Built for Learning: How EdLight Uses Artificial Intelligence for Math Instruction
Saved in:
| Title: | Built for Learning: How EdLight Uses Artificial Intelligence for Math Instruction |
|---|---|
| Language: | English |
| Authors: | Marisa Mission, Michelle Croft, Amy Chen Kulesa, Bellwether |
| Source: | Bellwether. 2026. |
| Availability: | Bellwether. 650 Massachusetts Avenue, NW Suite 600, Washington, D.C. 20001. Tel: 877-636-0909; Web site: https://bellwether.org/ |
| Peer Reviewed: | N |
| Page Count: | 8 |
| Publication Date: | 2026 |
| Sponsoring Agency: | Bezos Family Foundation Chan Zuckerberg Initiative Charter School Growth Fund (CSGF) Overdeck Family Foundation |
| Document Type: | Reports - Research |
| Education Level: | Elementary Secondary Education |
| Descriptors: | Artificial Intelligence, Technology Uses in Education, Mathematics Instruction, Educational Technology, Technology Integration, Elementary Secondary Education |
| Abstract: | The integration of artificial intelligence (AI) into ed tech tools has raised myriad questions about how such advanced technology can both ease burdens for students and teachers and facilitate deep learning. Building on Bellwether's prior work examining how AI could amplify productive struggle and how to measure the impact of AI-powered ed tech tools, this case study series showcases those concepts in practice by spotlighting select organizations and describing their design approaches, trade-offs, and implementation choices. The case studies in this series are drawn from interviews conducted with organization leaders in summer 2025, and each profiled organization reviewed its case study for accuracy in October 2025. For years, math-focused, K-12 ed tech tools assessed students using multiple-choice questions -- easy to grade at scale, but limited in gathering meaningful insights about learning and mastery. For students who struggle, this approach can reinforce deficit-based mindsets, as teachers see wrong answers without understanding where misconceptions originated or what partial knowledge students possess. When generative artificial intelligence (GenAI) arrived in 2022, EdLight Founder and CEO Teryn Thomas saw an opportunity to change this status quo. Instead of multiple-choice questions, EdLight uses GenAI to analyze and provide feedback on students' handwritten math work, helping teachers understand student thinking at scale. In Thomas' words, EdLight helps educators seek "the area between right and wrong," giving teachers more agency than they might otherwise feel with traditional structures and data. This focus on nuanced understanding reflects a core belief that teachers with greater capacity and more intuitive ways of interpreting data will feel more empowered to influence students' outcomes. EdLight uses GenAI to "see" a student's handwritten work and instantly diagnose the student's strategy, whether they were successful, and -- if they were not -- which misconceptions might have prevented the student from succeeding. From there, the tool creates "tailored, tangible, and actionable insights" for both students and teachers. This case study presents how EdLight uses artificial intelligence for math instruction. |
| Abstractor: | ERIC |
| Entry Date: | 2026 |
| Accession Number: | ED681621 |
| Database: | ERIC |
| Abstract: | The integration of artificial intelligence (AI) into ed tech tools has raised myriad questions about how such advanced technology can both ease burdens for students and teachers and facilitate deep learning. Building on Bellwether's prior work examining how AI could amplify productive struggle and how to measure the impact of AI-powered ed tech tools, this case study series showcases those concepts in practice by spotlighting select organizations and describing their design approaches, trade-offs, and implementation choices. The case studies in this series are drawn from interviews conducted with organization leaders in summer 2025, and each profiled organization reviewed its case study for accuracy in October 2025. For years, math-focused, K-12 ed tech tools assessed students using multiple-choice questions -- easy to grade at scale, but limited in gathering meaningful insights about learning and mastery. For students who struggle, this approach can reinforce deficit-based mindsets, as teachers see wrong answers without understanding where misconceptions originated or what partial knowledge students possess. When generative artificial intelligence (GenAI) arrived in 2022, EdLight Founder and CEO Teryn Thomas saw an opportunity to change this status quo. Instead of multiple-choice questions, EdLight uses GenAI to analyze and provide feedback on students' handwritten math work, helping teachers understand student thinking at scale. In Thomas' words, EdLight helps educators seek "the area between right and wrong," giving teachers more agency than they might otherwise feel with traditional structures and data. This focus on nuanced understanding reflects a core belief that teachers with greater capacity and more intuitive ways of interpreting data will feel more empowered to influence students' outcomes. EdLight uses GenAI to "see" a student's handwritten work and instantly diagnose the student's strategy, whether they were successful, and -- if they were not -- which misconceptions might have prevented the student from succeeding. From there, the tool creates "tailored, tangible, and actionable insights" for both students and teachers. This case study presents how EdLight uses artificial intelligence for math instruction. |
|---|
