NSF, Partners Commit $9M to AI-Driven K-12 Math Through CAMEL
The U.S. National Science Foundation's Directorate for Social, Behavioral, and Economic Sciences has launched the Collaboratory to Advance Mathematics Education and Learning (CAMEL). Backed by $9 million and supported by philanthropic partners including the Walton Family Foundation, CAMEL connects AI, learning science, education practice, and data science to improve K-12 math.
"CAMEL reflects NSF's commitment to advancing the nation's science and technology enterprise by strengthening mathematics education," said Kaye Husbands Fealing, assistant director for NSF SBE. "The knowledge and skills supported through this program are essential for student success and for building a workforce prepared to lead in artificial intelligence, biotechnology, and quantum technologies."
What CAMEL Is
CAMEL is a two-phase effort to build durable, evidence-driven progress in math education. It funds research networks that produce AI-ready datasets and then connects those networks into a national collaboratory that keeps the work going beyond individual awards.
How the Two Phases Work
- Phase I: Create new interdisciplinary research networks that generate or enhance high-value AI-ready datasets to study K-12 math learning. Each network must include learning scientists, classroom practitioners, and data scientists working together.
- Phase II: Open only to Phase I awardees. Establish a national collaboratory-a socio-technical platform-to build community, grow capacity, coordinate resources, and keep collaboration strong across projects and sectors.
Why This Matters for Schools and Districts
- Stronger math foundations that support AI literacy and smart use of emerging technologies in classrooms.
- Access to AI-ready datasets that can inform curriculum, intervention design, and tool selection.
- Closer ties between researchers and practitioners, so classroom realities shape the research-and vice versa.
What You Can Do Now
- Identify partners: Connect your district's math leads with local universities, research labs, and data teams that could join or form a CAMEL network.
- Prepare your data: Audit current math assessment and instructional data. Note formats, consent practices, and privacy safeguards to support ethical data sharing.
- Prioritize equity: Ensure datasets and pilots reflect diverse learners, including multilingual students and students with disabilities.
- Plan professional learning: Budget time for teachers to pilot AI-enabled tools, analyze results, and refine practice.
- Align initiatives: Map CAMEL participation to existing math goals, MTSS/RTI efforts, and curriculum adoptions to avoid extra burden on schools.
Policy Link
CAMEL supports the administration's focus on AI education by strengthening core math skills for AI literacy and by creating new AI-ready datasets. For background on NSF's social and behavioral science portfolio, see the NSF SBE directorate.
Key Date
To learn more, plan to join a webinar on Tuesday, January 6, at 4 p.m. EST. Please register in advance.
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