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Outcomes – Numeracy
Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 181 - 210 of 245
AI-Driven Virtual Teacher for Enhanced Educational Efficiency: Leveraging Large Pretrained Models for Autonomous Error Analysis and Correction
Tianlong Xu, Yi-Fan Zhang, Zhendong Chu, Shen Wang, Qingsong Wen. (12/2024). arXiv. https://arxiv.org/pdf/2409.09403
MNIST-Fraction: Enhancing Math Education with AI-Driven Fraction Detection and Analysis
Pegah Ahadian, Yunhe Feng, Karl Kosko, Richard Ferdig, Qiang Guan. (12/2024). arXiv. https://arxiv.org/pdf/2412.08633
Scaffold or Crutch? Examining College Students' Use and Views of Generative AI Tools for STEM Education
Karen D. Wang, Zhangyang Wu, L'Nard Tufts II, Carl Wieman, Shima Salehi, Nick Haber. (12/2024). arXiv. https://arxiv.org/pdf/2412.02653
VISTA: Visual Integrated System for Tailored Automation in Math Problem Generation Using LLM
Jeongwoo Lee, Kwangsuk Park, Jihyeon Park. (11/2024). arXiv. http://arxiv.org/pdf/2411.05423v1
Automatic Generation of Question Hints for Mathematics Problems using Large Language Models in Educational Technology
Junior Cedric Tonga, Benjamin Clement, Pierre-Yves Oudeyer. (11/2024). arXiv. http://arxiv.org/pdf/2411.03495v1
SBI-RAG: Enhancing Math Word Problem Solving for Students through Schema-Based Instruction and Retrieval-Augmented Generation
Prakhar Dixit, Tim Oates. (11/2024). arXiv. http://arxiv.org/pdf/2410.13293v2
MathFish: Evaluating Language Model Math Reasoning via Grounding in Educational Curricula
Li Lucy, Tal August, Rose E. Wang, Luca Soldaini, Courtney Allison, Kyle Lo. (10/2024). arXiv. https://arxiv.org/pdf/2408.04226
PromptHive: Bringing Subject Matter Experts Back to the Forefront with Collaborative Prompt Engineering for Educational Content Creation
Mohi Reza, Ioannis Anastasopoulos, Shreya Bhandari, Zachary A. Pardos. (10/2024). arXiv. http://arxiv.org/pdf/2410.16547v1
Automated Feedback in Math Education: A Comparative Analysis of LLMs for Open-Ended Responses
Sami Baral, Eamon Worden, Wen-Chiang Lim, Zhuang Luo, Christopher Santorelli, Ashish Gurung, Neil Heffernan. (10/2024). arXiv. http://arxiv.org/pdf/2411.08910v1
MalAlgoQA: Pedagogical Evaluation of Counterfactual Reasoning in Large Language Models and Implications for AI in Education
Naiming Liu, MyCo Le, Shashank Sonkar, Richard G. Baraniuk. (10/2024). arXiv. https://arxiv.org/pdf/2407.00938
LLM-based Cognitive Models of Students with Misconceptions
Shashank Sonkar, Xinghe Chen, Naiming Liu, Richard G. Baraniuk, Mrinmaya Sachan. (10/2024). arXiv. http://arxiv.org/pdf/2410.12294v2
The Future of Learning in the Age of Generative AI: Automated Question Generation and Assessment with Large Language Models
Subhankar Maity, Aniket Deroy. (10/2024). arXiv. http://arxiv.org/pdf/2410.09576v1
Learning to Love Edge Cases in Formative Math Assessment: Using the AMMORE Dataset and Chain-of-Thought Prompting to Improve Grading Accuracy
Owen Henkel, Hannah Horne-Robinson, Maria Dyshel, Nabil Ch, Baptiste Moreau-Pernet, Ralph Abood. (09/2024). arXiv. http://arxiv.org/pdf/2409.17904v1
A Comprehensive Review on Generative AI for Education
Uday Mittal, Siva Sai, Vinay Chamola, Devika Sangwan. (09/2024). IEEE. https://ieeexplore.ieee.org/document/10695056
Impact of Guidance and Interaction Strategies for LLM Use on Learner Performance and Perception
