Research Study Repository
A comprehensive collection of academic research on generative AI in preK12 education organized into three categories:
- Descriptive - Research that describes how generative AI is being used in classrooms, schools, or districts or how products are designed and built.
- Impact (includes RCT + Quasi-Experimental) - Studies that test how well something works including but not limited to randomly dividing people into groups and comparing the results.
- Review - Studies that combine and summarize all the research on a specific genAI topic to find patterns and answers.
We aim to include all research in the above categories on generative AI in preK12 education in the US. As research diverges from genAI for preK12 in the US - such as machine learning, education systems beyond preK12, or studies conducted outside the US - inclusion in the repository is based on relevance to our target audiences:
- Superintendents, state, and federal K12 leaders
- Education support organizations (unions, parent groups, etc.)
- Leadership and product teams at technology companies
- Academic researchers
- Global education leaders
The Research Repository includes pre-published works but does not include journalism on AI for education.
Research synthesis is AI-generated, human reviewed. Updated 05/2025.
Showing 241 - 270 of 580 results
Harnessing AI in Secondary Education to Enhance Writing Competence
Eyvind Elstad, Harald Eriksen. (12/2024). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student, Educator
Which age? High School (9-12)
Why use AI? Outcomes – Literacy, Outcomes – Differentiation
Study design: Descriptive – Implementation and UseA Benchmark for Math Misconceptions: Bridging Gaps in Middle School Algebra with AI-Supported Instruction
Nancy Otero, Stefania Druga and Andrew Lan. (12/2024). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Middle School (6-8)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product DevelopmentCognitive ease at a cost: LLMs reduce mental effort but compromise depth in student scientific inquiry
Matthias Stadler, Maria Bannert, Michael Sailer. (11/2024). Computers in Human Behavior.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic
Study design: Impact – Quasi–experimentalApplying IRT to Distinguish Between Human and Generative AI Responses to Multiple-Choice Assessments
Alona Strugatski, Giora Alexandron. (11/2024). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Teaching – Professional Learning, Learning – Student Support
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 – Other Academic, Outcomes – Differentiation
Study design: Systematic ReviewExploring the Effectiveness of AI Course Assistants on the Student Learning Experience
George Hanshaw, Joanna Vance, Craig Brewer. (11/2024). Open Praxis.
What is the application? Learning – Student Support
Who is the user? Student, Educator
Which age? Post-Secondary
Why use AI? Outcomes – Literacy, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Impact – Randomized Controlled TrialGLAT: The Generative AI Literacy Assessment Test
Yueqiao Jin, Roberto Martinez-Maldonado, Dragan Gašević, Lixiang Yan. (11/2024). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Student, Educator
Which age? Post-Secondary
Why use AI? Outcomes – Durable Skills
Study design: Impact – Quasi–experimentalUnderstanding Students' Acceptance, Trust, and Attitudes towards AI-generated Images for Educational Purposes
Aung Pyae. (11/2024). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student, Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic
Study design: Impact – Quasi–experimentalSBI-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? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Product DevelopmentGenerative AI and Agency in Education: A Critical Scoping Review and Thematic Analysis
Jasper Roe, Mike Perkins. (11/2024). arXiv.
What is the application? Teaching – Instructional Materials, 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), Post-Secondary
Why use AI? Outcomes – Literacy, Outcomes – Differentiation, Reimagined Schooling
Study design: Systematic ReviewLeveling Up or Leveling Down? The Impact of Large Language Models on Student Performance in Higher Education
Oana Vuculescu, Franziska Günzel-Jensen, Lars Frederiksen, Carsten Bergenholtz. (11/2024). SSRN.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Differentiation
Study design: Impact – Randomized Controlled TrialAutomatic 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? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student, Educator
Which age? High School (9-12)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product DevelopmentWhere Assessment Validation and Responsible AI Meet
Jill Burstein, Geoffrey T. LaFlair. (11/2024). arXiv.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary, Adult
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Other Academic, Outcomes – Differentiation, Reimagined Schooling
Study design: Descriptive – Implementation and Use, Descriptive – Product Development, Systematic ReviewGenerative AI Usage and Exam Performance
Janik Ole Wecks, Johannes Voshaar, Benedikt J. Plate, Jochen Zimmermann. (11/2024). arXiv.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic
Study design: Impact – Quasi–experimentalGenerative AI as a Tool or Leader? Exploring AI-Augmented Thinking in Student Programming Tasks
Tianlong Zhong, Gaoxia Zhu, Kang You Lim, Yew Soon Ong. (11/2024). arXiv.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Durable Skills
Study design: Impact – Quasi–experimentalThe Influence of Artificial Intelligence Tools on Student Performance in e-Learning Environments: Case Study
Mohd Elmagzoub Eltahir, Frdose Mohd Elmagzoub Babiker. (11/2024). Electronic Journal of e-Learning.
