Computational Thinking & Computational Literacy, Computer Science Education, Broadening Participation in Computing, Human-Computer Interaction, Data Science Education, Educational Technology, Design of Learning Environments

David Weintrop is an Associate Professor in the Department of Teaching & Learning, Policy & Leadership in the College of Education with a joint appointment in the College of Information Studies at the University of Maryland. His research focuses on the design, implementation, and evaluation of accessible and engaging computational learning environments. He is also interested in the use of technological tools in supporting exploration and expression across diverse contexts including STEM classrooms and informal spaces. His work lies at the intersection of human-computer interaction, design, and the Learning Sciences. David has a Ph.D. in the Learning Sciences from Northwestern University and a B.S. in Computer Science from the University of Michigan. He spent one year as a postdoctoral researcher at the University of Chicago studying computer science learning in elementary classrooms prior to joining the faculty at the University of Maryland. Before starting his academic career, he spent five years working as a software developer at a pair of start-ups in Chicago. You can learn more about David and his research on his website.

2022 National Science Foundation CAREER Award

2022 University of Maryland Graduate Faculty Mentor of the Year Award

2020 National Academy of Education/Spencer Postdoctoral Fellow

Select publications - a full list of publications can be found here.

Tissenbaum, M., Weintrop, D., Holbert, N., & Clegg, T. (2021). The Case for Alternative Endpoints in Computing Education. British Journal of Educational Technology, 52(3), 1164–1177.

Weintrop, D., Morehouse, S. & Subramaniam, M. (2021). Assessing Computational Thinking in Libraries. Computer Science Education.

Weintrop, D., Coenraad, M., Palmer, J., & Franklin, D. (2019). The Teacher Accessibility, Equity, and Content (TEC) Rubric for Evaluating Computing Curricula. ACM Transactions on Computing Education (TOCE), 20(1), 1–30.

Weintrop, D. & Wilensky, U. (2019). Transitioning from Introductory Block-based and Text-based Environments to Professional Programming Languages in High School Computer Science Classrooms. Computers & Education. 142.

Weintrop, D. (2019). Block-based Programming in Computer Science Education. Communications of the ACM, 62(8), 22–25.

Weintrop, D. & Wilensky, U. (2017). Comparing Blocks-based and Text-based Programming in High School Computer Science Classrooms. Transactions on Computing Education (TOCE), 18(1), 1-25.

Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining Computational Thinking for Mathematics and Science Classrooms. Journal of Science Education and Technology, 25(1), 127–147.

Weintrop, D., & Wilensky, U. (2017). Between a Block and a Typeface: Designing and Evaluating Hybrid Programming Environments. In Proceedings of the 2017 Conference on Interaction Design and Children (pp. 183–192). New York, NY, USA: ACM.

Weintrop, D., & Holbert, N. (2017). From Blocks to Text and Back: Programming Patterns in a Dual-Modality Environment. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (pp. 633–638). New York, NY, USA: ACM.

Weintrop, D. & Wilensky, U. (2015). Using Commutative Assessments to Compare Conceptual Understanding in Blocks-based and Text-based Programs. In Proceedings of the 11th annual International Computing Education Research (ICER) conference. New York, NY, USA: ACM.

Weintrop, D. & Wilensky, U. (2015). To Block or not to Block, That is the Question: Students’ Perceptions of Blocks-based Programming. In Proceedings of the 14th International Conference on Interaction Design and Children. New York, NY, USA: ACM.




CAREER: Situating Computational Learning Opportunities in the Digital Lives of High School Students. National Science Foundation. CSforAll 2141655. $1,040,084. 2022-2026. Principal Investigator.

Empowering Educators to Create Customized, Culturally-Responsive Instructional Materials from Scratch Encore Harmonized with the Interest of Students. National Science Foundation. DRK-12 2201312. $855,769. 2022-2025. Principal Investigator (Co-Principal Investigator: Diana Franklin).

INFACT: Include Neurodiversity in Foundational and Applied Computational Thinking. Department of Education: EIR #U411C190179. $3,175,344. 2019-2023. Co-Principal Investigator. (Principal Investigator: Jodi Asbell-Clark, Other Co-Principal Investigators: Quinn Burke, Fengfeng Ke, Shuchi Grover, Maya Israel).


Capturing Computational Thinking Literacy Development in Public Libraries. Institute of Museum and Library Services: LG-14-19-0079-19. $414,740. 2019-2022. Co-Principal Investigator. (Principal Investigator: Mega Subramaniam)