Research in Action

Since the launch of commercially available generative AI, the most common engagement platform is through chat. For all the appeal and flexibility of using natural language to interact with these AI models, it is not always easy to get them to generate the desired output from a question or request. For this reason, several Edtech platforms have designed custom fine-tuned education chatbots to cater to educator needs; yet, we know little about how educators are using these chat-based interfaces.

AI tools are arriving in schools faster than research can evaluate them. Teachers are experimenting with new tools and districts are writing policies, all while students are already using AI both inside and outside the classroom.

But for many education leaders, a basic question remains: What does rigorous research actually say about how AI affects teaching and learning?

To help answer that question, we released a new report: The Evidence Base on AI in K-12: A 2026 Review. The report reviews the current research, focusing specifically on studies that convincingly estimate causal impact, meaning studies that can tell us whether an AI tool changed outcomes for students or educators.

Education is one of AI’s most promising frontiers. With tools like ChatGPT, personalized learning support can be available to any student, anywhere, at any time. 

But the education sector is still early in its understanding of the impact of AI on learning outcomes. Last year, our team set out to study the use of tools like study mode⁠ and found promising gains in student performance. But our research also raised an important question: how can we assess how AI influences a learner's progress over time, not just on a final exam?

This is a broader ecosystem challenge. To-date, most research methods focus on narrow performance signals—such as test scores—and lack the ability to assess how students actually learn with AI in real-world settings, and how that use shapes outcomes over time. 

Since the release of user-facing generative artificial intelligence (AI) tools like ChatGPT in 2022, AI adoption has quickly permeated many sectors, including education. New EdTech platforms are constantly emerging, often designed to help teachers with tasks ranging from lesson planning to worksheet generation to assessment grading. The emergence of these new technologies spark both excitement and concern, not only in teachers and students, but also among parents and policymakers. Yet, we know little about what tools teachers are using, how much they are using these tools, and what implications this use has for student learning.

A new collaboration between Stanford’s SCALE and OpenAI, the creator of ChatGPT, strives to better understand how students and teachers use the popular AI platform and how it impacts learning

Education is one of the fastest-growing use cases of AI products. Students log on for writing assistance, brainstorming, image creation, and more. Teachers tap into tools like attendance trackers, get curriculum support to design learning materials, and much more.

Yet despite the rapid growth – and potential – a substantial gap remains in knowledge about the efficacy of these tools to support learning. 

A new research project from the Generative AI for Education Hub at SCALE, an initiative of the Stanford Accelerator for Learning, aims to help fill that gap by studying how ChatGPT is used in K-12 education. In particular, the research will examine how secondary level teachers and students use ChatGPT. 

This study provides compelling evidence that tutoring can do more than boost test scores; it can actually get students back in the classroom. On average, students were 1.2 percentage points less likely to be absent on days when they were scheduled to receive tutoring, suggesting that they are motivated to participate in tutoring. This impact was even greater for middle schoolers and students who’d missed more than 30% of school days the prior year. The study also found that the design matters: tutoring only improved attendance when it combined at least two evidence-based features like small groups, frequent sessions, and in-school delivery.