Search and Filter
Repository Feedback
Your feedback helps us improve the repository's content relevance and usability. Please share your thoughts to help us better serve researchers and practitioners.
Submit a research study
Contribute to the repository:
Research Study Repository
Research synthesis is AI-generated, human reviewed. Updated 08/2026.
Showing 631 - 660 of 1627 results
Ezyer: A Simulacrum Of High School With Generative Agent
Jinming Yang, Zimu Ji, Weiqi Luo, Gaoxi Wang, Bin Ma, Yueling Deng. (12/2025). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student, Educator
Which age? High School (9-12)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Differentiation, Reimagined Schooling
Study design: Descriptive – Product Development, Technical – ComputationalAi Tutoring Enhances Student Learning Without Crowding Out Reading Effort
Mira Fischer, Holger A. Rau, Rainer Michael Rilke. (12/2025). IZA Institute of Labor Economics.
What is the application? 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 TrialArtificial Intelligence Competence Of K-12 Students Shapes Their Ai Risk Perception: A Co-Occurrence Network Analysis
Ville Heilala, Pieta Sikstrom, Mika Setala, Tommi Karkkainen. (12/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? High School (9-12)
Why use AI? Outcomes – Differentiation, Outcomes – Durable Skills, Other
Study design: Quantitative – OthersKidspeak: A General Multi-Purpose LLM For Kids' Speech Recognition And Screening
Rohan Sharma, Dancheng Liu, Jingchen Sun, Shijie Zhou, Jiayu Qin, Jinjun Xiong, Changyou Chen. (12/2025). arXiv.
What is the application? Analyzing, Learning – Student Support, Teaching – Assessment and Feedback
Who is the user? Others
Which age? 0-3 years, Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Literacy, Outcomes – Differentiation
Study design: Technical – ComputationalHomogenizing effect of large language models (LLMs) on creative diversity: An empirical comparison of human and ChatGPT writing
Kibum Moon, Adam E. Green, Kostadin Kushlev. (12/2025). Computers in Human Behavior: Artifical Humans.
What is the application? Learning – Student Support
Who is the user? Student
Which age? High School (9-12), Post-Secondary
Why use AI? Outcomes – Literacy, Outcomes – Durable Skills
Study design: Quantitative – Others, Systematic ReviewLlm-Based Automated Grading With Human-In-The-Loop
Yucheng Chu, Yasemin Copur-Gencturk, Hang Li, Kaiqi Yang, Jiliang Tang. (12/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Adult
Why use AI? Efficiency
Study design: Technical – ComputationalAi-Enabled Grading With Near-Domain Data For Scaling Feedback With Human-Level Accuracy
Shyam Agarwall, Ali Moghimi, Kevin C. Haudek. (12/2025). 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, Outcomes – Durable Skills, Other
Study design: Technical – Computational, Quantitative – OthersChatgpt-5 In Secondary Education: A Mixed-Methods Analysis Of Student Attitudes, Ai Anxiety, And Hallucination-Aware Use
Tryfon Sivenas. (11/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? High School (9-12)
Why use AI? Outcomes – Other Academic, Outcomes – Durable Skills
Study design: Quantitative – OthersConfident Rag: Enhancing The Performance Of Llms For Mathematics Question Answering Through Multi-Embedding And Confidence Scoring
Shiting Chen, Zijian Zhao and Jinsong Chen. (11/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Middle School (6-8)
Why use AI? Outcomes – Numeracy
Study design: Technical – ComputationalSupporting Productivity Skill Development In College Students Through Social Robot Coaching: A Proof-Of-Concept
Himanshi Lalwani, Hanan Salam. (11/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Product Development, Quantitative – OthersPacee: Supporting Children'S Personal Emotion Education Through Parent-Ai Collaboration
Yu Mei, Xutong Wang, Ziyao Zhang, Yiming Fu, Shiyi Wang, Qingyang Wan, Qinghuan Lan, Chang Liu, Jie Cai, Chun Yu, Yuanchun Shi. (11/2025). arXiv.
What is the application? Teaching – Professional Learning, Learning – Student Support, Communicating / Social Tools
Who is the user? Parent/Caregiver
Which age? 0-3 years, Elementary (PK5)
Why use AI? Outcomes – Social Emotional
Study design: Descriptive – Implementation and Use, Descriptive – Product Development, Impact – Randomized Controlled Trial, Quantitative – OthersExploring Student Interactions With Ai-Powered Learning Tools: A Qualitative Study Connecting Interaction Patterns To Educational Learning Theories
Prathamesh Muzumdar, Sumanth Cheemalapati. (11/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Social Emotional, Outcomes – Durable Skills
Study design: Descriptive – Implementation and UsePeoat: Personalization-Guided Evolutionary Question Assembly For One-Shot Adaptive Testing
Xiaoshan Yu, Ziwei Huang, Shangshang Yang, Ziwen Wang, Haiping Ma, Xingyi Zhang. (11/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Student
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary, Adult
Why use AI? Efficiency, Outcomes – Differentiation
Study design: Technical – ComputationalEdueval: A Hierarchical Cognitive Benchmark For Evaluating Large Language Models In Chinese Education
Guoqing Ma, Jia Zhu, Hanghui Guo, Weijie Shi, Yue Cui, Jiawei Shen, Zilong Li, Yidan Liang. (11/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Analyzing
Who is the user? 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 – Durable Skills, Reimagined Schooling
Study design: Technical – ComputationalFeanel: A Benchmark For Fine-Grained Error Analysis In K-12 English Writing
Jingheng Ye, Shen Wang, Jiaqi Chen, Hebin Wang, Deqing Zou, Yanyu Zhu, Jiwei Tang, Hai-Tao Zheng, Ruitong Liu, Haoyang Li, Yanfeng Wang, Qingsong Wen. (11/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Others
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Literacy, Outcomes – Differentiation
Study design: Technical – ComputationalTraining For Obsolescence? The Ai-Driven Education Trap
Andrew J. Peterson. (11/2025). arXiv.
