A member of the SUSE faculty since 2000, Dr. Schwartz studies student understanding and representation and the ways that technology can facilitate learning. He works at the intersection of cognitive science, computer science, and education, examining cognition and instruction in individual, cross-cultural, and technological settings. A theme throughout Dr. Schwartz's research is how people's facility for spatial thinking can inform and influence processes of learning, instruction, assessment and problem solving. He finds that new media make it possible to exploit spatial representations and activities in fundamentally new ways, offering an exciting complement to the verbal approaches that dominate educational research and practice.
Instructional methods, transfer of learning and assessment, mathematical development, teachable agents, cognition, and cognitive neuroscience.
Small Group Instruction and Interaction
Technology in Teaching and Learning
“For many, assessments are a lighthouse in the fog of education—a clear guide by which to make safe decisions. But in reality, assessments create the fog. Current assessments perpetuate beliefs that the proper outcomes of learning are static facts and routine skills—stuff that is easy to score as right or wrong. Interest, curiosity, identification, self-efficacy, belonging, and all the other goals of informal learning cannot even sit at the assessment table, because these outcomes are too far removed from current beliefs about what is really important. Assessments seem to be built on the presupposition that people will never need to learn anything new after the test, because current assessments miss so many aspects of what it means to be prepared for future learning. These frozen-moment assessments have influenced what people think counts as useful learning, which then shows up in curricula, standards, instructional technologies, and people’s pursuits.
“If the fog were lifted, we would see that most of the stakeholders in education care first and foremost about people’s abilities to make good choices. Making good choices depends on what people know, but it also depends on much more, including interest, persistence, and a host of twenty-first-century soft skills that are critical to learning. Where we can anticipate a stable future—decoding letters into words is likely to be a stable demand for the next fifty years—then knowledge- and skill- based assessments make sense. In relation to those aspects of the future that are less stable, though, people will need to choose whether, what, when, and how to learn. Hence, it is important to focus on choices that influence learning, and assessments should measure those choices. Choice is the critical outcome of learning, not knowledge. Knowledge is an enabler; choice is the outcome.”
- From Measuring what matters most: Choice-based assessments for the digital age (Cambridge, MA: MIT Press, 2013), co-authored with Dylan Arena
PhD (Human Cognition and Learning), Columbia University, 1992
MA (Computers and Education), Columbia University, 1988
BA (Philosophy and Anthropology), Swarthmore College, 1979
Teaching Certificate, University of Southern California, 1981
Time at Stanford
Professor of Education
Teacher of Mathematics, Kitiwanga Day School, Kitiwanga, Kenya
Teacher of Remedial Reading and Writing, John Muir Jr. High, Los Angeles, CA
Teacher of Mathematics, Science, Reading and Language Arts, Kaltag Jr. & Sr. High Schools, Kaltag, AK
Programmer & Instructor in Lisp, C, & Assembler
Research Scientist, Learning Technology Center at Vanderbilt
Assistant and Associate Professor of Psychology and Human Development, Vanderbilt University
ABCs of Core Mechanics for Learning • Assessing Technologies for Learning • Methods in Psychological Studies in Education • Educational Neuroscience • Colloquium on Child Learning and Development • Colloquium on Learning Sciences, Technology, & Design • Cognition for Learning • Agency in Humans and Machines • Transfer of Learning • Spatial Learning • Quantitative Reasoning • Interactivity in Learning • Play • Feedback • Discovery and Innovation • Core Learning Mechanics • Visualizations for Learning • Human Induction and Introductory Statistics • Introductory Statistics for Doctoral Students
Cutumisu, M., Blair, K. P., Chin, D. B., & Schwartz, D. L. (in press) Posterlet: A game-based assessment of children’s choices to seek feedback and revise. Journal of Learning Analytics.
Tsang, J., Blair, K. P., Bofferding, L., & Schwartz, D. L. (2015). Learning to “see” less than nothing: Putting perceptual skills to work for learning numerical structure. Cognition & Instruction, 33, 154-197.
Shemwell, J., Chase, C., & Schwartz, D. L. (2015). Seeking the general explanation: A test of inductive activities for learning and transfer. Journal of Research in Science Teaching, 52(1), 58-83.
Oppezzo, M., & Schwartz, D. L. (2014). Give your ideas some legs: The positive effect of walking on creative thinking. Journal of Experimental Psychology: Learning, Memory, & Cognition.
Okita, S. A., & Schwartz, D. L. (2013). Learning by teaching human pupils and teachable agents: The importance of recursive feedback. Journal of the Learning Sciences, 22(3), 375-412.
Arena, D. A., & Schwartz, D. L. (2013). Experience and explanation: Using videogames to prepare students for formal instruction in statistics. Journal of Science Education and Technology.
Schwartz, D. L., Blair, K. P., & Tsang, J. M. (2012). How to build educational neuroscience: Two approaches with concrete instances. British Journal of Educational Psychology Monograph Series II, (8) 9-27.
Schwartz, D. L., Chase, C. C., Oppezzo, M. A., & Chin, D. B. (2011). Practicing versus inventing with contrasting cases: The effects of telling first on learning and transfer. Journal of Educational Psychology, 103(4), 759-775.
Schwartz, D. L., Tsang, J. M., & Blair, K. P. (forthcoming Feb. 2016). The ABCs of How We Learn: 26 Scientifically Proven Approaches, How They Work, and When to Use Them. W. W. Norton.
Schwartz, D. L., & Arena, D. (2013). Measuring what matters most: Choice-based assessments for the digital age. Cambridge, MA: MIT Press.
