I am a PhD candidate in Learning Sciences and Technology Design at Stanford Graduate School of Education with a PhD Minor in Computer Science. I am advised by Jason Yeatman, Nick Haber, and Ben Domingue. I am broadly interested in psychometrics, reading, and human-centered AI, with a specific emphasis on their applications in improving the future of special education.

My current research, as part of Rapid Online Assessment of Reading, aims to create advanced dyslexia screening and progress monitoring tools. In one aspect of my work, I develop an open-source library, jsCAT, enabling real-time, browser-based computerized adaptive testing for broad application in behavioral research. At the same time, I explore the potential of leveraging generative AI, assessment data, and human expertise to scale and diversify the item bank of reading assessments. Currently, my research evaluates AI-powered reading tutors using the ROAR assessments, with the goal of making resource-intensive interventions paired with progress monitoring—typically conducted by reading specialists in small groups—accessible to all families.

In 2023, I was awarded as the Stanford Interdisciplinary Graduate Fellow. In 2024, I interned at ETS Research Institute. In 2025, I was selected as the Stanford HAI Graduate Fellow. My research has recieved awards from the Psychometric Society and National Council on Measurement in Education, and has been featured at the Psychonomic Society.

Prior to Stanford, I was a middle school Chemistry teacher in Brooklyn, NY. My previous research focused on science education and learning analytics under the guidance of Susan Kirch, Camillia Matuk, and Ryan Baker.

My current CV is available for download here.

Education

Ph.D. in Education and Ph.D. Minor in Computer Science (Expected 2026)
Stanford University

M.S.Ed. in Learning Sciences and Technologies (2019)
University of Pennsylvania

B.S. in Computer Science and Teaching Chemistry 7–12 (2018)
New York University

Selected Publications

Note: *These authors contributed equally to this work

Ma, W. A., Richie-Halford, A., Burkhardt, A. K., Kanopka, K., Chou, C., Domingue, B. W., & Yeatman, J. D. (2025). ROAR-CAT: Rapid Online Assessment of Reading ability with Computerized Adaptive Testing. Behavior Research Methods, 57(1), 1-17. PDF

Ma, W. A., Flor, M., & Wang, Z. (2025). Automatic generation of inference making questions for reading comprehension assessments. 20th Workshop on Innovative Use of NLP for Building Educational Applications. PDF

Ma, W. A., Liu, Y., Kanopka, K., W. M., & Domingue, B. W. (2025) A comparison of the predictive performance of continuous and class-based latent trait models. PDF

Ma, W. A., Fuentes-Jimenez, M., Siebert, J. M., Saavedra, A., Townley-Flores, C., Richie-Halford, A., Domingue, B. W., & Yeatman, J. D. (2025). Improving validity and efficiency of digital dyslexia screening through trial by trial feedback. PDF

Zelikman, E.*, Ma, W. A. *, Tran, J. E., Yang, D., Yeatman, J. D., Haber, N. (2023). Generating and Evaluating Tests for K-12 Students with Language Model Simulations: A Case Study on Sentence Reading Efficiency. 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP. PDF