• The ‘Nonexistent’ Research on AI’s Benefits for Education

    | Inside Higher Ed

    Colleges are going all in on artificial intelligence. But it could be a long time before independent research emerges on how it should—or shouldn’t—be used to improve learning outcomes.

    “Can you get students to use AI tools consistently enough to even test whether or not they’re effective?” said Carly Robinson, director of research at Stanford University’s Systems Change Advancing Learning and Equity initiative, which tracks emerging research on AI and education. “The design has to be really deliberate just to get students to engage with these tools in the first place.”

    Although high-quality causal research is slow going, the limited findings so far support a measured approach to AI adoption in higher education.

    “There is increasing evidence that AI has the potential to benefit learning, but using it on its own without intentional design or guardrails probably reduces learning through cognitive offloading,” Robinson said. “There’s logic to the idea that AI can improve learning and potential for it to be transformational in education, but we’re a ways off from that.”

  • Less than half of states fund tutoring directly. Florida is one of them

    | Tampa Bay Times

    The big story: Florida is one of 24 states, including Washington D.C., that currently funds K-12 tutoring directly, according to a new review published today by Stanford University.

    The university’s third annual National Student Support Accelerator looks throughout the nation to analyze how states support high-impact tutoring and the policies and funding they have in place for it.

    High-impact tutoring is an immersive form of tutoring based on relationship building and individualized instruction known to improve education outcomes and even school attendance, according to lead author of the brief Kathy Bendheim.

  • Schools Ban AI For Students While Teachers Get It Free

    | Forbes

    There is also a growing body of evidence about what happens when AI is used directly with students.

    Stanford’s National Student Support Accelerator and its AI Hub for Education recently reviewed research on AI tutoring. One of the most interesting conclusions was that the strongest results were found where AI supported human tutors. AI-only tutoring was much less convincing.

    In some of the studies, engagement was a serious problem. In two randomized trials, 40% to 47% of students never used the AI platform at all, while those who did averaged only two to five minutes per week. There is an assumption behind quite a lot of education technology that giving a student access to a useful tool means they will naturally use it in a useful way. Often they do not.

  • OpenAI launches Learning Lab to build evidence base for AI in education

    | Ed Tech Innovation Hub (ETIH)

    The research network will bring together researchers, educators, students, and builders to study AI's effects on learning, teaching, assessment, and education systems

    OpenAI's Education team held the first Learning Lab convening at its San Francisco headquarters last week, bringing together researchers, educators, and builders from several countries.

    Researchers from the University of Tartu presented work connected to Estonia's national AI rollout and their study of how AI affects cognition over time. The University of Tartu and Stanford University are also working with OpenAI on new approaches to measuring learning outcomes.

    The meeting opened additional areas of collaboration, including research with Stanford's Accelerator for Learning, participation in the University of Oxford's AIEOU global community of practice, and work on challenges from Cornell University's National Tutoring Observatory.

  • AI Tutors Not Yet a Replacement for Humans, Research Says

    | The 74

    With tools like Amira and Khanmigo, ‘the take-up is very low,’ according to Stanford University’s Susanna Loeb.

    Wendy Graham’s two kids first encountered Amira, a popular artificial intelligence tutoring platform, in 2025, during a summer reading program in New Mexico. She also used it at home with her daughter, now a fourth grader.

    But she found that the purple-haired avatar with the big, round glasses didn’t seem to understand where her daughter was struggling. When she stumbled over “usually,” the “learning agent” wanted her to repeat the word and spend time defining it. 

    “She knew what the word meant; she just didn’t decode the word,” Graham said. Amira, in her view, “got hung up on all the wrong things.”

    Her son, on the other hand, never gave Amira a chance.

  • Stanford Summer Research Fellows Showcase Education Research

    | Stanford SCALE Initiative

    Thirteen Stanford undergraduates presented their research at the final showcase for the 2026 Summer Research Fellowship for Educational Impact on Aug. 27. 

    The fully funded program engages students in rigorous, faculty-led empirical research addressing critical issues in education, particularly equity. Working in a collaborative cohort, fellows build foundational research skills while contributing to interdisciplinary studies with the potential to influence education policy and practice. 

    Presentation topics included educational technology, literacy assessment, school desegregation and closures, student enrollment, childcare access, language processing, and school board elections. 

    The 2026 fellows were Aaliyah Agyen, Hallie Dong, Naomi Kao, Morgan Deale, Bryan Gonzalez, Nina Carbuccia, Aydin Alsan, Crystal Peng, Thomas Raith, Miranda (Hao) Li, Jocelyn Moreno, Joseph McDonald, and Calista Woo.

  • When Does AI Help Most With Tutoring? What Emerging Research Says

    | Education Week

    To help educators navigate the AI tutoring landscape, the National Student Support Accelerator and the AI Hub for Education at Stanford’s SCALE Initiative recently published a research brief examining the current research on the effectiveness of using AI in tutoring.

    As schools deal with an uncertain funding environment, they might consider using AI tutoring to reduce costs, and “we wanted to make a more actionable tool for education system leaders on what the evidence says about AI tutoring,” said Chris Agnew, the director of the AI Hub for Education, which researches AI’s impact on student learning.

    Part of the challenge with researching the effectiveness of AI tutoring is that the term could refer to a wide range of tutoring models, Agnew said.

  • Can Lighter-Touch Tutoring Programs Benefit Kids Too?

    | Education Week

    Intensive tutoring is supposed to be one of the most effective routes to raise student achievement. But it doesn’t always work out that way.

    While meta-analyses of studies on high-dosage tutoring programs find big, positive impacts on learning, it’s often challenging for districts to implement these time- and labor-intensive initiatives in practice. Recent studies of post-pandemic tutoring programs have shown smaller-than-expected gains, or even no student improvement at all.

    Could a lighter touch tutoring program be easier for schools to maintain, and still move the needle on student achievement? One new study suggests yes.

    The paper comes from researchers at the National Student Support Accelerator, a program of the SCALE Initiative at Stanford University that studies high-impact tutoring. They tested a tutoring intervention called Chapter One, in which part-time tutors delivered 5-10 minute lessons throughout the school day, while students were still in their regular classrooms.

  • Even With Human Help, Kids Need Motivation to Use AI Tutors. The Question Is What

    | The 74

    Artificial intelligence-based tutoring programs promise something schools have long struggled to provide: personalized instruction for every student at a fraction of the cost of traditional 1-on-1 tutoring. 

    But for that promise to be fulfilled, students have to use the AI tools. New research suggests that may be much harder to achieve than schools assume. 

    In a paper describing the results of randomized controlled trials led by the Stanford SCALE Initiative, 355 students in grades 1 to 5 in two school districts were assigned either to use an AI literacy tutor independently or to use the same platform with support from a human tutor. In both, the goal was to improve reading achievement.

  • Homework Helper or AI Tutor? The Difference Determines What Students Learn

    | Edtech Insiders

    As the catch-all term “AI tutoring” captures the public imagination, it’s time to define and measure what actually meets the bar for a “tutor.”

    A new SCALE brief from Stanford offers a useful route through this definitional problem. Instead of sorting tutoring models by how sophisticated their AI appears, AI Tutoring Is Not a Monolith places them on a spectrum of relational intensity: the depth and consistency of the human connection surrounding the student.

    At the high-intensity end, a human tutor leads the instruction and holds the relationship, while AI may assist with lesson preparation, data analysis, or suggestions. In the middle, the student works directly with an AI tutor while a person oversees the process and intervenes. At the lowest-intensity, the student works with an AI-only tutor without direct human oversight.