Dora Demszky

Assistant Professor

[email protected]

- Personal website

Assistant: Melissa Cromosini

Office: CERAS 536

Biography

Dr. Demszky is an Assistant Professor in Education Data Science at the Graduate School of Education at Stanford University. She works on developing natural language processing methods to support equitable and student-centered instruction. She has developed tools to give feedback to teachers on dialogic instructional practices, to analyze representation in textbooks, measure the presence of dialect features in text, among others. Dr Demszky has received her PhD in Linguistics at Stanford University, supervised by Dr Dan Jurafsky. Prior to her PhD, Dr. Demszky received a BA summa cum laude from Princeton University in Linguistics with a minor in Computer Science.

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Other Titles

Assistant Professor, Graduate School of Education
Assistant Professor (By courtesy), Computer Science

Program Affiliations

Learning Sciences and Technology Design (LSTD)

SHIPS (PhD)

SHIPS (PhD): Education Data Science

SHIPS (PhD): Educational Linguistics

(MS) EDS

Stanford Accelerator for Learning

See GSE Programs >

Research Interests

Curriculum and Instruction | Data Sciences | Social and Emotional Learning | Teachers and Teaching | Technology and Education

See a full list of GSE Faculty research interests >

Recent Publications

Demszky, D., Wang, R. E., Geraghty, S., & Yu, C. (2024). Does Feedback on Talk Time Increase Student Engagement? Evidence from a Randomized Controlled Trial on a Math Tutoring Platform. FOURTEENTH INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS & KNOWLEDGE, LAK 2024. ASSOC COMPUTING MACHINERY.

Malik, R., Abdi, D., Wang, R., & Demszky, D. (2024). Scaling High-Leverage Curriculum Scaffolding in Middle-School Mathematics. PROCEEDINGS OF THE ELEVENTH ACM CONFERENCE ON LEARNING@SCALE, L@S 2024. ASSOC COMPUTING MACHINERY.

Yun, J., Hicke, Y., Olson, M., & Demszky, D. (2024). Enhancing Tutoring Effectiveness Through Automated Feedback: Preliminary Findings from a Pilot Randomized Controlled Trial on SAT Tutoring. PROCEEDINGS OF THE ELEVENTH ACM CONFERENCE ON LEARNING@SCALE, L@S 2024. ASSOC COMPUTING MACHINERY.

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