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 421 - 450 of 553 results
NotebookLM: An LLM with RAG for active learning and collaborative tutoring
Eugenio Tufino. (04/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Professional Learning, Learning – Student Support
Who is the user? Student, Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Descriptive – Product DevelopmentInclusive Education with AI: Supporting Special Needs and Tackling Language Barriers
Ricardo Fitas. (04/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support, Communicating / Social Tools, Organizing, Analyzing
Who is the user? Student, Parent/Caregiver, Educator, School Leader, Others
Which age? Elementary (PK5)
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Social Emotional, Reimagined Schooling, Other
Study design: Descriptive – Implementation and Use, Descriptive – Product Development, Systematic ReviewAI for Accessible Education: Personalized Audio-Based Learning for Blind Students
Crystal Yang, Paul Taele. (04/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Elementary (PK5)
Why use AI? Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product DevelopmentAugmenting Captions With Emotional Cues: An Ar Interface For Real-Time Accessible Communication
Sunday David Ubur. (04/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersINSIGHT: Bridging the Student-Teacher Gap in Times of Large Language Models
Jarne Thys, Sebe Vanbrabant, Davy Vanacken, Gustavo Rovelo Ruiz. (04/2025). arXiv.
What is the application? Learning – Student Support, Analyzing
Who is the user? Student, Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Product Development, Technical – ComputationalA Platform for Generating Educational Activities to Teach English as a Second Language
Aiala Rosa, Santiago Gongora, Juan Pablo Filevich, Ignacio Sastre, Laura Musto, Brian Carpenter, Luis Chiruzzo. (04/2025). 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)
Why use AI? Outcomes – Other Academic
Study design: Descriptive – Product Development, Technical – ComputationalFostering Self-Directed Growth with Generative AI: Toward a New Learning Analytics Framework
Qianrun Mao. (04/2025). arXiv.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary, Adult
Why use AI? Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Product DevelopmentLLMs as Educational Analysts: Transforming Multimodal Data Traces into Actionable Reading Assessment Reports
Eduardo Davalos, Yike Zhang, Namrata Srivastaval, Jorge Alberto Salas, Sara McFadden, Sun-Joo Cho, Gautam Biswas, Amanda Goodwin. (03/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Elementary (PK5)
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – Others"Don't Forget the Teachers": Towards an Educator-Centered Understanding of Harms from Large Language Models in Education
Emma Harvey, Allison Koenecke, RenŽ F. Kizilcec. (02/2025). 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)
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Implementation and Use, Descriptive – Product DevelopmentVTutor: An Open-Source SDK for Generative AI-Powered Animated Pedagogical Agents with Multi-Media Output
Eason Chen, Chenyu Lin, Xinyi Tang, Aprille Xi, Canwen Wang, Jionghao Lin, Kenneth R. Koedinger. (02/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Educator, Others
Which age? Post-Secondary, Adult
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – ComputationalTowards Adaptive Feedback with AI: Comparing the Feedback Quality of LLMs and Teachers on Experimentation Protocols
Kathrin Sessler, Arne Bewersdorff, Claudia Nerdel, Enkelejda Kasneci. (02/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Middle School (6-8)
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersThe Responsible Development of Automated Student Feedback with Generative AI
Euan D Lindsay, Mike Zhang, Aditya Johri, Johannes Bjerva. (02/2025). arXiv.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student, Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Differentiation, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Product DevelopmentThe Art of Storytelling: Multi-Agent Generative AI for Dynamic Multimodal Narratives
Samee Arif, Taimoor Arif, Muhammad Saad Haroon, Aamina Jamal Khan, Agha Ali Raza, Awais Athar. (02/2025). arXiv.
What is the application? Teaching – Instructional Materials
Who is the user? Student
Which age? Elementary (PK5), Middle School (6-8)
Why use AI? Outcomes – Literacy, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Product Development, Technical – ComputationalThe Advancement of Personalized Learning Potentially Accelerated by Generative AI
Yuang Wei, Yuan-Hao Jiang, Jiayi Liu, Changyong Qi, Linzhao Jia, Rui Jia. (02/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Teaching – Professional Learning, Learning – Student Support, Communicating / Social Tools, 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 – Differentiation, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Product Development, Systematic ReviewSocratiQ: A Generative AI-Powered Learning Companion for Personalized Education and Broader Accessibility
Jason Jabbour, Kai Kleinbard, Olivia Miller, Robert Haussman, Vijay Janapa Reddi. (02/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary, Adult
Why use AI? Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills, Other
Study design: Descriptive – Implementation and Use, Descriptive – Product Development, Technical – Computational, Quantitative – OthersSET-PAIRED: Designing for Parental Involvement in Learning with an AI-Assisted Educational Robot
Hui-Ru Ho, Nitigya Kargeti, Ziqi Liu, Bilge Mutlu. (02/2025). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Parent/Caregiver
Which age? Elementary (PK5)
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Social Emotional, Other
Study design: Descriptive – Product Development, Quantitative – OthersScaffolding Middle-School Mathematics Curricula With Large Language Models
Rizwaan Malik, Dorna Abdi, Rose Wang, Dorottya Demszky. (02/2025). British Journal of Educational Technology.
