approach preserves creative control while encouraging divergent and iterative writing. Our evaluation shows that Script&Shift enables writers to creatively and efficiently incorporate LLMs while preserving a natural flow of composition.

  PublisherOA PDFDOI

• Constructions of Feasibility within Expansive Designs for Justice with Communities

  Proceedings. · 2025-06-10

  articleOpen access

  Design-based research (DBR) has served as an important methodological building block for researchers interested in working with communities to envision equitable possibilities for learning, particularly ones that differ from the status quo.Especially within these expansive design contexts, feasibility is a thorny issue precisely because it has historically been leveraged as a rigid, objective means to delimit what is possible in the world as it is, as opposed to what it could be.At the same time, we cannot ignore issues of feasibility if our goal is to realize expansive designs in real learning environments.This symposium brings together five papers across different phases of DBR and collectively illustrate a conception of feasibility that is dynamic, contextual, and contested.We design this symposium specifically to engage the learning sciences community about how such conceptions of feasibility can open up expansive possibilities for design.

  PublisherOA PDFDOI

• Advancing Quantum Information Science Pre-College Education: The Case for Learning Sciences Collaboration

  ArXiv.org · 2025-08-01

  preprintOpen access

  As quantum information science advances and the need for pre-college engagement grows, a critical question remains: How can young learners be prepared to participate in a field so radically different from what they have encountered before? This paper argues that meeting this challenge will require strong interdisciplinary collaboration with the Learning Sciences (LS), a field dedicated to understanding how people learn and designing theory-guided environments to support learning. Drawing on lessons from previous STEM education efforts, we discuss two key contributions of the learning sciences to quantum information science (QIS) education. The first is design-based research, the signature methodology of learning sciences, which can inform the development, refinement, and scaling of effective QIS learning experiences. The second is a framework for reshaping how learners reason about, learn and participate in QIS practices through shifts in knowledge representations that provide new forms of engagement and associated learning. We call for a two-way partnership between quantum information science and the learning sciences, one that not only supports learning in quantum concepts and practices but also improves our understanding of how to teach and support learning in highly complex domains. We also consider potential questions involved in bridging these disciplinary communities and argue that the theoretical and practical benefits justify the effort.

  PublisherOA PDFDOI

• Critical Algorithmic Literacy for LLM-assisted Decision-making

  Proceedings. · 2025-06-10

  articleOpen accessSenior author

  In today's information landscape, algorithm-driven technologies mediate nearly all aspects of information and communication, profoundly shaping our decisions and societal participation.This paper explores a rapidly evolving example of algorithmic influence: the role of LLMs in human decision-making.As LLMs become increasingly central to these processes, their influence extends beyond simple assistance, potentially transforming how individuals evaluate options and act on recommendations.We examine this through the lens of critical algorithmic literacy, which encompasses the ability to interpret and critically assess algorithmic systems that influence access to information and decision-making.Based on a scoping review of 45 papers, we highlight the need for autonomy-supportive LLM-assisted decision-making approaches that empower learners to critically engage with the entire process and confidently take control of their choices as transformative agents.

  PublisherOA PDFDOI

• A Design Space for Articulating and Addressing the Risks of Integrating Generative AI in Education

  Proceedings. · 2025-06-10

  articleOpen accessSenior author

  Generative AI in Education must be approached with caution.While it might offer learning benefits, it also poses risks.Ethics frameworks have proliferated to guide responsible design, but they often lack enforceability and can be vague or overwhelming to implement in practice.We draw inspiration from Human-Computer Interaction to argue for the development of a systematic and community-driven design space to articulate, prioritize, and address the risks associated with Generative AI systems in Education.

  PublisherOA PDFDOI

Recent grants

• EAGER: Foundations for Advancing Computational Thinking (FACT): Learning and Assessment through an Online Middle School Curriculum

  NSF · $253k · 2013–2015

• Cognitive Processes in Understanding and Using Scientific Diagrams

  NSF · $731k · 1988–1991

Frequent coauthors

• Robert M. Arnold

  49 shared

• Gwyn Barley

  49 shared

• Anthony L. Back

  University of Washington

  49 shared

• Kelly Fryer‐Edwards

  University of Washington

  49 shared

• James A. Tulsky

  Harvard University

  49 shared

• Walter F. Baile

  The University of Texas MD Anderson Cancer Center

  49 shared

• Christian Heath

  King's College School

  23 shared

• Lucy Suchman

  Lancaster University

  19 shared

Awards & honors

• McGraw Education Prize (2022)
• Fellow, American Academy of Arts and Sciences (2019-)
• Inaugural Fellow, International Society of the Learning Scie…
• Honorary Degree, Doctor of The University, The Open Universi…
• Best Bridging Paper: 7th International Conference on Educati…