Matt is a PhD candidate at the University of Washington College of Education, in the Measurement and Statistics area. His research works to improve the reliability, validity, and equity of CS assessments by bringing together psychometrics, CS education, and log data analysis methods.

Interests

• Computing Education
• Log Data
• Educational Statistics
• Anti-racist Psychometrics

Education

• PhD Candidate in Measurement and Statistics, 2017 -
  University of Washington
• MEd in Learning Sciences, 2014
  University of Washington
• BA in History, English, and Philosophy, 2007
  University of Texas

Recent Work

• Davidson, M. (2021 August). Towards an Understanding of Program Writing as a Cognitive Process: Analysis of Keystroke Logs. ICER ‘21: Proceedings of the 17th ACM Conference on International Computing Education Research, virtual event. https://doi.org/10.1145/3446871.3469774

• Xie, B., Davidson, M., Franke, B., McLeod, E., Li, M., & Ko, A.J. (2021 June). Domain Experts’ Interpretations of Assessment Bias in a Scaled, Online Computer Science Curriculum. L@S ‘21: Proceedings of the 8th ACM Conference on Learning @ Scale, virtual event. https://dx/doi/org/10.1145/3430895.3460141

• Davidson, M. & Li, M. (2021 April). Nonconstruct Item Features and Response Processes in Computer Science Assessments: Evidence From Think-Alouds and Sequence Analysis. Presented at the American Education Research Association Annual Meeting, virtual event. View the iPresentation, Watch a recording of the talk (youtube), Read a blog post on the methods we used

• Davidson, M., Wortzman, B., Ko, A.J., & Li, M. (2021 March). Investigating Item Bias in a CS1 Exam with Differential Item Functioning. SIGCSE ‘21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, 1142–1148. https://doi.org/10.1145/3408877.3432397 More at bit.ly/sigcse21DIF

• Ko, A.J., Oleson, A., Ryan, N., Register, Y., Xie, B., Tari, M., Davidson, M., Druga, S., and Loksa, D. (2020 November). It is time for more critical CS education. Communications of the ACM 63:11, 31–33. https://cacm.acm.org/magazines/2020/11/248199-it-is-time-for-more-critical-cs-education/fulltext

• Davidson, M.J., Fan, F. Dallas, D., Goodman, J., Weir, J.B. (2020, April). Modeling Latent Ability Change in a Longitudinal Assessment: a MIRT Approach. Accepted for presentation at National Council on Measurement in Education Annual Meeting, original location San Francisco, California.

• Davidson M.J., Dong, D., Xie, B., Li, M., & Ko, A. (2019, April). Exploring Item Difficulty in Assessments of Computer Programming with Cognitive Interviews. Accepted for presentation at National Council on Measurement in Education Annual Meeting, Toronto, Ontario, Canada.

• Xie, B., Davidson, M.J., Li, M. & Ko, A. (2019, February). An Item Response Theory Evaluation of a Language-Independent CS1 Knowledge Assessment. Presented at the Association of Computing Machinery (ACM) Special Interest Group on Computer Science Education Technical Symposium, Minneapolis, Minnesota.

• Xie, B., Loksa, D., Nelson, G.L., Davidson, M.J., Dong, D., Kwik, H., Tan, A.H., Hwa, L., Li, M., & Ko, A.J. (2019). A Theory of Instruction for Introductory Programming Skills. Computer Science Education. https://doi.org/10.1080/08993408.2019.1565235

• Davidson, M., Dong, D., Xie, B., Loska, D., Li, M., & Ko, A. (2018, June). Assessing Programming Knowledge and Skills: A Theory-based Approach. Presented at the International Test Commission, Montreal, Ontario, Canada