What is the application? Teaching – Instructional Materials
Who is the user? Educator
Which age? Middle School (6-8)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersPosition: LLMs Can be Good Tutors in Foreign Language Education
Jingheng Ye, Shen Wang, Deqing Zhou, Yibo Yan, Kun Wang, Hai-Tao Zheng, Zenglin Xu, Irwin King, Philip S. Yu, Qingsong Wen. (02/2025). 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 – Literacy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Implementation and Use, Descriptive – Product DevelopmentMindCraft: Revolutionizing Education through AI-Powered Personalized Learning and Mentorship for Rural India
Arihant Bardia, Aayush Agrawal. (02/2025). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student, Educator, Others
Which age? Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Social Emotional, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Product DevelopmentCo-designing Large Language Model Tools for Project-Based Learning with K-12 Educators
Prerna Ravi, John Masla, Gisella Kakoti, Grace C. Lin, Emma Anderson, Matt Taylor, Anastasia K. Ostrowski, Cynthia Breazeal, Eric Klopfer, Hal Abelson. (02/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Organizing
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Efficiency, Outcomes – Differentiation, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Implementation and Use, Descriptive – Product DevelopmentUnifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors
Kaushal Kumar Maurya, KV Aditya Srivatsa, Kseniia Petukhova and Ekaterina Kochmar. (02/2025). arXiv.
… large language models (LLMs) are effective as AI tutors and whether they demonstrate pedagogical abilities necessary for good AI tutoring in educational dialogues. Previous efforts towards … designed to assess the pedagogical value of LLM-powered AI tutor responses grounded in student mistakes or confusion in …What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Elementary (PK5), Middle School (6-8)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – ComputationalTutorLLM: Customizing Learning Recommendations with Knowledge Tracing and Retrieval-Augmented Generation
Zhaoxing LI, Vahid Yazdanpanah, Jindi Wang, Wen Gu, Lei Shi, Alexandra I. Cristea, Sarah Kiden, Sebastian Stein. (01/2025). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Descriptive – Product Development, Impact – Randomized Controlled Trial, Technical – ComputationalIntelliChain: An Integrated Framework for Enhanced Socratic Method Dialogue with LLMs and Knowledge Graphs
Changyong Qi, Linzhao Jia, Yuang Wei, Yuan-Hao Jiang, Xiaoqing Gu. (01/2025). 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? Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersiLLuMinaTE: An LLM-XAI Framework Leveraging Social Science Explanation Theories Towards Actionable Student Performance Feedback
Vinitra Swamy, Davide Romano, Bhargav Srinivasa Desikan, Oana-Maria Camburu, Tanja Kaser. (01/2025). 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 – Differentiation
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersGenerative AI in Education: From Foundational Insights to the Socratic Playground for Learning
Xiangen Hu, Sheng Xu, Richard Tong, & Art Graesser. (01/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support, Communicating / Social Tools
Who is the user? Student
Which age? Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Product Development, Technical – ComputationalExploring Iterative Enhancement for Improving Learnersourced Multiple-Choice Question Explanations with Large Language Models
Qiming Bao, Juho Leinonen, Alex Yuxuan Peng, Wanjun Zhong, Ga‘l Gendron, Tim Pistotti, Alice Huang, Paul Denny, Michael Witbrock, Jiamou Liu. (01/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback
Who is the user? Student
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Product Development, Technical – ComputationalAuto-Evaluation: A Critical Measure in Driving Improvements in Quality and Safety of AI-Generated Lesson Resources
Hannah-Beth Clark, Margaux Dowland, Laura Benton, Reka Budai, Ibrahim Kaan Keskin, Emma Searle, Matthew Gregory, Mark Hodierne, William Gayne, John Roberts. (01/2025). 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 – Other Academic
Study design: Descriptive – Product Development, Quantitative – OthersA Study on Educational Data Analysis and Personalized Feedback Report Generation Based on Tags and ChatGPT*
Yizhou Zhou, Mengqiao Zhang, Yuan-Hao Jiang, Xinyu Gao, Naijie Liu, Bo Jiang. (01/2025). arXiv.
What is the application? Teaching – Assessment and Feedback, Analyzing
Who is the user? Educator
Which age? Elementary (PK5)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – Others"From Unseen Needs to Classroom Solutions": Exploring AI Literacy Challenges & Opportunities with Project-Based Learning Toolkit in K-12 Education
Hanqi Li, Ruiwei Xiao, Hsuan Nieu, Ying-Jui Tseng, Guanze Liao. (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? Middle School (6-8), High School (9-12)
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Implementation and Use, Descriptive – Product DevelopmentAI-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 – Others
