Grand Challenges: Using Machine Learning to Measure and Improve Equity in K-12 Mathematics Classrooms

A Framework for Building High-Quality Education Data for R&D in the Age of AI: The EDSI Dataset and Expert Insights
October 8, 2025

AI Goes to School for Math-Instruction Study
September 15, 2025

University of Maryland Opens Center for Ed-Tech Research (Government Technology)
May 15, 2025

College of Education Launches New Center to Bridge Education and AI
May 5, 2025

Grand Challenges Grantees Awarded $4.5M to Build Large-Scale, Open-Source Database and Use AI to Improve Math Learning Outcomes
March 3, 2025

New AI Seed Grants Support Trustworthy Tech 
September 10, 2024

Overdeck Family Foundation Funds Study Led by Jing Liu on Generative AI Coaching Tools for Improving K-12 Instruction and Student Outcomes
July 8, 2024

A Campus-wide Commitment to Advancing Ethical Artificial Intelligence: Q&A with Jing Liu
April 9, 2024

Teachers Ask Better Questions With Feedback That’s Frequent, Personal, and AI-Generated, Study Shows (Newsweek)
December 8, 2023

Grand Challenges Q&A: The Potential of Artificial Intelligence to Empower Teachers and Advance Equity
December 4, 2023

Jing Liu and Wei Ai Part of $1.5M NSF Grant to Improve Middle-Grade Math Education with AI
October 6, 2023

Improving Fairness in Classrooms Through Machine Learning
June 7, 2023

Persistent achievement gaps between different racial and ethnic groups are a stubborn feature of U.S. education systems. Recent advances in machine learning and natural language processing afford an unprecedented opportunity to support instruction in a way that can disrupt existing inequality. Building on a recent project that won a global education technology award, this interdisciplinary study combines cutting-edge machine learning techniques, rich educational theory, and behavioral sciences to deliver an effective, affordable, and scalable mechanism to measure and improve equity-focused teaching practices in K-12 mathematics classrooms. Through a randomized controlled trial that evaluates the effectiveness of the team's tool and dedicated efforts to improve the performance and reduce bias in the machine learning technology used, this project addresses the intersection of two grand challenges faced by our modern society — social and racial injustice and ethical, fair, and trustworthy technology.