Victor R. Lee is an Associate Professor in the Graduate School of Education at Stanford University and leads the Data Interactions & STEM Teaching and Learning (DISTAL) Lab. Through his research, he asks what STEM knowledge, tools, and practices are important to know to enable active participation and critical engagement with our increasingly digitally-infused lives. He then uses the tools of educational design to create examples for how we could get there. Currently, this involves researching and designing learning experiences and resources for data literacy, K-12 data science education, and artificial intelligence literacy. He also conducts research related to elementary computer science education, maker education, and science cognition. His research is most often done through research-practice partnerships and involves design, implementation, analysis, and continual revision of new learning experiences in actual learning settings (such as schools, districts, or libraries). Lee completed his undergraduate studies at UC San Diego with emphasis in cognitive science, human computer interaction, and mathematics. He earned his doctorate in Learning Sciences at Northwestern University where he was supported for several years through a fellowship with the NSF-funded Center for Curriculum Materials in Science. Since leaving the midwest and beginning his professional academic career, he has received the National Science Foundation CAREER award, the Jan Hawkins Award, a post-doctoral fellowship from the National Academy of Education and the Spencer Foundation, and various best paper awards. His book, Learning Technologies and the Body (published by Routledge), is the first compendium of current research of embodied technologies for learning. With Abigail Phillips, he published, Reconceptualizing Libraries: Perspectives from the Information and Learning Sciences (2018). In 2021, he co-authored the National Academies of Science, Engineering, and Medicine's consensus report on authentic computing education experiences. Currently, he is completing a new book on K-12 data science education. Victor sits on the editorial board of several leading journals, including Journal of the Learning Sciences and Cognition & Instruction. He is a past-president and elected fellow of the International Society of the Learning Sciences.

Academic Appointments

Administrative Appointments

  • Assistant Professor, Department of Instructional Technology & Learning Sciences, Utah State University, Logan (2009 - 2015)
  • Associate Professor, Department of Instructional Technology & Learning Sciences,, Utah State University, Logan (2015 - 2019)

Honors & Awards

  • Fellow, International Society of the Learning Sciences (2022)
  • Fellow, International Society for Design and Development in Education (2021)
  • Outstanding Research Award, Council for Technology & Engineering Teacher Education (2018)
  • Postdoctoral Fellowship, National Academy of Education/Spencer Foundation (2014)
  • Jan Hawkins Award, American Educational Research Association (2013)
  • CAREER Award, National Science Foundation (2011)

Boards, Advisory Committees, Professional Organizations

  • President, International Society of the Learning Sciences (2020 - 2021)
  • Committee Member, National Academies of Science, Engineering and Medicine - Committee on Authentic STEM Experiences (2019 - 2021)
  • Board Member, International Society of the Learning Sciences (2015 - 2022)

Program Affiliations

  • Symbolic Systems Program

Professional Education

  • PhD, Northwestern University, Learning Sciences (2008)
  • BS, UC San Diego, Cognitive Science with Specialization in Human-Computer Interaction (2001)
  • BA, UC San Diego, Math/Applied Science (2001)

Research Interests

  • Brain and Learning Sciences
  • Collaborative Learning
  • Curriculum and Instruction
  • Early Childhood
  • Elementary Education
  • Lifelong Learning
  • Math Education
  • Motivation
  • Science Education
  • Teachers and Teaching
  • Technology and Education

Current Research and Scholarly Interests

My research has three major strands, connected by their focus on STEM and learning technologies.

One is the "data" strand. I look at student learning through the use of data sets that they create themselves and are about their routine activities. This is associated with the "Quantified Self" movement which entails gaining personal insight from collecting and analyzing one's own data. Through support of an NSF CAREER award, I have conducted multiple years of design-based research studies with elementary and middle school classrooms where we have developed learning activities for students to work with their own bodily data obtained from wearable devices. This is extending into research on teaching and learning with data generally and exploring what a K-12 data science education would look like. New projects are looking at interdisciplinary integrations of data science into classroom instruction and has extended into artificial intelligence literacy.

A second strand of research involves looking at learning in maker spaces and programs outside of the classroom. The broader maker movement has inspired a range of community activities and informal learning organizations to offer maker learning experiences. In one project, I have been examining student engagement in maker learning activities hosted at an after school program based at a community maker space. In another, I have been designing supports for rural libraries to host and enact maker programs for teens. Additionally, I have sought to examine what knowledge changes through participation in making.

