First Grantees of the K-12 AI Infrastructure Program

Following a competitive review process that brought together funders, researchers, developers, and educators, Digital Promise and its partners selected four organizations to receive grants for projects lasting six to 12 months. Recipients include:

• Learning Equality, PI: Richard Tibbles – A Benchmark for AI Identification of Science Misconceptions in Free-Form Student Responses
• Princeton University, PI: Tammy Kwan – Pipeline for Training Simulated Student Models with Reduced Human Data
• National Tutoring Observatory/Cornell University, PI: Allison Koenecke – Open Leaderboards for Benchmarking Automated Speech Recognition in Educational Contexts
• Stanford University, PI: Hariharan Subramonyam – KB-TutorBench: A Multimodal Knowledge-Building Dataset for AI-Enabled Formative Assessment

“The projects chosen for funding are applying advanced data science approaches, often proven in other fields, in education contexts,” said John Whitmer, senior researcher and founder of Learning Data Insights. “It was a difficult selection given the depth and breadth of responses that we received, and I look forward to seeing the public goods emerge from these projects for the field.”

This initiative is supported by Learning Commons, Charles and Lynn Schusterman Family Philanthropies, Gates Foundation, Overdeck Family Foundation, Valhalla Foundation, and Walton Family Foundation. These projects reflect the range of ways AI could better support teaching and learning. Each project is designed with a focus on students and communities who have been historically underserved. Over four years, the program will continue to fund the development of these shared public goods to improve quality, relevance, and trustworthiness of AI in education.

Our team will be making additional grants in coming months and years, with a total of approximately 30 grants expected in the life of the program.