Empowering tutoring expertise with AI

By Cynthia Lake, Johns Hopkins University

Effective tutoring can significantly improve student learning outcomes, but many students, particularly in under-served communities, often lack access to high-quality, expert-guided instruction due to resource limitations and the scarcity of trained educators. Stanford University researchers conducted the first randomized controlled trial of Tutor CoPilot, a Human-AI system designed to provide real-time, expert-like guidance to K-12 tutors, to explore its impact on enhancing tutor effectiveness during live sessions. In collaboration with FEV Tutor and a U.S. Southern school district, the researchers conducted an intervention involving 900 tutors and 1,800 students from Title I schools participating in an in-school, virtual tutoring program focused on mathematics.

The study showed that students whose tutors used Tutor CoPilot were 4 percentage points more likely to master mathematical lesson topics compared to those in the control group. This effect was especially pronounced among students taught by lower-rated tutors, whose mastery improved by 9 percentage points. The system also promoted the use of expert teaching strategies, such as prompting students to explain their reasoning and asking guiding questions, rather than giving away answers, fostering deeper student understanding.

Despite some challenges, such as occasional misalignment of AI suggestions with student grade levels, tutors reported that Tutor CoPilot helped them better address student needs. With an annual cost of just $20 per tutor, Tutor CoPilot offers a scalable and affordable path to improving tutoring quality in contexts where expert educators are in short supply. This study illustrates the potential of Human-AI systems like Tutor CoPilot to make high-quality learning accessible to all students.