Finally, a third strand of research involves computational thinking at the elementary school levels. Schools are increasingly seeking out and introducing computer science curricula for their students, and elementary schools are no exception. In one project, my team has been designing instruction around computer science board games as a way of introducing computer science through an "unplugged" approach. Rather than leaving all learning activities in their unplugged format, we then transition students to working with computer-based versions of the same activities to transfer their nascent understandings. In another project, I work with colleagues to study computational thinking of kindergarteners as it is expressed through use of commercial coding toys. Our larger goal is to develop an assessment protocol for measuring computational thinking for this young age group, which is also beginning to experience computer science activities in their classrooms. Finally, I have a research-practice partnership with colleagues in Utah and a rural school district to better support paraprofessionals in providing computer science instruction.

All Publications

  • Learning sciences and learning engineering: A natural or artificial distinction? JOURNAL OF THE LEARNING SCIENCES Lee, V. R. 2022
  • Data science education across the disciplines: Underexamined opportunities for K-12 innovation BRITISH JOURNAL OF EDUCATIONAL TECHNOLOGY Jiang, S., Lee, V. R., Rosenberg, J. M. 2022

    View details for DOI 10.1111/bjet.13258

    View details for Web of Science ID 000822579700001

  • Taking data feminism to school: A synthesis and review of pre-collegiate data science education projects BRITISH JOURNAL OF EDUCATIONAL TECHNOLOGY Lee, V. R., Pimentel, D. R., Bhargava, R., D'Ignazio, C. 2022

    View details for DOI 10.1111/bjet.13251

    View details for Web of Science ID 000817736800001

  • A Call for a Humanistic Stance Toward K-12 Data Science Education EDUCATIONAL RESEARCHER Lee, V. R., Wilkerson, M., Lanouette, K. 2021
  • Remembering What Produced the Data: Individual and Social Reconstruction in the Context of a Quantified Self Elementary Data and Statistics Unit COGNITION AND INSTRUCTION Lee, V. R., Drake, J., Cain, R., Thayne, J. 2021
  • Tabletop games designed to promote computational thinking COMPUTER SCIENCE EDUCATION Poole, F. J., Clarke-Midura, J., Rasmussen, M., Shehzad, U., Lee, V. R. 2021
  • At Home With Data: Family Engagements With Data Involved in Type 1 Diabetes Management JOURNAL OF THE LEARNING SCIENCES Lee, V. R., Dubovi, I. 2019
  • A wearables-based approach to detect and identify momentary engagement in afterschool Makerspace programs Contemporary Educational Psychology Lee, V. R., Fischback, L., Cain, R. 2019
  • A Broad View of Wearables as Learning Technologies: Current and Emerging Applications LEARNING IN A DIGITAL WORLD: PERSPECTIVE ON INTERACTIVE TECHNOLOGIES FOR FORMAL AND INFORMAL EDUCATION Lee, V. R., Shapiro, R., Diaz, P., Ioannou, A., Bhagat, K. K., Spector, J. M. 2019: 113–33
  • The technical matters: young children debugging (with) tangible coding toys INFORMATION AND LEARNING SCIENCES Silvis, D., Lee, V. R., Clarke-Midura, J., Shumway, J. F. 2022
  • Exploring Measurement through Coding: Children's Conceptions of a Dynamic Linear Unit with Robot Coding Toys EDUCATION SCIENCES Welch, L. E., Shumway, J. F., Clarke-Midura, J., Lee, V. R. 2022; 12 (2)
  • Identifying the Content, Lesson Structure, and Data Use Within Pre-collegiate Data Science Curricula JOURNAL OF SCIENCE EDUCATION AND TECHNOLOGY Lee, V. R., Delaney, V. 2021
  • Kindergarten students' mathematics knowledge at work: the mathematics for programming robot toys MATHEMATICAL THINKING AND LEARNING Shumway, J. F., Welch, L. E., Kozlowski, J. S., Clarke-Midura, J., Lee, V. R. 2021
  • Youth engagement during making: using electrodermal activity data and first-person video to generate evidence-based conjectures INFORMATION AND LEARNING SCIENCES Lee, V. R. 2021
  • Developing a kindergarten computational thinking assessment using evidence-centered design: the case of algorithmic thinking COMPUTER SCIENCE EDUCATION Clarke-Midura, J., Silvis, D., Shumway, J. F., Lee, V. R., Kozlowski, J. S. 2021
  • It's More Than Just Technology Adoption: Understanding Variations in Teachers' Use of an Online Planning Tool TECHTRENDS Leary, H., Lee, V. R., Recker, M. 2021
  • What do Teens Make of Personal Informatics? Young People's Responses to Self-Tracking Practices for Self-Determined Motives Potapov, K., Vasalou, A., Lee, V., Marshall, P., ASSOC COMP MACHINERY ASSOC COMPUTING MACHINERY. 2021
  • Let's cut to commercial: where research, evaluation, and design of learning games should go next ETR&D-EDUCATIONAL TECHNOLOGY RESEARCH AND DEVELOPMENT Lee, V. R. 2020
  • An Emerging Technology Report on Computational Toys in Early Childhood TECHNOLOGY KNOWLEDGE AND LEARNING Hamilton, M., Clarke-Midura, J., Shumway, J. F., Lee, V. R. 2020; 25 (1): 213–24
  • Instructional support for learning with agent-based simulations: A tale of vicarious and guided exploration learning approaches COMPUTERS & EDUCATION Dubovi, I., Lee, V. R. 2019; 142
  • The picture of smartphones at school is not a dire one and the picture of student competence is a bright one LEARNING CULTURE AND SOCIAL INTERACTION Lee, V. R. 2019; 21: 293–95
  • Youth Concerns and Responses to Self-Tracking Tools and Personal Informatics Systems Potapov, K., Lee, V. R., Vasalou, A., Marshall, P., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019
  • The building blocks of coding: a comparison of early childhood coding toys INFORMATION AND LEARNING SCIENCES Clarke-Midura, J., Lee, V. R., Shumway, J. F., Hamilton, M. M. 2019; 120 (7-8): 505–18
  • On researching activity tracking to support learning: a retrospective INFORMATION AND LEARNING SCIENCES Lee, V. R. 2019; 120 (1-2): 133–54
  • Paper Circuits: A Tangible, Low Threshold, Low Cost Entry to Computational Thinking TECHTRENDS Lee, V. R., Recker, M. 2018; 62 (2): 197–203
  • A rubric for describing competences in the areas of circuitry, computation, and crafting after a course using e-textiles INTERNATIONAL JOURNAL OF INFORMATION AND LEARNING TECHNOLOGY Lee, V. R., Fields, D. A. 2017; 34 (5): 372–84
  • A Comparison of Discovered Regularities in Blood Glucose Readings across Two Data Collection Approaches Used with a Type 1 Diabetic Youth METHODS OF INFORMATION IN MEDICINE Lee, V., Thurston, T., Thurston, C. 2017; 56: E84–E91


