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Outcomes – Numeracy
Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 1 - 30 of 259
Not Faster, But Better: Generative AI And Teacher Skill In Peru
Carla Z. Glave, Carolina Lopez, Ezequiel Molina, Roman Andres Zarate. (10/2026). World Bank. http://documents.worldbank.org/curated/en/099309210012625906
Teacher-Mediated Multimodal Platform And Math Achievement: Evidence From Goblins' Yearlong District Implementation
Anika Alam, Nicolas Dominguez-Mel, Jing Liu. (10/2026). EdWorking Papers. https://edworkingpapers.com/ai26-1611
Characterizing LLM-Based Family Education Through The Lens Of Activity Theory: A Scoping Review Of The Hci Literature
Lan Luo, Yuqi Liang, Jie Cai, Anqi Wang, Dongyijie Primo Pan, Muzhi Zhou, Chun Yu, Pan Hui. (09/2026). arXiv. https://arxiv.org/abs/2609.28886v1
Studentbench: AI And Human Tutoring Yield Equivalent Gre Learning Gains
Curtis Northcutt, Inaara Hasmani, Kevin Feng, Trevor Khangi, Andreas Plesner, Jonas Mueller. (09/2026). arXiv. https://arxiv.org/abs/2609.28470?utm_source=chatgpt.com
When AI Tutors Speak: Evidence From A Randomized Field Experiment
Shihao Yang, Marshall Van Alstyne, Chrysanthos Dellarocas. (09/2026). arXiv. https://arxiv.org/abs/2609.23958v1
From Content Generation To Learning Support: Pedagogy-Guided Generative Video Tutors For STEM Learning
Xinchen Ma, Shuimu Wang, Gaole He, Yanbin Zhang, Chunyang Wang, Yunshi Lan, Weining Qian. (09/2026). arXiv. https://arxiv.org/abs/2609.24083v1
Little Impact Of ChatGPT On High School Test Scores
Nick Huntington-Klein. (09/2026). arXiv. https://arxiv.org/abs/2605.08812v3
A Brief AI Literacy Intervention Does Not Significantly Reduce Over-Reliance And Increases Under-Reliance On ChatGPT: A Randomized Study
Brett Puppart, Jaan Aru. (09/2026). arXiv. https://arxiv.org/abs/2503.10556
Mathematics Graduate Training In The Age Of AI
David Glickenstein. (09/2026). arXiv. https://arxiv.org/abs/2609.21132v1
Llama Lima: A Living Meta-Analysis On The Effects Of Generative AI On Learning Mathematics
Anselm Strohmaier, Samira Bodefeld, Oliver Straser, Frank Reinhold. (09/2026). arXiv. https://arxiv.org/abs/2601.18685v5
Statistical Theory In The Age Of Machine-Assisted Mathematics: Rethinking How Theory Is Made And Taught
Pietro Coretto. (09/2026). arXiv. https://arxiv.org/abs/2609.04481v1
Beyond Helpfulness: A Teaching-Over-Solving Diagnostic For Measuring Educational Impact In LLM Tutors
Junyi Yao, Zihao Zheng, Baichuan Li. (08/2026). arXiv. https://arxiv.org/abs/2606.16206v2
Gen AI In Proof-Based Math Courses: A Pilot Study
Hannah Klawa, Shraddha Rajpal, Cigole Thomas. (08/2026). arXiv. https://arxiv.org/abs/2509.13570v2
Methodologies For Improving The Quality Of AI Tutoring In K-12 Education
Tushar Udeshi, Anna Khazenzon, Kabir Khan, Nick Breen, RJ Corwin, Chris DiGiano, Kodi Weatherholtz, Marek Zaluski. (08/2026). arXiv. https://arxiv.org/abs/2608.11259v1
Eduzone: A Framework For Evaluating LLM Safety For K-12 Students And Teachers
Junyeong Park, Jieun Han, Haneul Yoo, So-Yeon Ahn, Jinsung Yoon, Alice Oh. (08/2026). arXiv. https://arxiv.org/abs/2608.02024v1
One Click Away: AI Tutoring with Khanmigo in a Two-Year School Experiment
Philip Oreopoulos, Nina Low. (08/2026). NBER. https://www.nber.org/papers/w35620
Virtual Tutoring with Computer-Assisted Learning: An Experiment in Take-Up and Learning
Philip Oreopoulos, Ruochong Dong, Nina Low. (08/2026). NBER. https://www.nber.org/papers/w35622?utm_campaign=ntwh&utm_medium=email&utm_sourc…
Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment
Philip Oreopoulos, Michael Liut, Alp Sungu, Nina Low. (08/2026). NBER. https://www.nber.org/papers/w35621?utm_campaign=ntwh&utm_medium=email&utm_sourc…
What Remains Human In Mathematics In The Age Of AI
Amir Moradifam. (07/2026). arXiv. https://arxiv.org/abs/2607.28791v1
Generative AI Can Harm Teaching
Alp Sungu, Benjamin Lira, Angela L. Duckworth. (07/2026). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7007339
Faster Completion, Less Learning: Generative AI Reduced Study Time On Math Problems And The Knowledge They Build
Sina Rismanchian, Hasan Uzun, Jeffrey Matayoshi, Eric Cosyn, Eyad Kurd-Misto. (07/2026). arXiv. https://arxiv.org/abs/2605.21629v3
From Answer Generators To Reasoning Facilitators: Designing AI Tutors For Mathematical Reasoning In High-Stakes Environments
Harry Feng, Yuan Tian, Erica Zhao. (07/2026). arXiv. https://arxiv.org/abs/2607.01692v1
The Generative AI Learning Penalty: Evidence from Chinese Secondary Education
David Stromberg, Victor Lei, Yanhui Wu. (07/2026). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6868618
LLM-Generated Summaries For Teachers: A Randomized Field Experiment In A Digital Learning Platform
Wen-Chiang Ivan Lim, Eamon Worden, Adam Sales, Neil T. Heffernan III. (06/2026). Proceedings of the 13th ACM Conference on Learning @ Scale (L@S ’26). https://dl.acm.org/doi/10.1145/3774398.3811606
Context-Aware Prediction Of Student Quiz Performance With Multimodal Textbook Features
Samin Khan. (05/2026). arXiv. https://arxiv.org/abs/2606.24770v1
Facet: Multi-Agent AI Supporting Teachers In Scaling Differentiated Learning For Diverse Students
Jana Gonnermann-Muller, Jennifer Haase, Nicolas Leins, Moritz Igel, Konstantin Fackeldey and Sebastian Pokutta. (05/2026). arXiv. https://arxiv.org/abs/2601.22788v4
"Would You Want an AI Tutor?" Understanding Stakeholder Perceptions of LLM-based Systems in the Classroom
Caterina Fuligni, Daniel Dominguez Figaredo, Armanda Lewis, Julia Stoyanovich. (05/2026). arXiv. https://arxiv.org/abs/2503.02885v3
Addressing The Reality Gap: A Three-Tension Framework For Agentic AI Adoption
Jason Fournier, Kacper Łodzikowski. (05/2026). arXiv. https://arxiv.org/abs/2604.27245v2
A Scoping Review Of Large Language Model-Based Pedagogical Agents
Shan Li, Juan Zheng. (05/2026). arXiv. https://arxiv.org/abs/2604.12253v2
