AugmentED is a team of educators, researchers, and technologists working together to build the evidence base for what AI should (and shouldn’t) do in the classroom, and the technology to do it well.
The Challenge
Ready or not, AI tools have arrived in the classroom. Many companies and schools are rushing in before we know what AI can do well, what teachers uniquely bring, or what would actually benefit students. Today’s tools rely on general-purpose AI that was never designed for education, and it shows. We need better evidence on the roles AI should (and shouldn’t) play in schools, and purpose-built technology that can bridge between AI and real classroom needs.
Our Approach
We run an iterative research and development cycle, with educators, researchers, and engineers as equal partners at every step. We start by asking what teachers and students need. Each cycle focuses on one role AI could play in meeting some of those needs. Together, we identify what the role requires but doesn't yet exist, build it, and test it in real classrooms. What we learn informs the next turn of the cycle.
Each turn of the cycle informs the next.
Tap a step to read more. Each turn of the cycle informs the next.
Each co-design cycle produces more than prototypes. It creates evidence about what students need, what AI can do reliably, and what teachers need to use it well. AugmentED turns those lessons into research, technical foundations, and tools the field can trust and build on.
Ideas and evidence that help the field reason about AI in education: research insights on the roles AI should (and shouldn’t) play in the classroom and methods for evaluating how well AI can play those roles.
Reusable infrastructure that future classroom tools can be built on, from validated AI capabilities to the datasets that power them. We build these to work across many subjects and types of schools.
Tested classroom resources that help educators apply AI, including AI-powered applications, implementation guides, and proven methods for teaching alongside AI, all built with teachers, not for them, to solve real challenges in their classrooms.
Our Current Work
In our first cohort, teachers from several pioneering high schools worked with researchers and engineers to co-design AI-powered tools. Each project below is a work in progress, and each one feeds reusable capabilities back into a foundation that others can build on.
All three put the same AI role to work: AI as a “cognitive extender.” In this role, AI surfaces patterns hidden in more information than any individual teacher or student could track alone.
Crosstown High
Students learn more deeply when new material connects to what they already know and care about. This tool maps a teacher’s course material to each student’s pre-existing knowledge, experiences, and interests and then suggests personalized connections.
Museum High School
During multi-week projects, students respond to teacher prompts with short voice memos. The tool surfaces where each student and group is progressing, getting stuck, or drifting off track, so teachers can provide specific, meaningful feedback for every student.
High Tech High Mesa & High Tech High International
After students reflect on their small-group work, the tool generates insights about how each group is functioning. It makes group dynamics visible to teachers in real time, so they can coach students on collaboration and repair interpersonal problems before they harden.
Our Thinking
We work with university and research partners to study what each classroom role for AI makes possible, where it falls short, and what we can build to shift those limits. We publish what we find so the whole field can move forward together. Here are three recent papers:
Can AI help assess a skill as complex as critical thinking? We show that AI models—when given skill definitions and training—can measure some critical-thinking subskills in student writing, and we map where they still fall short.
We share a standardized, step-by-step process for improving and validating the capacity of AI systems to detect complex skills like critical thinking, so the field can build AI measurement tools without starting from scratch every time.
Forthcoming
Arguing over whether AI is good or bad for education misses the point: AI isn't one thing. We define five distinct roles AI can play in the classroom, and show how naming a tool's role determines what it should do, how to judge whether it works, and what safeguards it needs.
We co-design with educators, publish what we learn, and create infrastructure the whole field can build on. If that's the future of AI in education you want, come build it with us.
AI is arriving in classrooms whether schools are ready or not. The danger is that some companies and schools are rushing in without asking what AI can do well, what teachers uniquely bring, or what students actually need.
Most of us built our critical thinking, writing ability, and judgment without AI, which is what allows us to use it well now. We direct it rather than defer to it. Students who lean on AI too early can short-circuit those skills before they form.
It's a safe bet that AI can improve how people learn. But nobody has discovered how. The entire field fundamentally lacks research into the right ways to integrate AI into the classroom.
Ed tech companies build the apps teachers and students use. The big AI labs build the underlying models that power these apps. What's missing is the layer in between: the foundational capabilities that let AI understand what a student knows, measure skills as complex as critical thinking, and adapt to what's happening in a real classroom.
