Research Study Repository

Striving to be the comprehensive collection of academic research on generative AI in preK-12 education.

Research Categories

We organize studies into three distinct categories to help you find exactly what you need today:

Where is the field right now?

Research that describes how generative AI is being used in classrooms, schools, or districts, or how products are designed and built.

Descriptive – Implementation and Use

Descriptive – Product Development

When Does AI Support Thinking, And When Does It Replace It? Learners' Conceptualisations Of AI As A Dynamic Cognitive Partner: A Typology. Cecilia Ka Yuk Chan. (04/2026). arXiv.

What is proven to be effective?

Research that tests how well something works using Randomized Controlled Trials (RCT) and Quasi-Experimental designs (QED) that randomly divide people into groups and compare the results.

Impact – Randomized Controlled Trial

Impact – Quasi-experimental

Assessing The Impact And Underlying Pathways Of Sequenced AI Feedback On Student Learning. Jie Cao, Chloe Qianhui Zhao, Christian Schunn, Elizabeth A. McLaughlin, Jionghao Lin, Kenneth R. Koedinger. (04/2026). arXiv.

What are the overarching trends?

Research that combines and summarizes all the research on a specific genAI topic to find overarching patterns and answers.

Systematic Review

The Landscape Of AI In Science Education: What Is Changing And How To Respond. Xiaoming Zhai, Kent Crippen. (03/2026). arXiv.

Scope & Relevance

To maintain a high standard of academic rigor and practical utility, we filter all inclusions based on the following guardrails:

We Include

Generative AI in US preK-12 education
Vetted, peer-reviewed studies
Pre-published academic works

We Exclude

Broad machine learning / non-genAI topics
Higher education or international systems
Journalism and media opinion pieces

This Repository is For You

This platform is designed to enable collaboration and insight across two primary sectors:

K-12 Leadership & Policy

Superintendents, state, and federal K12 leaders
Education support organizations (unions, parent groups, etc.)
Global education leaders

Research & Development

Academic researchers
Education support organizations (unions, parent groups, etc.)
Leadership and product teams at technology companies

Research synthesis is AI-generated, human reviewed. Updated 05/2026.

Showing 751 - 780 of 1372 results

LEKIA: A Framework for Architectural Alignment via Expert Knowledge Injection

Boning Zhao, Yutong Hu. (07/2025). arXiv.

What is the application? Learning – Student Support
Who is the user? Others
Which age? Post-Secondary, Adult
Why use AI? Outcomes – Social Emotional, Other
Study design: Descriptive – Product Development, Technical – Computational
EduThink4AI: Translating Educational Critical Thinking into Multi-Agent LLM Systems

Xinmeng Hou, Zhouquan Lu, Wenli Chen, Hai Hu, Qing Guo. (07/2025). arXiv.

What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Literacy, Outcomes – Durable Skills, Other
Study design: Technical – Computational, Quantitative – Others
Explainable Collaborative Problem Solving Diagnosis with BERT using SHAP and its Implications for Teacher Adoption

Kester Wong, Sahan Bulathwela and Mutlu Cukurova. (07/2025). arXiv.

What is the application? Teaching – Assessment and Feedback
Who is the user? Educator
Which age?
Why use AI? Other
Study design: Technical – Computational
Using LLMs to identify features of personal and professional skills in an open-response situational judgment test

Cole Walsh, Rodica Ivan, Muhammad Zafar Iqbal, Colleen Robb. (07/2025). arXiv.

What is the application? Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Post-Secondary, Adult
Why use AI? Efficiency, Outcomes – Social Emotional, Outcomes – Durable Skills
Study design: Technical – Computational
Partnering with AI: A Pedagogical Feedback System for LLM Integration into Programming Education

Niklas Scholz, Manh Hung Nguyen, Adish Singla, Tomohiro Nagashima. (07/2025). arXiv.

