Generative AI has been promoted as the technology that could transform education by providing every student a personal tutor. We provide some of the first large-scale experimental evidence, from a two-year cluster randomized trial in 18 Tennessee middle schools in which randomly assigned students used Khan Academy with its AI tutor, Khanmigo, configured to coach rather than give answers, during existing daily remedial mathematics sessions. Assignment raises math achievement by 1.3 national percentile ranks per term, or about 0.06 to 0.08 standard deviations over a school year; the implied effect of a full year of active participation reaches 0.14 standard deviations. These gains resemble those from Khan Academy practice without AI assistance. One explanation is that students used the tutor infrequently and, when they did, rarely engaged it in substantive mathematical dialogue: 96 percent of students tried Khanmigo at least once, but the median student messaged it on only a third of the days they practiced, and in only 17 percent of the exercise sessions in which they made a mistake. Messages that students did send were mostly bare answers or clicks on suggested prompts. The binding constraint appears to be engagement: realizing the promise of AI tutoring will require getting students to use it, not just giving them access.
AI Tutoring with Khanmigo in a Two-Year School Experiment

Key takeaways
A two-year study in 18 Tennessee middle schools found that using AI tutor Khanmigo with Khan Academy raised math achievement by 0.14 standard deviations over a year.
- Students used Khanmigo infrequently, messaging it on only a third of practice days.
- Most messages sent to Khanmigo were bare answers or clicks on suggested prompts.
- 96% of students tried Khanmigo at least once.
- The study suggests that engagement is the main constraint to realizing AI tutoring's potential.
Summarised automatically by AI from the original article by Hacker News. AI can make mistakes, so check the original for details.
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