Parents and teachers are alarmed. Some districts are pushing screens and AI out of schools entirely. This instinct is understandable, but both extremes carry real costs. Letting AI take over the classroom would stunt student learning and hollow out the relationships it depends on. Yet pushing AI out altogether leaves students unprepared for a world that already runs on it.
The gap exists because frontier AI and classroom learning operate on different timelines and constraints. Our work closes that gap by creating the infrastructure that lets them work together—safely, effectively, and in service of what students actually need to learn.
We believe better educational AI will emerge from discovering what classrooms actually need, building solutions with educators, testing them in real classrooms, and using what we learn to improve the technology. That's why every AugmentED project combines research and development in an iterative co-design cycle, carried out by teams of educators, researchers, and engineers.
Education technology companies build the applications teachers and students use every day. The large AI labs build the underlying models. What's missing is the layer in between: the capabilities that let AI understand what a student knows, measure skills as complex as critical thinking, and adapt to what's happening in a real classroom. That's the layer we are building.
01 Define the role
Each cycle focuses on one role AI could play in meeting real classroom needs, such as deepening a teacher's understanding of her students' prior experiences and interests, assessing complex skills, or facilitating feedback. We select and shape each role with researchers, educators, and engineers. That role becomes the North Star for everything that follows.
02 Build the capabilities
Our researchers and engineers then build the underlying infrastructure, with educators informing the work: the reusable technical capabilities a tool needs to play its chosen role well. For the roles we're currently exploring, that includes building capabilities such as validated ways for AI to measure and support durable skills and a living map of how the ideas in a particular teacher's class connect to each other and to students' prior experiences and interests. Most of these capabilities don't exist yet. Once we build and prove them, they can be reused, adapted, and made available to others to build on.
03 Co-design the tools
Our teams of educators, researchers, and engineers use that infrastructure to build and test AI-powered tools, and new ways of teaching alongside them. This second part is crucial: an AI tool might help students evaluate sources or collaboratively solve problems, but it's only truly effective when paired with a teaching approach that combines what AI and human teachers each do best.
04 Test, learn, begin again.
Every tool is tested in classrooms by teachers and students. What we learn tells us which capabilities to build or improve next, while new and improved capabilities make better tools possible. Then the cycle turns again.
Each turn of the cycle strengthens the field's understanding of what roles AI should play, what capabilities those roles require, and how those ideas translate into practical tools that genuinely improve learning.
Every co-design cycle generates evidence about what AI should do in education, when it works, and why. We openly share our research findings, evaluation methods, and models for teaching and learning alongside AI, so the field can build from evidence instead of assumptions.
Behind every successful classroom tool are foundational capabilities that make it possible. We develop and share reusable capabilities, from specially trained models and datasets to ways of representing what's being taught and learned in a classroom, that any educational AI application can build on.
Research and capabilities only matter if they improve learning. We build and validate classroom tools and teaching methods alongside educators and students to demonstrate what works in practice.
AugmentED brings together people from classrooms, research labs, and engineering teams who share a conviction that AI should augment human teaching, not replace it. We build the infrastructure that lets teachers and students work alongside frontier AI in ways that deepen their thinking, learning, and relationships rather than short-circuit them.
Founder & Executive Director
Co-Founder & Chief of Research and Impact
Chief Technology Officer
Vice President of Education Innovation and Partnerships
Associate Professor of Computer Science, University of Massachusetts Amherst
Professor of Artificial Intelligence and Education, Adelaide University
Data Scientist
Graduate Student, University of Minnesota
Assistant Professor, University of Minnesota
Humanities Teacher, 504 Coordinator
High Tech High Mesa
San Diego, CA
Principal on Special Assignment, Innovation Design
Grand Rapids Public Museum High School
Grand Rapids, MI
Social Studies Teacher
Grand Rapids Public Museum High School
Grand Rapids, MI
Science & Computer Science Teacher
Grand Rapids Public Museum High School
Grand Rapids, MI
Science Teacher, Director of Research & Innovation
Crosstown High School
Memphis, TN
STEM, Design, and Media Teacher
Crosstown High School
Memphis, TN
Math Teacher, Math Department Lead
Crosstown High School
Memphis, TN
Computer Science Teacher, 9th Grade Lead
Crosstown High School
Memphis, TN
Product Design Consultant
Engineering Consultant
Project Consultant & Manager
Principal Engineer
Program Manager
We co-design with educators, publish what we learn, and create infrastructure for the whole field.
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