What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Differentiation
Study design: Descriptive – Product Development, Quantitative – Others
Findings of MEGA: Maths Explanation with LLMs using the Socratic Method for Active Learning

Tosin Adewumi, Foteini Simistira Liwicki, Marcus Liwicki, Viktor Gardelli, Lama Alkhaled, Hamam Mokayed. (07/2025). arXiv.

What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Social Emotional, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Product Development, Impact – Quasi–experimental, Technical – Computational
Mitigating Trojanized Prompt Chains In Educational Llm Use Cases: Experimental Findings and Detection Tool Design

Richard M. Charles, Ph.D, James H. Curry, Ph.D, Richard B. Charles. (07/2025). arXiv.

What is the application? Teaching – Instructional Materials, Learning – Student Support, Organizing
Who is the user? Student
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Efficiency, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – Others
On the development of an AI performance and behavioural measures for teaching and classroom management

Andreea I.Niculescu, Jochen Ehnes, Chen Yi, Du Jiawei, Tay Chiat Pin, Joey Tianyi Zhou, Vigneshwaran Subbaraju, Teh Kah Kuan, Tran Huy Dat, Gi Soong Chee, Kenneth Kwok. (07/2025). arXiv.

What is the application? Teaching – Professional Learning
Who is the user? Educator
Which age? Post-Secondary
Why use AI? Efficiency, Other
Study design: Descriptive – Product Development, Technical – Computational
Beyond Classical And Contemporary Models: A Transformative Ai Framework For Student Dropout Prediction In Distance Learning Using RAG, Prompt Engineering, And Cross-Modal Fusion

Miloud Mihoubi, Meriem Zerkouk, Belkacem Chikhaoui. (07/2025). arXiv.

What is the application? Analyzing
Who is the user? Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Differentiation
Study design: Technical – Computational
Natural Language-based Assessment of L2 Oral Proficiency using LLMs

Stefano Banno, Rao Ma, Mengjie Qian, Siyuan Tang, Kate Knill, Mark Gales. (07/2025). arXiv.

What is the application? Teaching – Assessment and Feedback
Who is the user?
Which age? Post-Secondary, Adult
Why use AI? Efficiency, Outcomes – Other Academic
Study design: Technical – Computational
SentiDrop: A Multi-Modal Machine Learning model for Predicting Dropout in Distance Learning

Meriem Zerkouk, Miloud Mihoubi, Belkacem Chikhaoui. (07/2025). arXiv.

What is the application? Analyzing
Who is the user? Educator
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Differentiation
Study design: Technical – Computational
AI-Powered Math Tutoring: Platform for Personalized and Adaptive Education

Jaros_aw A. Chudziak, Adam Kostka. (07/2025). arXiv.

What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Product Development, Technical – Computational
SimStep: Chain-of-Abstractions for Incremental Specification and Debugging of AI-Generated Interactive Simulations

Zoe Kaputa, Anika Rajaram, Vryan Almanon Feliciano, Zhuoyue Lyu, Maneesh Agrawala, Hari Subramonyam. (07/2025). arXiv.

What is the application? Teaching – Instructional Materials
Who is the user? Educator
Which age? High School (9-12)
Why use AI? Efficiency, Outcomes – Other Academic
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – Others
Can LLMs Reliably Simulate Real Students' Abilities in Mathematics and Reading Comprehension?

KV Aditya Srivatsa, Kaushal Kumar Maurya, Ekaterina Kochmar. (07/2025). arXiv.

What is the application? Teaching – Assessment and Feedback
Who is the user?
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Efficiency
Study design: Technical – Computational
Enhancing Essay Cohesion Assessment: A Novel Item Response Theory Approach

Bruno Alexandre Rosa, Hil¬ário Oliveira, Luiz Rodrigues, Eduardo Araujo Oliveira, Rafael Ferreira Mello. (07/2025). arXiv.