What is the application? Learning – Student Support, Teaching – Instructional Materials, Teaching – Assessment and Feedback
Who is the user? Student, Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Impact – Quasi–experimentalImproving Bilingual Capabilities of Language Models to Support Diverse Linguistic Practices in Education
Anand Syamkumar, Nora Tseng, Kaycie Barron, Shanglin Yang, Shamya Karumbaiah, Rheeya Uppal, Junjie Hu. (11/2024). arXiv.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Outcomes – Literacy, Outcomes – Differentiation
Study design: Impact – Quasi–experimentalMetabook: A System to Automatically Generate Interactive AR Storybooks to Improve Children's Reading
Yibo Wang, Yuanyuan Mao, Shi-ting Ni, Wang Zeyu, Hui Pan. (11/2024). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support, Communicating / Social Tools
Who is the user? Educator
Which age? Elementary (PK5)
Why use AI? Outcomes – Literacy, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Descriptive – Product Development, Impact – Quasi–experimentalVISTA: 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
Who is the user? Educator
Which age? High School (9-12)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product DevelopmentLLM-Powered AI Tutors with Personas for d/Deaf and Hard-of-Hearing Online Learners
Haocong Cheng, Si Chen, Christopher Perdriau, Yun Huang. (11/2024). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Differentiation
Study design: Descriptive – Implementation and UseHowzat? Appealing to Expert Judgement for Evaluating Human and AI Next-Step Hints for Novice Programmers
Neil C. C. Brown, Pierre Weill-Tessier, Juho Leinonen, Paul Denny, Michael Kolling. (11/2024). arXiv.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Educator
Which age? High School (9-12), Post-Secondary
Why use AI? Outcomes – Literacy, Outcomes – Differentiation
Study design: Descriptive – Product Development, Impact – Quasi–experimentalAdvancing Transformative Education: Generative AI as a Catalyst for Equity and Innovation
Chiranjeevi Bura, Praveen Kumar Myakala. (11/2024). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Teaching – Professional Learning, Learning – Student Support, Organizing, Analyzing
Who is the user? Educator, School Leader
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 – Social Emotional, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Implementation and UseThe Extent of AI Applications in EFL Learning and Teaching
Yousif A. Alshumaimeri, Abdulrahman K. Alshememry. (10/2024). IEEE.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student, Educator
Which age? High School (9-12), Post-Secondary
Why use AI? Outcomes – Literacy, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Systematic ReviewArtificial Human Lecturers: Initial Findings From Asia's First AI Lecturers in Class to Promote Innovation in Education
Ching Christie Pang, Yawei Zhao, Zhizhuo Yin, Jia Sun, Reza Hadi Mogavi, Pan Hui. (10/2024). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Professional Learning
Who is the user? Student, Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Descriptive – Implementation and Use, Impact – Quasi–experimentalMalAlgoQA: Pedagogical Evaluation of Counterfactual Reasoning in Large Language Models and Implications for AI in Education
Naiming Liu, Shashank Sonkar, Myco Le, Richard Baraniuk. (10/2024). 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)
Why use AI? Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product DevelopmentA Systematic Assessment of OpenAI o1-Preview for Higher Order Thinking in Education
Ehsan Latif, Yifan Zhou, Shuchen Guo, Yizhu Gao, Lehong Shi, Matthew Nayaaba, Gyeonggeon Lee, Liang Zhang, Arne Bewersdorff, Luyang Fang, Xiantong Yang, Huaqin Zhao, Hanqi Jiang, Haoran Lu, Jiaxi Li, Jichao Yu, Weihang You, Zhengliang Liu, (eta.). (10/2024). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Durable Skills
Study design: Systematic ReviewInto the Unknown Unknowns: Engaged Human Learning through Participation in Language Model Agent Conversations
Yucheng Jiang, Yijia Shao, Dekun Ma, Sina J. Semnani, Monica S. Lam. (10/2024). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary, Adult
Why use AI? Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Product Development, Impact – Randomized Controlled Trial, Impact – Quasi–experimentalAn Eye for an AI: Evaluating GPT-40's Visual Perception Skills and Geometric Reasoning Skills Using Computer Graphics Questions
Tony Haoran Feng, Paul Denny, Burkhard C. Wünsche, Andrew Luxton-Reilly, Jacqueline Whalley. (10/2024). arXiv.
What is the application? Teaching – Assessment and Feedback, Teaching – Professional Learning
Who is the user? Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic
Study design: Impact – Quasi–experimentalTutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise
Rose E. Wang, Ana T. Ribeiro, Carly D. Robinson, Susanna Loeb, Dorottya Demszky. (10/2024). EdWorkingPapers.com.
What is the application? Teaching – Professional Learning, Learning – Student Support
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8)
Why use AI? Efficiency, Outcomes – Other Academic
Study design: Impact – Randomized Controlled TrialLLM-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? Educator
Which age? Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product DevelopmentOpenDebateEvidence: A Massive-Scale Argument Mining and Summarization Dataset
Allen Roush, Yusuf Shabazz, Arvind Balaji, Peter Zhang, Stefano Mezza, Markus Zhang, Sanjay Basu, Sriram Vishwanath, Mehdi Fatemi, Ravid Shwartz Ziv. (10/2024). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support, Analyzing
Who is the user? Educator, Others
Which age? Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Other Academic, Outcomes – Durable Skills
Study design: Descriptive – Product Development
