The K-12 AI Infrastructure Program has released its newest request for proposals (RFP), titled Integrating Public Goods to Advance AI-Enabled Formative Assessment. This RFP seeks submissions to create a coherent package of open-source tools and workflows. These packages will demonstrate, document, and enable the use of existing public goods to improve AI-enabled formative assessment tasks in K-12 education.
In this next round of funding, applicants will need to address the present problem of poor coordination between human teachers and AI-enabled technologies with regard to known failure points, such as incoherent instruction, insufficient adaptation to learner variability, and limited transparency/control for teachers over AI outputs. This work aims to produce open-source software, such as enhanced AI agent harnesses or reference architectures, that makes education-specific public goods accessible, testable, and integrable for downstream developers while giving educators greater agency.
Grant Overview
“In our final grant competition this year, we are seeking to connect the dots—we want to show how investments in underlying infrastructure components such as datasets and benchmarks can lead to development of better AI-based applications in education,” said Rebecca Griffiths, program design director of the K-12 AI Infrastructure Program. “With this round of grants we want to lower the barriers for edtech developers to build on this infrastructure and show what kinds of improvements are possible.”
The K-12 AI Infrastructure Program, a multi-year initiative led by global education nonprofit Digital Promise, aims to bridge the gap between the scientific principles of teaching and learning and the growing potential of artificial intelligence. Core partners include Learning Data Insights, DrivenData, Massive Data Institute at Georgetown University, and Catalyst @ Penn GSE.
The review process will bring together funding partners, edtech developers, researchers, and practitioners to ensure a rigorous and collaborative evaluation. After an initial review of submitted proposals, selected recipients will be announced in early 2027. Additional funding opportunities will be announced in 2027.
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