Overview
Yvonne Kao is a computer science, data science, and mathematics education researcher who focuses on the design and evaluation of instructional materials and educational technology for all age groups. She is most energized by working directly with teachers, teacher leaders, and product developers through research–practice partnerships that address significant problems of educational practice. Her research uses a range of approaches from large-scale cluster-randomized trials to smaller behavioral studies.
Kao currently leads a research–practice partnership between WestEd and Oakland Unified School District (OUSD), which has received two grants from the National Science Foundation. The first project, Computer Science (CS) Connections, creates data science lessons for OUSD’s middle school computer science classes. Code.org, a nonprofit dedicated to expanding access and broadening participation in computer science in K–12 schools, incorporated materials from this project into their data science curriculum. The second project, Talking CS, is currently developing computer science language routines to support middle school students’ academic language and conceptual understanding of core programming constructs.
Kao also regularly participates in statewide and national committees to improve computer science, data science, and mathematics education and the use of educational technology. She is currently working with the Computer Science Teachers Association to revise their K–12 CS standards; the revised standards are scheduled for release in summer 2026. She was a member of the Data Science 4 Everyone Learning Progressions writing sprint and of a National Academies working group on data science assessment. In 2020 she served as the chair of the Vision for Teaching and Learning working group for the EdTech Genome Project sponsored by the EdTech Evidence Exchange. From 2017 to 2019, she was a writer for the California state computer science standards and strategic implementation plan.
Education
- PhD in cognitive psychology, Carnegie Mellon University
- BS in computer science, mathematics, and psychology, University of Wisconsin—Madison
Select Publications
Kao, Y., Owen, R., Houchins, J., Higgin, T., Gorson Benario, J., Dawson, M., & Jennings, K. (2025). Necessary skills for students to problem-solve with artificial intelligence: A literature review. In ICERI2025 proceedings. International Academy of Technology, Education and Development (IATED), Seville, Spain.
Kao, Y., McKinney, D., Berg, S., Tuohy, B., & Ortega, C. (2024). Discourse practices in computer science education. In SIGCSE 2024: Proceedings of the 55th Technical Symposium on Computer Science Education (pp. 632–638). Association for Computing Machinery.
Kao, Y., Murphy, D. L., Hubbard Cheuoua, A., Kannan, P., Tsan, J., Jennings, K. E., Smith, H., Emanuel, S., & Miller, E. R. (2023). The development and validation of a survey to predict computing career intentions. In K. Fisler, P. Denny, K. Franklin, & M. Hamilton (Eds.), ICER ’23: Proceedings of the 2023 ACM Conference on International Computing Education Research (Vol. 1, pp. 256–269). Association for Computing Machinery.
Kao, Y. S., Matlen, B., & Weintrop, D. (2022). From one language to the next: Applications of analogical transfer for programming education. ACM Transactions on Computing Education, 22(4), 1–21.
Kao, Y. S., Matlen, B., Tiu, M., & Li, L. (2017). Logic models as a framework for iterative user research in educational technology: Illustrative cases. In R. D. Roscoe, S. D. Craig, & I. Douglas (Eds.), End-user considerations in educational technology design (pp. 52–75). IGI Global.