What is the application? Teaching – Assessment and Feedback
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 – Differentiation
Study design: Technical – Computational
Findings of the BEA 2025 Shared Task on Pedagogical Ability Assessment of AI-powered Tutors

Ekaterina Kochmar, Kaushal Kumar Maurya, Kseniia Petukhova, KV Aditya Srivatsa, Ana¬Øs Tack, Justin Vasselli. (07/2025). 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), Post-Secondary
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical – Computational
Short-Term Gains, Long-Term Gaps: The Impact Of GenAI and Search Technologies On Retention

Mahir Akgun, Sacip Toker. (07/2025). arXiv.

What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Durable Skills
Study design: Impact – Randomized Controlled Trial
Do AI tutors empower or enslave learners? Toward a critical use of AI in education

Lucile Favero, Juan Antonio P¬érez-Ortiz, Tanja K¬ásser and Nuria Oliver. (07/2025). arXiv.

What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Differentiation, Outcomes – Social Emotional, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Implementation and Use
Exploring LLMs for Predicting Tutor Strategy and Student Outcomes in Dialogues

Fareya Ikram, Alexander Scarlatos, Andrew Lan. (07/2025). arXiv.

What is the application? Analyzing
Who is the user?
Which age? Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Numeracy
Study design: Technical – Computational
Creating a customisable freely-accessible Socratic AI physics tutor

Eugenio Tufino, Bor Gregorcic. (07/2025). arXiv.

What is the application? Learning – Student Support
Who is the user? Student, Educator
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Durable Skills
Study design: Descriptive – Implementation and Use, Descriptive – Product Development
Assessing the Prevalence of AI-assisted Cheating in Programming Courses: A Pilot Study

Kal¬éu Delphino. (07/2025). arXiv.

What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic
Study design: Descriptive – Implementation and Use, Quantitative – Others
Narrowing the Gap: Supervised Fine-Tuning of Open-Source LLMs as a Viable Alternative to Proprietary Models for Pedagogical Tools

Lorenzo Lee Solano, Charles Koutcheme, Juho Leinonen, Alexandra Vassar, Jake Renzella. (07/2025). arXiv.

What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Durable Skills, Other
Study design: Technical – Computational
AGACCI : Affiliated Grading Agents for Criteria-Centric Interface in Educational Coding Contexts

Kwangsuk Park, Jiwoong Yang. (07/2025). arXiv.

What is the application? Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic
Study design: Technical – Computational
Conversational Education at Scale: A Multi-LLM Agent Workflow for Procedural Learning and Pedagogic Quality Assessment

Jiahuan Pei, Fanghua Ye, Xin Sun, Wentao Deng, Koen Hindriks, Junxiao Wang. (07/2025). arXiv.

What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support
Who is the user?
Which age? Post-Secondary, Adult
Why use AI? Efficiency, Outcomes – Other Academic, Other
Study design: Descriptive – Product Development, Technical – Computational
Understanding The Impacts Of Generative Ai Use On Children

Hashem, Y., Esnaashari, S., Onslow, K., Chakraborty, S., Poletaev, A., Francis, J., Bright, J. (2025).. (07/2025). SSRN.

What is the application? Learning – Student Support, Communicating / Social Tools
Who is the user? Student, Parent/Caregiver
Which age? Elementary (PK5)
Why use AI? Outcomes – Literacy, Outcomes – Social Emotional, Other
Study design: Quantitative – Others
Do Students Write Better Post-AI Support? Effects of Generative AI Literacy and Chatbot Interaction Strategies on Multimodal Academic Writing

Yueqiao Jin, Kaixun Yang, Roberto Martinez-Maldonado, Dragan Ga_evi_, Lixiang Yan. (07/2025). arXiv.

What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Literacy, Outcomes – Durable Skills
Study design: Impact – Randomized Controlled Trial
From Query to Explanation: Uni-RAG for Multi-Modal Retrieval-Augmented Learning in STEM

Xinyi Wu, Yanhao Jia, Luwei Xiao, Shuai Zhao, Fengkuang Chiang, Erik Cambria. (07/2025). arXiv.

What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student, Educator
Which age? Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Technical – Computational
Evaluating the Effectiveness of Large Language Models in Solving Simple Programming Tasks: A User-Centered Study

Kai Deng. (07/2025). arXiv.