Chapters and Such
Schwartz, D. L., & Goldstone, R. (in press). Learning as coordination: Cognitive psychology and education. In L. Corno and E. Aldemann (Eds.), Handbook of Educational Psychology. American Psychological Association, Washington, DC.
Blair, K. P., Tsang, J. M., & Schwartz, D. L. (2013). The bundling hypothesis: How perception and culture give rise to abstract mathematical concepts in individuals. In S. Vosniadou (Ed.), International Handbook of Research on Conceptual Change II (pp. 322-340). New York: Taylor & Francis.
Martin, L., & Schwartz, D. L. (2013). Conceptual innovation and transfer. In S. Vosniadou (Ed.), International Handbook of Research on Conceptual Change II (pp. 447-465). New York: Taylor & Francis.
Oppezzo, M.A. & Schwartz, D.L. (2013). A behavior change perspective on self-regulated learning with teachable agents. In R. Azevedo, & V. Alevan (Eds), International Handbook of Metacognition and Learning (pp. 485-500). New York: Springer.
Blair, K. P., & Schwartz, D. L. (2012). A value of concrete learning materials in adolescence. In Reyna, V. F., Chapman, S., Dougherty, M., & Confrey, J. (Eds.). The adolescent brain: Learning, reasoning, and decision making (pp. 95-122). Washington, DC: American Psychological Association.
Dow, S. P., Fortuna, J., Schwartz, D., Altringer, B., Schwartz, D. L., & Klemmer, S. L. (2012). Prototyping dynamics: sharing multiple designs improves exploration, group rapport and results. In H. Plattner, C. Meinel & L. Leifer (Eds.) Design Thinking Research Understanding Innovation, (pp. 47-70). Berlin: Springer.
Research on the benefits of informal learning for subsequent school-based instruction.
Serving on the National Academy of Sciences committee to write How People Learn II.
Principal Investigator, Department of Education Institute of Education Sciences grant, Designing Contrasting Cases for Inductive Learning, 2014-17.
Blair, K. P., Pfaffman, J., Cutumisu, M., Hallinen, N., & Schwartz, D. L. (2015, April). Testing the effectiveness of iPad math game: Lessons learned from running a multi-classroom study. CHI ’15 Extended Abstracts.
Cutumisu, M., & Schwartz, D. L. (2014, November). Choosing negative feedback improves learning for students of all ages: A game-based assessment of seeking negative feedback and revising. Proceedings of the London International Conference in Education (pp. 171-176). London, England.
Cutumisu, M., Chin, D. B., & Schwartz, D. L. (2014, October). A game-based assessment of students’ choses to seek feedback and to revise. Proceedings of the 11th International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA) (pp. 17-24). Porto, Portugal. ** Best Paper **
Chi, M., Schwartz, D. L., Blair, K. P., & Chin, D. L. (2014, July). Choice-based assessment: Can choices made in digital games predict 6th grade students’ math scores? Proceedings of the 7th International Conference on Educational Data Mining, (36-43). London, England.
Conlin, L., Hallinen, N.R., & Schwartz, D.L. (2014, June). Supporting middle schoolers’ use of inquiry strategies for discovering multivariate relations in interactive physics simulations. In Polman, J. L., Kyza, E. A., O'Neill, D. K., Tabak, I., Penuel, W. R., Jurow, A. S., O'Connor, K., Lee, T., and D'Amico, L. (Eds.). Learning and becoming in practice: The International Conference of the Learning Sciences (ICLS), (pp. 31-37). Boulder, CO.
Hallinen, N.R., Cheng, J., Chi, M., & Schwartz, D.L. (2014, June). Tug of War – What is it good for? Measuring Student Inquiry Choices in an Online Science Game. In Polman, J. L., Kyza, E. A., O'Neill, D. K., Tabak, I., Penuel, W. R., Jurow, A. S., O'Connor, K., Lee, T., and D'Amico, L. (Eds.). Learning and becoming in practice: The International Conference of the Learning Sciences (ICLS) (1645-1646), Boulder, CO.
International Invited Addresses
Schwartz, D. L. (November, 2014). Learning technologies to understand and improve the human mind (brain). Lund University, Sweden.
Schwartz, D. L. (July, 2013). Induction. Presentation at EPFL, Switzerland.
Schwartz, D. L. (October, 2012). Assessing informal learning. Presentation to the Wellcome Trust, London.
Schwartz, D. L. (April, 2012). Cognitive Science and education. Presentation at the Swedish Cognitive Science Society.
Schwartz, D. L. (March, 2012). Technology and learning. Presentation to faculty and dignitaries at the University of Bejing.
National Invited Addresses
Schwartz, D. L. (2015, March). Walking and creativity. University of Indiana, Bloomington.
Schwartz, D. L. & Cutumisu, M. (2014, April). Choice-based assessments of preparation for future learning. Invited Presidential Symposium, New ways to evaluate mathematics and science education. AERA, Philadelphia.
Schwartz, D. L. (2014, April). The science of learning meets the learning sciences. Invited Presidential Symposium, The sciences of learning, the educational sciences, and AERA: Strange bedfellows or all in the family. AERA, Philadelphia.
Schwartz, D. L. (2012, Dec.) Transfer across disciplines. Presentation to the science faculty of Carleton College.
Schwartz, D. L. (2012, July). I am not here to bury lectures. Presentation to the faculty of Yale University.
Schwartz. D. L. (2012, March). Negative transfer. Presentation to the faculty and students of Arizona State University.
Stanford Graduate School of Education
485 Lasuen Mall, Stanford, CA 94305-3096
Tel: (650) 723-2109