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An AI tutor alone may not be enough to significantly improve student learning, according to findings from a two-year study conducted in 18 middle schools in Tennessee.
The study, conducted by the National Bureau of Economic Research (NBER), examined the use of Khanmigo, an AI-powered tutoring tool developed to guide students through problems rather than simply provide answers.
Students used Khanmigo during regular remedial mathematics sessions. Those who used the tool saw their math scores increase by an average of 1.3 points per academic term. Over the course of a school year, the estimated impact was equivalent to about 0.06 to 0.08 standard deviations. For students who actively engaged with the program throughout the year, researchers estimate that the effect could have reached 0.14 standard deviations.
But the study’s findings point to a key limitation: access to an AI tutor does not necessarily mean students will use it in ways that support learning.
Nearly all students — 96% — tried Khanmigo at least once. Yet students with average math skills sought guidance from the AI tutor during only about one-third of the time available.
The tool was used even less when students struggled. After giving an incorrect answer, students asked Khanmigo for help in just 17% of cases.
Researchers also found that many requests for guidance did not lead to meaningful interaction with the AI tutor. Instead, students often submitted answers or selected one of the suggested hints. This limited the kind of mathematical dialogue that could have allowed the AI system to provide more personalized support. The findings suggest that the effectiveness of AI tutoring may depend not only on how well the technology is designed, but also on how students engage with it.
The National Bureau of Economic Research, an independent economic research organization, is governed by a 51-member Board of Directors that includes representatives from leading research universities, professional economic associations, business and labor organizations.