    Type 1 diabetes requires frequent testing and monitoring of blood glucose levels in order to determine appropriate type and dosage of insulin administration. This can lead to thousands of individual measurements over the course of a lifetime of a single individual, of which very few are retained as part of a permanent record. The third author, aged 9, and his family have maintained several years of written records since his diagnosis with Type 1 diabetes at age 20 months, and have also recently begun to obtain automated records from a continuous glucose monitor.This paper compares regularities identified within aggregated manually-collected and automatically-collected blood glucose data visualizations by the family involved in monitoring the third author's diabetes.7,437 handwritten entries of the third author's blood sugar readings were obtained from a personal archive, digitized, and visualized in Tableau data visualization software. 6,420 automatically collected entries from a Dexcom G4 Platinum continuous glucose monitor were obtained and visualized in Dexcom's Clarity data visualization report tool. The family was interviewed three times about diabetes data management and their impressions of data as presented in data visualizations. Interviews were audiorecorded or recorded with handwritten notes.The aggregated visualization of manually-collected data revealed consistent habitual times of day when blood sugar measurements were obtained. The family was not fully aware that their existing life routines and the third author's entry into formal schooling had created critical blind spots in their data that were often unmeasured. This was realized upon aggregate visualization of CGM data, but the discovery and use of these visualizations were not realized until a new healthcare provider required the family to find and use them. The lack of use of CGM aggregate visualization was reportedly because the default data displays seemed to provide already abundant information for in-the-moment decision making for diabetes management.Existing family routines and school schedules can shape if and when blood glucose data are obtained for T1D youth. These routines may inadvertently introduce blind spots in data, even when it is collected and recorded systematically. Although CGM data may be superior in its overall density of data collection, families do not necessarily discover nor use the full range of useful data visualization features. To support greater awareness of youth blood sugar levels, families that manually obtain youth glucose data should be advised to avoid inadvertently creating data blind spots due to existing schedules and routines. For families using CGM technology, designers and healthcare providers should consider implementing better cues and prompts that will encourage families to discover and utilize aggregate data visualization capabilities.

