As schools across the U.S. continue to grapple with student learning loss in mathematics, educators are increasingly turning their attention to artificial intelligence as a potential game-changer, as stated in Education Week. With math scores still lagging behind pre-pandemic levels, many K-12 leaders are searching for innovative tools that can aid both students and teachers in catching up and staying engaged.
A recent nationally representative survey by the EdWeek Research Center, conducted in late 2024 and published in EdWeek Market Brief's special report “What’s Next for the K-12 Math Market,” sheds light on how school and district leaders view AI’s role in math instruction. The survey included 137 district leaders and 217 school leaders and explored expectations for AI in math classrooms over the next five years.
A recent nationally representative survey by the EdWeek Research Center, conducted in late 2024 and published in EdWeek Market Brief's special report “What’s Next for the K-12 Math Market,” sheds light on how school and district leaders view AI’s role in math instruction. The survey included 137 district leaders and 217 school leaders and explored expectations for AI in math classrooms over the next five years.
Optimism for AI’s Role in Math Education
The results point to cautious optimism. Nearly 70% of respondents believe AI will have a “somewhat” or “very positive” impact on math teaching and learning. Only 13% foresee a negative impact, while 17% anticipate a neutral or negligible effect.
AI's promise lies in its ability to offer tailored support. When asked which AI features would most influence their recommendation of a math product, 64% of leaders prioritized tools that help identify students falling behind. Another 61% favored features that assist teachers in developing lessons and materials. A close 59% valued AI that helps students understand their mistakes and how to improve.
However, there was less enthusiasm for AI features that assist with homework (28%) or reduce lesson bias (21%).
AI's promise lies in its ability to offer tailored support. When asked which AI features would most influence their recommendation of a math product, 64% of leaders prioritized tools that help identify students falling behind. Another 61% favored features that assist teachers in developing lessons and materials. A close 59% valued AI that helps students understand their mistakes and how to improve.
However, there was less enthusiasm for AI features that assist with homework (28%) or reduce lesson bias (21%).
Personalized Learning for Better Engagement
“Students are losing interest in math,” said Jie Chao, a learning scientist at the Concord Consortium, an organization focused on improving STEM education through technology. “All these instruction-support needs, in terms of feedback and guiding, tutoring, and personalization — AI could really help.”
Chao emphasized that learning doesn’t end when the school bell rings. AI, she argued, could support not just teachers but also parents and community leaders, particularly in areas where access to tutoring or extracurricular programs is limited.
She offered a compelling example: a rural district might lack resources, but AI can adapt curriculum to resonate with local experiences, such as farming or ranching. “It may be difficult and time-consuming for teachers to manually tailor each lesson, but AI can help contextualize content to relevant examples,” Chao explained.
Interestingly, support for AI in lesson planning was strongest in smaller districts. Among K-12 systems with fewer than 2,500 students, 74% of leaders endorsed AI tools for creating math resources. That number dropped to 52% in mid-sized districts (2,500–9,999 students) and 41% in larger ones (10,000+ students).
Chao emphasized that learning doesn’t end when the school bell rings. AI, she argued, could support not just teachers but also parents and community leaders, particularly in areas where access to tutoring or extracurricular programs is limited.
She offered a compelling example: a rural district might lack resources, but AI can adapt curriculum to resonate with local experiences, such as farming or ranching. “It may be difficult and time-consuming for teachers to manually tailor each lesson, but AI can help contextualize content to relevant examples,” Chao explained.
Interestingly, support for AI in lesson planning was strongest in smaller districts. Among K-12 systems with fewer than 2,500 students, 74% of leaders endorsed AI tools for creating math resources. That number dropped to 52% in mid-sized districts (2,500–9,999 students) and 41% in larger ones (10,000+ students).
Making Math Meaningful
Beyond automation and personalization, Chao highlighted the importance of real-world relevance. “Math modeling is about planning for a day trip or party — all of these problems in real life that you need to solve, and there’s no written word problem for you,” she said.
Artificial intelligence, she suggested, can help design these open-ended, practical challenges that better reflect everyday problem-solving, thus increasing student engagement. “We’ve had teachers do this and tell us that they see a very different side of their students in math classrooms,” she added.
For AI to be truly effective in education, Chao urged developers and education companies to collaborate closely with teachers and communities. “Education companies must understand the ecosystem within the school and the community in developing the technology,” she said. “That means bringing [educators] alongside as developers and designers to understand their needs and concerns.”
As schools look ahead, AI’s role in math instruction seems poised to grow — not as a replacement for teachers, but as a powerful ally in addressing persistent learning challenges and reimagining how students experience mathematics.
Artificial intelligence, she suggested, can help design these open-ended, practical challenges that better reflect everyday problem-solving, thus increasing student engagement. “We’ve had teachers do this and tell us that they see a very different side of their students in math classrooms,” she added.
For AI to be truly effective in education, Chao urged developers and education companies to collaborate closely with teachers and communities. “Education companies must understand the ecosystem within the school and the community in developing the technology,” she said. “That means bringing [educators] alongside as developers and designers to understand their needs and concerns.”
As schools look ahead, AI’s role in math instruction seems poised to grow — not as a replacement for teachers, but as a powerful ally in addressing persistent learning challenges and reimagining how students experience mathematics.