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Education Data Science Conference

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The Education Data Science Conference 2026 was a two-day forum for researchers, practitioners, and students to shape the future of education through data. Submissions that advance rigorous, ethical, and interdisciplinary approaches through using data in a variety of learning contexts were presented. From classrooms to platforms, from theory to practice, new applications of methods, addressing challenges of teaching, learning, and policy, and pushing the boundaries of an evolving discipline in pursuit of better, more equitable educational outcomes were explored during the conference. Thank you to all who attended and contributed! 

 

Best Submission Awards

Best student submission

Mei TanFeedback Footprint: Modeling the Language of Written Feedback Across Teachers and LLMs 

Best overall submission

Renzhe YuHow Have Instructors Adapted to Generative AI? Evidence from 90,000 Assignments in Postsecondary Courses

Organizing Committee

(alphabetical order)

Dora Demszky

Assistant Professor of Education
ddemszky@stanford.edu

Dora is an Assistant Professor in Education Data Science at Stanford University. Her research combines natural language processing and input to from practitioners to develop and test tools for supporting teachers.


 

Dora Demszky  Assistant Professor of Education

Katharine Sadowski

Assistant Professor of Education
ksadow@stanford.edu

Sadowski’s research bridges economics and public policy to examine how education and labor market policies shape the experiences of students, families, educators, and educational institutions. She combines econometric analysis with advanced machine learning methods to clean, link, and analyze large-scale administrative data for policy evaluation.

 

Katharine Sadowski Assistant Professor of Education

 

Sanne Smith

Lecturer
sannesmith@stanford.edu

Sanne Smith is a lecturer at the Stanford Graduate School of Education and is the Program Director of the Education Data Science MS Program. She teaches courses that introduce students to coding, data wrangling and visualization, various statistical methods, and the interpretation of quantitative research.

Sanne Smith  Lecturer

 

 

Advising Committee

Emma Brunskill Associate Professor of Computer Science

Emma Brunskill
Associate Professor of Computer Science

Susanna Loeb Professor of Education

Susanna Loeb
Professor of Education

Ben Domingue Associate Professor of Education

Ben Domingue
Associate Professor of Education

Daniel McFarland Professor of Education

Daniel McFarland
Professor of Education

Nick Haber Assistant Professor of Education

Nick Haber
Assistant Professor of Education

Mitchell Stevens Professor of Education

Mitchell Stevens
Professor of Education