What is the application? Learning – Student Support
Who is the user? Student
Which age? High School (9-12)
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Durable Skills
Study design: Impact – Quasi–experimental
Detection of Disengagement from Voluntary Quizzes: An Explainable Machine Learning Approach in Higher Distance Education

Behnam Parsaeifard, Christof Imhof, Tansu Pancar, Ioan-Sorin Comsa, Martin Hlosta, Nicole Bergamin and Per Bergamin. (07/2025). arXiv.

What is the application? Analyzing
Who is the user? Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Technical – Computational
Autonomous AI Surveillance: Multimodal Deep Learning for Cognitive and Behavioral Monitoring

Ameer Hamza, Zuhaib Hussain But, Umar Arif, Samiya, M. Abdullah Asad, Muhammad Naeem. (07/2025). arXiv.

What is the application? Teaching – Assessment and Feedback, Organizing, Analyzing
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – Computational

Research Study Repository

Research Categories

Scope & Relevance

This Repository is For You

Search and Filter

Submit a research study

LEKIA: A Framework for Architectural Alignment via Expert Knowledge Injection

EduThink4AI: Translating Educational Critical Thinking into Multi-Agent LLM Systems

Explainable Collaborative Problem Solving Diagnosis with BERT using SHAP and its Implications for Teacher Adoption

Using LLMs to identify features of personal and professional skills in an open-response situational judgment test

Partnering with AI: A Pedagogical Feedback System for LLM Integration into Programming Education

Findings of MEGA: Maths Explanation with LLMs using the Socratic Method for Active Learning

Mitigating Trojanized Prompt Chains In Educational Llm Use Cases: Experimental Findings and Detection Tool Design

On the development of an AI performance and behavioural measures for teaching and classroom management

Beyond Classical And Contemporary Models: A Transformative Ai Framework For Student Dropout Prediction In Distance Learning Using RAG, Prompt Engineering, And Cross-Modal Fusion

Natural Language-based Assessment of L2 Oral Proficiency using LLMs

SentiDrop: A Multi-Modal Machine Learning model for Predicting Dropout in Distance Learning

AI-Powered Math Tutoring: Platform for Personalized and Adaptive Education

SimStep: Chain-of-Abstractions for Incremental Specification and Debugging of AI-Generated Interactive Simulations

Can LLMs Reliably Simulate Real Students' Abilities in Mathematics and Reading Comprehension?

Enhancing Essay Cohesion Assessment: A Novel Item Response Theory Approach

Findings of the BEA 2025 Shared Task on Pedagogical Ability Assessment of AI-powered Tutors

Short-Term Gains, Long-Term Gaps: The Impact Of GenAI and Search Technologies On Retention

Do AI tutors empower or enslave learners? Toward a critical use of AI in education

Exploring LLMs for Predicting Tutor Strategy and Student Outcomes in Dialogues

Creating a customisable freely-accessible Socratic AI physics tutor

Assessing the Prevalence of AI-assisted Cheating in Programming Courses: A Pilot Study

Narrowing the Gap: Supervised Fine-Tuning of Open-Source LLMs as a Viable Alternative to Proprietary Models for Pedagogical Tools

AGACCI : Affiliated Grading Agents for Criteria-Centric Interface in Educational Coding Contexts

Conversational Education at Scale: A Multi-LLM Agent Workflow for Procedural Learning and Pedagogic Quality Assessment

Understanding The Impacts Of Generative Ai Use On Children

Do Students Write Better Post-AI Support? Effects of Generative AI Literacy and Chatbot Interaction Strategies on Multimodal Academic Writing

From Query to Explanation: Uni-RAG for Multi-Modal Retrieval-Augmented Learning in STEM

Evaluating the Effectiveness of Large Language Models in Solving Simple Programming Tasks: A User-Centered Study

Detection of Disengagement from Voluntary Quizzes: An Explainable Machine Learning Approach in Higher Distance Education

Autonomous AI Surveillance: Multimodal Deep Learning for Cognitive and Behavioral Monitoring