AI Overview
Generative AI can expand access to expert guidance in domains like education, where expert support is often limited.
- Question: Does providing real-time AI guidance to tutors improve student math mastery and tutor practices?
- Setting and data: More than 700 tutors and 1,000 students from underserved communities; analysis of over 350,000 messages.
- Method: Randomized controlled trial and message analysis
- AI tools: Tutor CoPilot
- Students whose tutors used Tutor CoPilot were 4 percentage points more likely to master math topics.
- Math mastery gains were highest for students working with lower-rated tutors, showing a 9 percentage point increase.
- Tutor CoPilot promoted effective pedagogy by increasing probing questions and reducing generic praise at an estimated cost of about $20 per tutor per year.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
Generative AI, particularly Large Language Models (LLMs), can expand access to expert guidance in domains like education, where such support is often limited. We introduce Tutor CoPilot, a Human-AI system that models expert thinking to assist tutors in real time. In a randomized controlled trial involving more than 700 tutors and 1,000 students from underserved communities, students with tutors using Tutor CoPilot were 4 percentage points more likely to master math topics (p<0.01). Gains were highest for students of lower-rated tutors (+9 p.p.), and the tool is low-cost (about $20/tutor/year). Analysis of over 350,000 messages shows Tutor CoPilot promotes effective pedagogy, increasing the use of probing questions and reducing generic praise. In this work we show the potential for human-AI systems to scale expertise in a real-world domain, bridge gaps in skills, and create a future where high-quality education is accessible to all students.
