AI Goes to School for Math-Instruction Study
Researchers to Create Database of A+ Classroom Teaching
Improving education systems and outcomes
through more effective use of data science, technology, and AI
Kimberly A. Griffin
Professor and Dean of the College of Education
The Center for Educational Data Science and Innovation, also known as EDSI, aligns well with UMD's commitment to innovation and exploration in the areas of data science and AI. EDSI will be a unique interdisciplinary center, committed to research, practice, and dissemination of critical information to ensure the ethical use of AI to enhance equity, effectiveness, and efficiency in education.
Jennifer King Rice
Senior Vice President and Provost
This center holds great potential for improving education systems and outcomes through more effective use of data science, technology, and AI. I am particularly excited about the cutting edge research that this center will enable, and the potential for that research to drive data-informed policy and practice, technological advances, and ultimately, more effective and equitable educational opportunities for all learners.
Recent Publications
. Michael L. Chrzan, Francis A. Pearman. EdWorkingPapers.com. https://doi.org/10.26300/dfry-5906
A Quantitative Study of Mathematical Vocabulary Use in Upper Elementary Classrooms
. Zachary Himmelsbach, Heather C. Hill, Jing Liu, Dorottya Demszky. Educational Researcher. https://doi.org/10.3102/0013189X251393232
The Effect of Centralized-Admission School Lotteries on Between-School Segregation: Evidence from 300 Largest School Districts in the United States
. Francisco Lagos, Jason Saltmarsh, Jing Liu. EdWorkingPapers.com. https://doi.org/10.26300/1mfx-cc03
A Framework for Building High-Quality Education Data for R&D in the Age of AI: The EDSI Dataset and Expert Insights
. Jing Liu, Brendon Krall, Sarah Montana, Ariel Chung, Heather Hill. Center for Educational Data Science and Innovation and Research Partnership for Professional Learning
. Jiseung Yoo, Campbell F. Scribner. Theory Into Practice. https://doi.org/10.1080/00405841.2025.2528553
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UMD Faculty Member Co-Hosts Workshop to Advance Automated Speech Recognition Systems Used for Education
| The University of Maryland Institute for Advanced Computer Studies