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Research Study Repository
Research synthesis is AI-generated, human reviewed. Updated 08/2026.
Showing 181 - 210 of 245 results
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.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support, Analyzing
Who is the user? Student, Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Efficiency, Outcomes – Numeracy
Study design: Technical – ComputationalBuilding Bridges - AI Custom Chatbots as Mediators between Mathematics and Physics
Julia Lademann, Jannik Henze, Sebastian Becker-Genschow. (12/2024). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student
Which age? Middle School (6-8)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Impact – Randomized Controlled TrialAI-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.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Elementary (PK5)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Differentiation, Reimagined Schooling, Other
Study design: Descriptive – Implementation and Use, Descriptive – Product Development, Technical – Computational, Quantitative – OthersVISTA: Visual Integrated System for Tailored Automation in Math Problem Generation Using LLM
Jeongwoo Lee, Kwangsuk Park, Jihyeon Park. (11/2024). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback
Who is the user? Educator
Which age? High School (9-12)
Why use AI? Efficiency, Outcomes – Numeracy
Study design: Descriptive – Product Development, Technical – ComputationalSBI-RAG: Enhancing Math Word Problem Solving for Students through Schema-Based Instruction and Retrieval-Augmented Generation
Prakhar Dixit, Tim Oates. (11/2024). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Middle School (6-8)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – ComputationalAutomatic 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.
What is the application? Learning – Student Support
Who is the user?
Which age? High School (9-12)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical – ComputationalThe 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.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback
Who is the user? Student, Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary, Adult
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Implementation and Use, Descriptive – Product DevelopmentPromptHive: 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.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Numeracy
Study design: Descriptive – Product Development, Impact – Randomized Controlled TrialMathFish: 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.
What is the application? Teaching – Instructional Materials
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Efficiency, Outcomes – Numeracy
Study design: Technical – ComputationalLLM-based Cognitive Models of Students with Misconceptions
Shashank Sonkar, Xinghe Chen, Naiming Liu, Richard G. Baraniuk, Mrinmaya Sachan. (10/2024). arXiv.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user?
Which age? Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical – ComputationalAutomated 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.
What is the application? Teaching – Assessment and Feedback
Who is the user? Student, Educator
Which age? Middle School (6-8)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical – Computational, Quantitative – OthersMalAlgoQA: 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.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student, Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Technical – ComputationalLearning 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.
What is the application? Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Middle School (6-8), High School (9-12)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical – ComputationalA Comprehensive Review on Generative AI for Education
Uday Mittal, Siva Sai, Vinay Chamola, Devika Sangwan. (09/2024). IEEE.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Teaching – Professional Learning, Learning – Student Support, Communicating / Social Tools, Organizing, Analyzing
Who is the user? Student, Parent/Caregiver, Educator
Which age? 0-3 years, Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary, Adult
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills, Reimagined Schooling
Study design: Systematic ReviewStudents' 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.
What is the application? Learning – Student Support, Communicating / Social Tools
Who is the user? Student
Which age? Middle School (6-8)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Social Emotional, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Implementation and Use, Descriptive – Product DevelopmentImpact 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.
What is the application? Learning – Student Support
Who is the user? Student, Others
Which age? Post-Secondary, Adult
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Durable Skills
Study design: Impact – Randomized Controlled TrialBackwards Planning with Generative AI: Case Study Evidence from US K12 Teachers
Samantha Keppler, Wichinpong Park Sinchaisri, Clare Snyder. (08/2024). SSRN.
… use it, backward planning is a universal practice among US K12 teachers. The emergence of generative AI has stimulated many … Given backward planning is standard workflow process in K12 education, we ask: How are teachers using generative AI …What is the application? Teaching – Instructional Materials, Teaching – Professional Learning
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Other Academic
Study design: Quantitative – OthersThe 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.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Middle School (6-8)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Social Emotional
Study design: Impact – Quasi–experimentalStepwise 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.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical РComputational, Quantitative РOthersCOMET : "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.
What is the application? Teaching – Instructional Materials
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical – ComputationalGenerative AI Can Harm Learning
Hamsa Bastani, Osbert Bastani, Alp Sungu, Haosen Ge, Ozge Kabaci, Rei Mariman. (07/2024). SSRN.
What is the application? Learning – Student Support
Who is the user? Student
Which age? High School (9-12)
Why use AI? Outcomes – Numeracy, Outcomes – Durable Skills
Study design: Impact – Randomized Controlled TrialExposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning
Joykirat Singh, Akshay Nambi, Vibhav Vineet. (06/2024). arXiv.
What is the application? Learning – Student Support
Who is the user? Student, Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Outcomes – Numeracy
Study design: Technical – ComputationalSystematic review of research on artificial intelligence in K-12 education (2017-2022)
Florence Martin, Min Zhuang, Darlene Schaefer. (06/2024). ScienceDirect.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support, Analyzing
Who is the user? Student, Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Social Emotional, Outcomes – Durable Skills, Reimagined Schooling
Study design: Systematic ReviewGenerative 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.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support
Who is the user?
Which age? High School (9-12)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical – ComputationalEncouraging 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.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Outcomes – Numeracy, Outcomes – Durable Skills, Other
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersBringing 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.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support, Analyzing
Who is the user? Student, Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Implementation and Use, Descriptive – Product Development, Systematic ReviewMath Multiple Choice Question Generation via Human-Large Language Model Collaboration
Jaewook Lee, Digory Smith, Simon Woodhead, Andrew Lan. (05/2024). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Middle School (6-8), High School (9-12)
Why use AI? Efficiency, Outcomes – Numeracy
Study design: Descriptive – Product Development, Quantitative – OthersLLMs can Find Mathematical Reasoning Mistakes by Pedagogical Chain-of-Thought
Zhuoxuan Jiang, Haoyuan Peng, Shanshan Feng, Fan Li, Dongsheng Li. (05/2024). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user?
Which age? High School (9-12)
Why use AI? Outcomes – Numeracy
Study design: Technical – ComputationalLarge Language Models for Education: A Survey
Hanyi Xu, Wensheng Gan, Zhenlian Qi, Jiayang Wu and Philip S. Yu. (05/2024). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Teaching – Professional Learning, Learning – Student Support, Communicating / Social Tools, Organizing, Analyzing
Who is the user? Student, Parent/Caregiver, Educator
Which age? 0-3 years, Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary, Adult
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Implementation and Use, Technical – Computational, Systematic ReviewJiuZhang3.0: 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.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user?
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Efficiency, Outcomes – Numeracy
Study design: Technical – Computational