What is the application? Teaching – Instructional Materials, 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? Efficiency, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Social Emotional, Outcomes – Durable Skills
Study design: Descriptive – Implementation and Use, Quantitative – OthersAutomated Program Repair Of Uncompilable Student Code
Griffin Pitts, Aum Pandya, Darsh Rank, Tirth Bhatt, Muntasir Hoq, Bita Akram. (11/2025). arXiv.
What is the application? Teaching – Assessment and Feedback, Analyzing
Who is the user?
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Differentiation
Study design: Technical – ComputationalRethinking Ai Evaluation Through Teach-Ai: A Human-Centered Benchmark And Toolkit For Evaluating Ai Assistants In Education
Shi Ding, Brian Magerko. (11/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support, Organizing
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, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Product Development, Systematic ReviewScaling Equitable Reflection Assessment In Education Via Large Language Models And Role-Based Feedback Agents
Chenyu Zhang, Xiaohang Luo. (11/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Adult
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersHuman Experts' Evaluation Of Generative Ai For Contextualizing Steam Education In The Global South
Matthew Nyaaba, Macharious Nabang, Patrick Kyeremeh, Ibrahim Nantomah, Collins Owusu-Fordjour, Martin Ako, Bismark Nyaaba Akanzire, Kassim Korah Nantomah, Cecilia Issaka, Xiaoming Zhai. (11/2025). arXiv.
What is the application? Teaching – Instructional Materials
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8)
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Social Emotional, Reimagined Schooling
Study design: Quantitative – OthersCllmrec: Llm-Powered Cognitive-Aware Concept Recommendation Via Semantic Alignment And Prerequisite Knowledge Distillation
Xiangrui Xiong, Yichuan Lu, Zifei Pan, Chang Sun. (11/2025). 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? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Technical – Computational, Quantitative – OthersSupporting Students In Navigating Llm-Generated Insecure Code
Jaehwan Park, Kyungchan Lim, Seonhye Park, Doowon Kim. (11/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Durable Skills
Study design: Descriptive – Product Development, Quantitative – OthersChatgpt As A Cognitive Crutch: Evidence From A Randomized Controlled Trial On Knowledge Retention
Andre Barcaui. (11/2025). Social Sciences & Humanities Open.
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 TrialPresentcoach: Dual-Agent Presentation Coaching Through Exemplars And Interactive Feedback
Sirui Chen, Jinsong Zhou, Xinli Xu, Xiaoyu YANG, Litao Guo, Ying-Cong Chen. (11/2025). arXiv.
What is the application? Teaching – Assessment and Feedback, Teaching – Professional Learning, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Social Emotional, Outcomes – Durable Skills
Study design:Tutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise
Rose E. Wang, Ana T. Ribeiro, Carly D. Robinson, Susanna Loeb, Dora Demszky. (11/2025). EdWorkingPapers.
What is the application? Learning – Student Support, Teaching – Professional Learning
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Impact – Randomized Controlled TrialAddressing Situated Teaching Needs: A Multi-Agent Framework For Automated Slide Adaptation
Binglin Liu, Yucheng Wang, Zheyuan Zhang, Jiyuan Lu, Shen Yang, Daniel Zhang-Li, Huiqin Liu, Jifan Yu. (11/2025). arXiv.
What is the application? Teaching – Instructional Materials, Organizing
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Efficiency
Study design: Descriptive – Product Development, Technical – ComputationalScaling Item-To-Standard Alignment With Large Language Models: Accuracy, Limits, And Solutions
Farzan Karimi-Malekabadi, Pooya Razavi, Sonya Powers. (11/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Elementary (PK5)
Why use AI? Efficiency
Study design: Technical – ComputationalMagma-Edu: Multi-Agent Generative Multimodal Framework For Text-Diagram Educational Question Generation
Zhenyu Wu, Jian Li, Hua Huang. (11/2025). arXiv.
What is the application? Teaching – Instructional Materials
Who is the user? Educator
Which age? Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Numeracy, Other
Study design: Technical – ComputationalGenerating Reading Comprehension Exercises With Large Language Models For Educational Applications
Xingyu Huang, Fei Jiang, Jianli Xiao. (11/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback
Who is the user? Student, Educator
Which age? Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Differentiation
Study design: Technical – ComputationalExploring Families' Use And Mediation Of Generative Ai: A Multi-User Perspective
Shirley Zhang, Dakota Sullivan, Jennica Li, Bengisu Cagiltay, Bilge Mutlu, Heather Kirkorian, Kassem Fawaz. (11/2025). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student, Parent/Caregiver
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Social Emotional, Outcomes – Durable Skills, Other
Study design: Descriptive – Implementation and Use