Harsh Kumar, Ilya Musabirov, Mohi Reza, Jiakai Shi, Xinyuan Wang, Joseph Jay Williams, Anastasia Kuzminykh, Michael Liut. (08/2024). arXiv. http://arxiv.org/pdf/2310.13712v3
Backwards Planning with Generative AI: Case Study Evidence from US K12 Teachers
Samantha Keppler, Wichinpong Park Sinchaisri, Clare Snyder. (08/2024). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4924786
Students' Perceived Roles, Opportunities, and Challenges of a Generative AI-powered Teachable Agent: A Case of Middle School Math Class
Yukyeong Song, Jinhee Kim, Zifeng Liu, Chenglu Li, Wanli Xing. (08/2024). arXiv. http://arxiv.org/pdf/2409.06721v1
The Neglected 15%: Positive Effects Of Hybrid Human-Ai Tutoring Among Students With Disabilities
Danielle R. Thomas, Erin Gatz, Shivang Gupta, Vincent Aleven, Kenneth R. Koedinger. (07/2024). Artificial Intelligence in Education: 25th International Conference, AIED 2024. https://dl.acm.org/doi/abs/10.1007/978-3-031-64302-6_29
COMET : "Cone of experience” enhanced large multimodal model for mathematical problem generation
Sannyuya Liu, Jintian Feng, Zongkai Yang, Yawei Luo, Qian Wan, Xiaoxuan Shen, Jianwen Sun. (07/2024). arXiv. http://arxiv.org/pdf/2407.11315v1
Generative AI Can Harm Learning
Hamsa Bastani, Osbert Bastani, Alp Sungu, Haosen Ge, Ozge Kabaci, Rei Mariman. (07/2024). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4895486
Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model Tutors
Nico Daheim, Jakub Macina, Manu Kapur, Iryna Gurevych, Mrinmaya Sachan. (07/2024). arXiv. http://arxiv.org/pdf/2407.09136v1
Systematic review of research on artificial intelligence in K-12 education (2017-2022)
Florence Martin, Min Zhuang, Darlene Schaefer. (06/2024). ScienceDirect. https://www.sciencedirect.com/science/article/pii/S2666920X23000747
Bringing Generative AI to Adaptive Learning in Education
Hang Li, Tianlong Xu, Chaoli Zhang, Eason Chen, Jing Liang, Xing Fan, Haoyang Li, Jiliang Tang, Qingsong Wen. (06/2024). arXiv. https://arxiv.org/pdf/2402.14601
Generative AI for Enhancing Active Learning in Education: A Comparative Study of GPT-3.5 and GPT-4 in Crafting Customized Test Questions
Hamidreza Rouzegar, Masoud Makrehchit. (06/2024). arXiv. https://arxiv.org/pdf/2406.13903
Encouraging Responsible Use of Generative AI in Education: A Reward-Based Learning Approach
Aditi Singh, Abul Ehtesham, Saket Kumar, Gaurav Gupta, Tala Talaei Khoei. (06/2024). arXiv. https://arxiv.org/pdf/2407.15022
Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning
Joykirat Singh, Akshay Nambi, Vibhav Vineet. (06/2024). arXiv. http://arxiv.org/pdf/2406.10834v1
Large Language Models for Education: A Survey
Hanyi Xu, Wensheng Gan, Zhenlian Qi, Jiayang Wu and Philip S. Yu. (05/2024). arXiv. http://arxiv.org/pdf/2405.13001v1
JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models
Kun Zhou, Beichen Zhang, Jiapeng Wang, Zhipeng Chen, Wayne Xin Zhao, Jing Sha, Zhichao Sheng, Shijin Wang, Ji-Rong Wen. (05/2024). arXiv. http://arxiv.org/pdf/2405.14365v1
ChatGPT-generated help produces learning gains equivalent to human tutor-authored help on mathematics skills
Zachary A. Pardos, Shreya Bhandari. (05/2024). PLOS ONE. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0304013
Effective and Scalable Math Support: Experimental Evidence on the Impact of an AI- Math Tutor in Ghana
Owen Henkel, Hannah Horne-Robinson, Nessie Kozhakhmetova, Amanda Lee. (05/2024). arXiv. https://arxiv.org/pdf/2402.09809
