NSF AI grant $3.78M: training K-12 teachers to teach AI at national scale — "AI PD Weeks" (CSTA)
Most K-12 teachers lack preparation to understand how AI works or how to teach it. The NSF awarded about $3.78M to extend a proven multi-state teacher PD model into AI, equipping thousands of teachers to bring "creating with AI, not just consuming it" to hundreds of thousands of students.
Grant overview (primary data)
- Award amount$3,779,879 / Est. total $11,539,324
- RecipientCOMPUTER SCIENCE TEACHERS ASSOCIATION, LLC.(NY)
- ProgramRobert Noyce Scholarship Pgm, CER-ComputingEducationResearch, TIP-CHIPS KTA-1 AI-ML
- Period2026-04-01 〜 2029-03-31
- FunderU.S. National Science Foundation (NSF) / NSF
Key points
- Builds K-12 teachers' capacity to teach AI at national scale
- "Creating with AI," not just consuming it — cultivating makers alongside foundational CS
- Intensive summer learning plus sustained support via existing state/local networks
- Thousands of teachers → hundreds of thousands of students reached
- Includes CHIPS Act AI/ML talent (KTA-1); about $3.78M; CSTA; 2026–2029
The NSF awarded about $3,779,879 to the Computer Science Teachers Association (CSTA) project "AI PD Weeks: CS Foundations for Creating with AI" (NSF Award 2607763; programs include Robert Noyce Scholarship and CHIPS KTA-1 AI-ML; April 2026 – March 2029).
Per the abstract, AI is rapidly transforming work, civic life, and learning, yet most K-12 teachers lack the preparation to understand how AI systems work, how they connect to foundational computer science, and how to design instruction in which students meaningfully create with AI rather than simply consume AI-generated outputs. The project responds to this national need by extending a proven, multi-state computer-science teacher professional-development model into a coherent, AI-focused initiative. AI Professional Development Weeks combine intensive, strand-based summer professional learning with sustained community support through existing state and local networks, creating a scalable infrastructure for rapidly expanding AI teaching capacity. It aims to equip thousands of teachers across multiple states with the content knowledge and instructional strategies to expand AI and CS learning for hundreds of thousands of students.
Why it matters: the heart of this project is an educational stance of "creating with AI" rather than merely using it — cultivating, alongside foundational computer science, the ability to understand how AI works and become a maker rather than a passive consumer. And rather than training teachers one by one, it leverages existing teacher networks to scale nationally — a realistic way to broaden reach on a limited budget. The inclusion of the CHIPS Act's KTA-1 (AI/ML talent) is telling: it positions the national semiconductor-and-AI talent strategy to build from the broadest possible base — K-12.
Why it matters
A concrete effort to build the AI talent pipeline from its broadest base, K-12 education. The "create, don't just consume" stance and the design that leverages existing networks to scale nationally are useful references for AI-literacy and talent strategy.
FAQ
What does "creating with AI" mean?
Why use teacher networks?
Sources (primary)
Source: NSF Award Search (U.S. National Science Foundation, public domain). Amounts are the obligated amount. For privacy, we do not handle principal investigator names.
- NSF Award (original, official)
- NSF Award ID: 2607763