Study shows AI is as good as human tutoring for GRE learning gains

A study submitted to arXiv on 23 Sep 2026 by Curtis Northcutt introduces StudentBench, a suite of AI teaching evaluations built on over 175,000 student-AI messages, and reports that AI tutoring is statistically equivalent to expert human tutoring for GRE learning gains (p = .015) across 2,383 human participants. In five of seven GRE domains the best-performing AI tutor surpassed the human tutor on average, and one AI tutor matched human tutoring gains (p = .044) at 918 times lower cost — USD 0.0052 for AI versus USD 4.81 for human per percentage point gained. A second study of 2,028 pairwise rubric evaluations by expert human tutors separated AI tutors on lesson planning, practice-problem creation, conversational pedagogy, cost and engagement, and the StudentBench platform is freely available at studentbench.org.

Computer Science Artificial Intelligence Submitted on 23 Sep 2026 Title:StudentBench: AI and human tutoring yield equivalent GRE learning gains View PDF https://arxiv.org/pdf/2609.28470 HTML experimental https://arxiv.org/html/2609.28470v1 Abstract:Artificial intelligence offers an unprecedented opportunity to augment human capabilities, yet progress at the frontier has focused primarily on advancing model capabilities. We introduce StudentBench, a suite of AI teaching evaluations and a public platform that enables large-scale data collection with over 175,000 student-AI messages to study whether large language models LLMs produce learning gains equivalent to human tutoring. Using StudentBench, we measured learning gains on Quantitative and Verbal GRE questions across 2,383 human participants receiving AI tutoring, human tutoring, or no tutoring. We establish that AI tutoring is statistically equivalent to expert human tutoring for GRE learning gains p = .015 , and in five of the seven GRE domains, the best performing AI tutor surpassed the human tutor, on average. In a second study, expert human tutors compared LLM-generated lesson plans and practice problems through 2,028 pairwise rubric evaluations. Together, the two studies clearly separate AI tutors across: 1 lesson planning, 2 practice-problem creation, 3 conversational pedagogy, 4 cost, and 5 engagement. Surprisingly, one AI tutor achieved learning gains equivalent to human tutoring p = .044 at 918 times lower cost USD 0.0052 for AI versus USD 4.81 for human, per percentage point gained . For Quantitative GRE sessions, faster AI replies correlated with more student messages, more messages with more correct practice, and more correct practice with larger learning gains all p < .002 . The StudentBench platform is freely available at this https URL https://studentbench.org . Submission history From: Curtis Northcutt view email https://arxiv.org/show-email/659c2238/2609.28470 v1 Wed, 23 Sep 2026 17:57:45 UTC 5,657 KB References & Citations Loading... Bibliographic and Citation Tools Bibliographic Explorer What is the Explorer? https://info.arxiv.org/labs/showcase.html arxiv-bibliographic-explorer Connected Papers What is Connected Papers? https://www.connectedpapers.com/about Litmaps What is Litmaps? https://www.litmaps.co/ scite Smart Citations What are Smart Citations? https://www.scite.ai/ Code, Data and Media Associated with this Article alphaXiv What is alphaXiv? https://alphaxiv.org/ CatalyzeX Code Finder for Papers What is CatalyzeX? https://www.catalyzex.com DagsHub What is DagsHub? https://dagshub.com/ Gotit.pub What is GotitPub? http://gotit.pub/faq Hugging Face What is Huggingface? https://huggingface.co/huggingface ScienceCast What is ScienceCast? https://sciencecast.org/welcome Demos Recommenders and Search Tools Influence Flower What are Influence Flowers? https://influencemap.cmlab.dev/ CORE Recommender What is CORE? https://core.ac.uk/services/recommender arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs https://info.arxiv.org/labs/index.html .