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Outcomes – Numeracy
Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 1 - 30 of 245
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…
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…
What Remains Human In Mathematics In The Age Of AI
Amir Moradifam. (07/2026). arXiv. https://arxiv.org/abs/2607.28791v1
Llama Lima: A Living Meta-Analysis On The Effects Of Generative AI On Learning Mathematics
Anselm Strohmaier, Samira Bodefeld, Frank Reinhold. (07/2026). arXiv. https://arxiv.org/abs/2601.18685v4
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
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
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
Beyond Helpfulness: A Teaching-Over-Solving Diagnostic For Measuring Educational Impact In LLM Tutors
Junyi Yao, Zihao Zheng, Baichuan Li. (06/2026). arXiv. https://arxiv.org/abs/2606.16206v1
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
Teaching with Gemini: Measuring the impact of Guided Learning on student mathematics progress in Sierra Leone
LearnLM Team, Google & Fab AI. (05/2026). Google. https://storage.googleapis.com/deepmind-media/LearnLM/learnLM_sierraleone_may26…
Promptdecipher: Supporting AI Tutor Authoring Through Editable Simulated Interactions
Miina Koyama, Ruiwei Xiao, John Stamper. (05/2026). arXiv. https://arxiv.org/abs/2605.16605v1
Little Impact Of ChatGPT Availability On High School Student Test Score Performance
Nick Huntington-Klein. (05/2026). arXiv. https://arxiv.org/abs/2605.08812v2
When Should Teachers Control AI Generation For Mathematics Visuals?
Zhengxu Li, Junling Wang, April Yi Wang. (05/2026). arXiv. https://arxiv.org/abs/2605.10672v1
Math Education Digital Shadows For Facilitating Learning With LLMs: Math Performance, Anxiety And Confidence In Simulated Students And Ais
Naomi Esposito, Anthony Tricarico, Luisa Porzio, Ali Aghazadeh Ardebili, and Massimo Stella. (04/2026). arXiv. https://arxiv.org/abs/2604.27618v1
From Test-Taking To Cognitive Scaffolding: A Pedagogical Diagnostic Benchmark For LLMs On English Standardized Tests
Luoxi Tang, Tharunya Sundar, Yuqiao Meng, Shuai Yang, Ankita Patra, Lakshmi Manohar Chippada, Jiqian Zhao, Yi Li, Weicheng Ma, Zhaohan Xi. (04/2026). arXiv. https://arxiv.org/abs/2505.17056v2
Human-In-The-Loop Benchmarking Of Heterogeneous LLMs For Automated Competency Assessment In Secondary Level Mathematics
Jatin Bhusal, Nancy Mahatha, Aayush Acharya, Raunak Regmi. (04/2026). arXiv. https://arxiv.org/abs/2604.26607v1
Knowledge without Wisdom: Measuring Misalignment between LLMs and Intended Impact
Michael Hardy, Yunsung Kim. (04/2026). arXiv. https://arxiv.org/abs/2603.00883
Beyond The AI Tutor: Social Learning With LLM Agents
Harsh Kumar, Jonathan Vincentius, Zi Kang (Jace) Mu, Ashton Anderson. (04/2026). arXiv. https://arxiv.org/abs/2604.02677v1
How Motivation Relates To Generative AI Use: A Large-Scale Survey Of Mexican High School Students
Echo Zexuan Pan, Danny Glick, Ying Xu. (04/2026). arXiv. https://arxiv.org/abs/2603.19263v2
Evaluating Vision-Language And Large Language Models For Automated Student Assessment In Indonesian Classrooms
Nurul Aisyah, Muhammad Dehan Al Kautsar, Arif Hidayat, Raqib Chowdhury, and Fajri Koto. (04/2026). arXiv. https://arxiv.org/abs/2506.04822v3
Practitioner Voices Summit: How Teachers Evaluate AI Tools Through Deliberative Sensemaking
Dorottya Demszky, Christopher Mah, Helen Higgins. (03/2026). arXiv. https://arxiv.org/abs/2603.22588v3
Evaluating A Data-Driven Redesign Process For Intelligent Tutoring Systems
Qianru Lyu, Conrad Borchers, Meng Xia, Karen Xiao, Paulo F. Carvalho, Kenneth R. Koedinger, and Vincent Aleven. (03/2026). arXiv. https://arxiv.org/abs/2603.29094v1
Exploring Student Perception On Gen AI Adoption In Higher Education: A Descriptive Study
Harpreet Singh, Jaspreet Singh, Satwant Singh, Rupinder Singh, Shamim Ibne Shahid, Mohammad Hassan Tayarani Najaran. (03/2026). arXiv. https://arxiv.org/abs/2603.27777v1
