The National Science Foundation has slashed funding available for research into STEM instruction in K-12 schools.
The move—which amounts to a roughly 50% cut for such research, experts calculate—also cut the maximum amount available for STEM education research grants by 85%, from $5 million to $750,000.
And the NSF refocused the grants primarily on artificial intelligence, a Trump administration priority.
The NSF outlined this new approach in a call for grants released last month.
The call for grants invited researchers from higher education institutions, nonprofit organizations, for-profit companies, and state or tribal governments to apply for a slice of $30 million from the administration’s NSF STEM K-12 program.
But the call for grants document also noted that four other programs aimed at figuring out how K-12 educators should teach science, technology, engineering, and math, were now “archived.”
Those programs are:
- Advancing Informal STEM Learning, or AISL: Most recently funded at $34 million a year, this program helped study how best to advance STEM learning in settings such as libraries, museums, or after-school programs. Some of its findings have been applied to children’s programs on public broadcasting stations, experts said.
- Computer Science for All: A $20 million program aimed at funding research into computer science education.
- Discovery Research PreK-12: A $50 million program that supported broad research on teaching STEM subjects in K-12 schools, including much of the research tied to the Next Generation Science Standards, which have been adopted by 49 states.
- Translation and Diffusion: A $7 million program that helped experts and school systems use research to improve education practice.
A spokesperson for the NSF declined to comment for this story.
New STEM curriculum often starts with NSF-funded research
These programs—and even the NSF itself—may not be familiar to many classroom teachers. But educators interact every day with products and programs informed by the research they have financed.
“We’re hemorrhaging our future with this,” said Bill Penuel, a professor in the school of education at the University of Colorado in Boulder. “The areas of science we care about, that kids will get employment in, they are cutting-edge science, and the materials need to be updated.”
Research financed by NSF’s STEM education programs translates into practical classroom materials.
For instance, Scratch, a beginning coding language, was developed in part through research funded by the NSF, said Victor Lee, an associate professor at the Stanford Graduate School of Education.
Slashing the size of the maximum grant down to $750,000 means that it will be virtually impossible to fund the kind of studies that lead to evidence-based research into how to help students learn STEM subjects, Penuel added.
Those types of projects—which might, for example, examine the effectiveness of a particular learning intervention or a new science and math curriculum—require examining a large enough sample of schools to draw meaningful conclusions, observing classrooms, interviewing teachers to understand their perspectives, and collecting student data on learning outcomes.
“That’s how much money it takes to do those large-scale studies,” Penuel said. With the smaller awards, “there will be no more studies like that.”
What’s more, focusing the program so tightly on AI may hinder the goal of improving how AI technology is used in teaching and learning, since AI intersects with both math and science education in ways educators and experts are still struggling to understand, said Lee, who has worked on AI literacy for the Organisation for Economic Cooperation and Development, or OECD.
“This exact focus on AI is very narrow and constraining,” Lee said. “It would be healthier to have a broader research ecosystem.”
