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AI and Emerging Tech

Igniting a National Leadership Movement for AI-Enabled Reading Research

Yenda Prado, Jeremy Roschelle

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A first-grade boy and his kindergarten friend read together on a bench outside.

Key Ideas

  • This is the first of a three-part series highlighting the efforts of Digital Promise’s U-GAIN Reading R&D Center (U-GAIN Reading) to advance the role of generative AI to support student literacy.
  • U-GAIN Reading will provide national guidance on the use of generative AI to improve reading instruction for grades 1-3.
  • U-GAIN Reading will launch a three-part national leadership strategy to amplify insights on using generative AI to improve reading instruction through events, a national leadership cohort, and research.

As National Reading Month concludes, we’re eager to share the work of Digital Promise’s U-GAIN Reading R&D Center. U-GAIN Reading, with support from an Institute of Education Sciences (IES) grant, is a research and development hub dedicated to exploring how teachers can effectively use generative artificial intelligence (AI) to enhance elementary reading instruction in grades 1-3.

Laying the Foundation: U-GAIN Reading

Over five years, U-GAIN Reading will use insights from the Science of Reading to advance how we use reading technology to give students feedback and support as they read decodable text out loud. Our team will identify ways to improve the accuracy of reading technologies to hear students as they read out loud, to customize texts to work with each students’ strengths and needs, and to improve students’ interactions with technology to support their fluency and comprehension.

Our research will build on Amira, a powerful reading technology that has a research base and is already serving millions of students across the United States. Our research team will co-design reading intervention activities for Amira. These include individualized tutoring lessons, to be tailored to each learner’s specific reading strengths and needs across reading ability, specific letter, sound, and word recognition skills, and vocabulary development.

We are working with schools with developing readers in grades 1 to 3, including many students who are English learners (ELs). This is relevant because “hearing students accurately” is more challenging for technologies when listening to students with speech patterns that differ from standard American English. To give a sense of the challenge, only 33% of ELs meet the National Assessment of Educational Progress (NAEP) Basic reading level, compared to 67% of all fourth-grade students. Working with ELs provides a strong opportunity to advance how reading technology can be used to support developing readers, as well as advance our goal of serving every reader in each classroom.

The Spark: Our Inaugural National Leadership Kickoff

U-GAIN Reading will also foster national leadership that goes beyond any specific technology, grade level, or population of students. We launched our national leadership initiative in January 2025 and we have already hosted various presentations across the country, including the AI K12 Deeper Learning Summit, which brought together representatives from 118 districts across 31 states earlier this year.

An image of fourty educators and leaders having roundtable discussions at the K12 AI Deeper Learning Summit.
A group of 40+ educators and leaders discusses AI-enabled technologies to support student reading at the K12 AI Deeper Learning Summit.

At the summit we facilitated discussions among more than 40 educators, leaders, and researchers about how they use technology to help students learn to read. Educators shared many insights, including the need for:

  • Customizable texts to meet individualized student needs
  • Decodable texts that are interest-driven and relate to other school content
  • Reading technologies interweaving phonics, content knowledge, and vocabulary support

Following the event, we have begun conducting interviews with educators to better understand how they use technology for reading and how they would like to see it improved. If you have ideas, please contact us!

Looking Forward: Key Elements for a National Leadership Strategy

The U-GAIN Reading team will continue to plan national leadership activities across three key leadership strands:

  • Hosting AI Literacy Events: We will facilitate workshops at national convenings, such as the AI K12 Deeper Learning Summit discussed above. These events provide platforms for sharing knowledge, fostering discussions, and raising awareness about our national initiative to amplify the potential of using AI-enabled digital learning practices and tools to support students’ reading development.
  • Growing a Practitioner Leadership Cohort: To create a lasting impact, we will connect leading educators nationwide through the U-GAIN Reading National Leadership Cohort, provide them with opportunities to learn from each other and from experts, and amplify their messages.
  • Amplifying Reading Best Practices & Research: We are committed to identifying and sharing best practices for building a successful national strategy to support the uptake of Science of Reading practices in the use of AI-enabled digital learning tools. Over time, we will be sharing what works on our website, on social media, and through future blog posts.
Want to learn more about U-GAIN Reading National Leadership efforts?
  • If you are a K-6 educator, reading coordinator, or specialist interested in joining the U-GAIN Reading National Leadership Cohort please complete the educator form.
  • If you are a school district leader or superintendent interested in nominating educators for the National Leadership Cohort please complete the nomination form.
  • For additional questions about UGAIN-Reading or our national leadership efforts, contact Yenda Prado at yprado@digitalpromise.org.

Authors

Yenda Prado

Jeremy Roschelle

Co-Executive Director, Learning Sciences Research

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Jeremy Roschelle, Ph.D., serves as co-executive director of Digital Promise’s Center for Learning Sciences Research (CLSR) where he leads research on the future of learning with technology. He co-leads the NSF Engage AI Institute and leads the U-GAIN Reading R&D Center, both of which investigate advanced uses of AI in education. Dr. Roschelle is a Fellow of the International Society of the Learning Sciences, and is internationally known for his work on artificial intelligence, computer-supported collaborative learning, learning mathematics with technology, and on scaling up research-based technologies. Over his 30+ year career, he has authored about 200 publications. His publications have about 28,000 citations and he holds 10 patents.

At Digital Promise, Dr. Roschelle oversees a dedicated group of researchers and learning scientists working to improve teaching and learning across preschool, PreK-12, and postsecondary programs. His focus is particularly on improving the infrastructure for generating research evidence and creating an infrastructure for learning-sciences-based applications of AI. Programs including SEERNet, AIMS EduData, and SafeInsights are creating state-of-the-art approaches to generating evidence on digital learning platforms. The K-12 AI Infrastructure Program is funding public goods, cultivating datasets, benchmarks and models that are grounded in the learning sciences.

Prior to joining Digital Promise, Dr. Roschelle led some of the most important research studies on the efficacy of technologies for learning mathematics. He is also well-known for his contributions to collaborative learning and his leadership of several national research hubs related to educational technology. Over the course of his career, he has secured and managed tens of millions of dollars in highly competitive external funding from federal agencies and global foundations. His research has contributed to policy, products, and into practical applications in schools. He also communicates about learning sciences research and AI directly to the public through his podcast, Future Fluent, and through his large following on LinkedIn.

Dr. Roschelle earned an bachelor’s degree in Computer Science  from the Massachusetts Institute of Technology and a Ph.D. in learning sciences from the University of California, Berkeley. He enjoys jazz, backpacking and photography.

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