    View details for DOI 10.3414/ME16-02-0047

    View details for Web of Science ID 000413013300004

    View details for PubMedID 28678303

    View details for PubMedCentralID PMC6291844

  • Appropriating Quantified Self Technologies to Support Elementary Statistical Teaching and Learning IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES Lee, V. R., Drake, J. R., Thayne, J. L. 2016; 9 (4): 354–65
  • Let's Get Physical: K-12 Students Using Wearable Devices to Obtain and Learn About Data from Physical Activities TECHTRENDS Lee, V. R., Drake, J., Williamson, K. 2015; 59 (4): 46–53
  • Combining High-Speed Cameras and Stop-Motion Animation Software to Support Students' Modeling of Human Body Movement JOURNAL OF SCIENCE EDUCATION AND TECHNOLOGY Lee, V. R. 2015; 24 (2-3): 178–91
  • Understanding the Opportunities and Challenges of Introducing Computational Crafts to Alternative High School Students EDUCATIONAL MEDIA AND TECHNOLOGY YEARBOOK, VOL 39 DuMont, M., Lee, V. R., Orey, M., Branch, R. M. 2015; 39: 83–99
  • The Role of School District Science Coordinators in the District-Wide Appropriation of an Online Resource Discovery and Sharing Tool for Teachers JOURNAL OF SCIENCE EDUCATION AND TECHNOLOGY Lee, V. R., Leary, H. M., Sellers, L., Recker, M. 2014; 23 (3): 309–23
  • Students' Digital Photography Behaviors during a Multiday Environmental Science Field Trip and Their Recollections of Photographed Science Content EDUCATION RESEARCH INTERNATIONAL Lee, V. R. 2014
  • Knowing and Learning with Technology (and on Wheels!): An Introduction to the Special Issue TECHNOLOGY KNOWLEDGE AND LEARNING Lee, V. R. 2013; 18 (1-2): 1–8
  • Digital Physical Activity Data Collection and Use by Endurance Runners and Distance Cyclists TECHNOLOGY KNOWLEDGE AND LEARNING Lee, V. R., Drake, J. 2013; 18 (1-2): 39–63
  • Collaborative Strategic Board Games as a Site for Distributed Computational Thinking DEVELOPMENTS IN CURRENT GAME-BASED LEARNING DESIGN AND DEPLOYMENT Berland, M., Lee, V. R., Felicia, P. 2013: 285–301
  • Framing in cognitive clinical interviews about intuitive science knowledge: Dynamic student understandings of the discourse interaction SCIENCE EDUCATION Russ, R. S., Lee, V. R., Sherin, B. L. 2012; 96 (4): 573–99

    View details for DOI 10.1002/sce.21014

    View details for Web of Science ID 000305122800001

  • Some assembly required: How scientific explanations are constructed during clinical interviews JOURNAL OF RESEARCH IN SCIENCE TEACHING Sherin, B. L., Krakowski, M., Lee, V. R. 2012; 49 (2): 166–98

    View details for DOI 10.1002/tea.20455

    View details for Web of Science ID 000299071500002

  • Material Pets, Virtual Spaces, Isolated Designers: How Collaboration May Be Unintentionally Constrained in the Design of Tangible Computational Crafts DuMont, M., Lee, V. R., ACM ASSOC COMPUTING MACHINERY. 2012: 244–47
  • In Pursuit of Consensus: Disagreement and legitimization during small-group argumentation INTERNATIONAL JOURNAL OF SCIENCE EDUCATION Berland, L. K., Lee, V. R. 2012; 34 (12): 1857–82
  • RETWEETING HISTORY Exploring the Intersection of Microblogging and Problem-based Learning for Historical Reenactments DESIGNING PROBLEM-DRIVEN INSTRUCTION WITH ONLINE SOCIAL MEDIA Lee, V. R., Shelton, B. E., Walker, A., Caswell, T., Jensen, M., Seo, K. K., Pellegrino, D. A., Engelhard, C. 2012: 23–40
  • Integrating physical activity data technologies into elementary school classrooms ETR&D-EDUCATIONAL TECHNOLOGY RESEARCH AND DEVELOPMENT Lee, V. R., Thomas, J. M. 2011; 59 (6): 865–84
  • Collaborative Strategic Board Games as a Site for Distributed Computational Thinking INTERNATIONAL JOURNAL OF GAME-BASED LEARNING Berland, M., Lee, V. R. 2011; 1 (2): 65–81
  • How Different Variants of Orbit Diagrams Influence Student Explanations of the Seasons SCIENCE EDUCATION Lee, V. R. 2010; 94 (6): 985–1007

    View details for DOI 10.1002/sce.20403

    View details for Web of Science ID 000283273100003

  • What Students Include in Hand-Drawn Diagrams to Explain Seasonal Temperature Variation Lee, V. R., Goel, A. K., Jamnik, M., Narayanan, N. H. SPRINGER-VERLAG BERLIN. 2010: 313–15
  • Adaptations and Continuities in the Use and Design of Visual Representations in US Middle School Science Textbooks INTERNATIONAL JOURNAL OF SCIENCE EDUCATION Lee, V. R. 2010; 32 (8): 1099–1126