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Research Study Repository
Research synthesis is AI-generated, human reviewed. Updated 08/2026.
Showing 1111 - 1140 of 1627 results
Evaluating Gemini in an Arena for Learning
LearnLM Team, Google. (05/2025). 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? Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Technical – ComputationalWhere's the Line? A Classroom Activity on Ethical and Constructive Use of Generative AI in Physics
Zosia Krusberg. (05/2025). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Durable Skills
Study design: Descriptive – Implementation and Use, Descriptive – Product DevelopmentEnhancing Marker Scoring Accuracy through Ordinal Confidence Modelling in Educational Assessments
Abhirup Chakravarty, Mark Brenchley, Trevor Breakspear, Ian Lewin, Yan Huang. (05/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Post-Secondary, Adult
Why use AI? Efficiency, Other
Study design: Technical – ComputationalFrom Coders to Critics: Empowering Students through Peer Assessment in the Age of AI Copilots
Santiago Berrezueta-Guzman, Stephan Krusche, Stefan Wagner. (05/2025). arXiv.
What is the application?
Who is the user?
Which age? Post-Secondary
Why use AI? Outcomes – Durable Skills
Study design: Quantitative – OthersA Human-Centric Approach to Explainable AI for Personalized Education
Vinitra Swamy. (05/2025). 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 – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Implementation and Use, Descriptive – Product Development, Technical – Computational, Quantitative – OthersDistinguishing Fact from Fiction: Student Traits, Attitudes, and AI Hallucination Detection in Business School Assessment
Dr Canh Thien Dang, Dr An Nguyen. (05/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Durable Skills
Study design: Quantitative – OthersLearn Like Feynman: Developing and Testing an AI-Driven Feynman Bot
Akshaya Rajesh, Sumbul Khan. (05/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Adult
Why use AI? Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Product Development, Impact – Quasi–experimentalFrom EduVisBench to EduVisAgent: A Benchmark and Multi-Agent Framework for Reasoning-Driven Pedagogical Visualization
Haonian Ji, Shi Qiu, Siyang Xin, Siwei Han, Zhaorun Chen, Dake Zhang, Hongyi Wang, Huaxiu Yao. (05/2025). arXiv.
What is the application? Teaching – Instructional Materials
Who is the user?
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 – ComputationalCoderAgent: Simulating Student Behavior for Personalized Programming Learning with Large Language Models
Yi Zhan, Qi Liu, Weibo Gao, Zheng Zhang, Tianfu Wang, Shuanghong Shen, Junyu Lu and Zhenya Huang. (05/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary, Adult
Why use AI? Efficiency, Outcomes – Differentiation
Study design: Technical – ComputationalLMCD: Language Models are Zeroshot Cognitive Diagnosis Learners
Yu He, Zihan Yao, Chentao Song, Tianyu Qi, Jun Liu, Ming Li, Qing Huang. (05/2025). 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? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical – ComputationalEvaluating LLM Adaptation to Sociodemographic Factors: User Profile vs. Dialogue History
Qishuai Zhong, Zongmin Li, Siqi Fan, Aixin Sun. (05/2025). arXiv.
What is the application?
Who is the user?
Which age?
Why use AI? Other
Study design: Technical – ComputationalA Structured Unplugged Approach for Foundational AI Literacy in Primary Education
Maria Cristina Carrisi, Mirko Marras, Sara Vergallo. (05/2025). arXiv.
What is the application?
Who is the user?
Which age? Elementary (PK5)
Why use AI? Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Durable Skills
Study design: Quantitative – OthersRATAS: A Generative AI Framework for Explainable and Scalable Automated Answer Grading
Masoud Safilian, Amin Beheshti, Stephen Elbourn. (05/2025). 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
Study design: Technical – ComputationalParticle Builder - Learn about the Standard Model while playing against an AI*
Mohammad Attar, Andrew Carse, Yeming Chen, Thomas Green, Jeong-Yeon Ha, Yanbai Jin, Amy McWilliams, Theirry Panggabean, Zhengyu Peng, Lujin Sun, Jing Ru, Jiacheng She, Jialin Wang, Zilun Wei, Jiayuan Zhu, Lachlan McGinness. (05/2025). 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
Study design: Descriptive – Product Development, Quantitative – OthersIntegrating emotional intelligence, memory architecture, and gestures to achieve empathetic humanoid robot interaction in an educational setting
Fuze Sun, Lingyu Li, Shixiangyue Meng, Xiaoming Teng, Terry Payne, Paul Craig. (05/2025). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Social Emotional
Study design: Descriptive – Product Development, Impact – Randomized Controlled TrialAutomated evaluation of children's speech fluency for low-resource languages
Bowen Zhang, Nur Afiqah Abdul Latiff, Justin Kan, Rong Tong, Donny Soh, Xiaoxiao Miao, Ian McLoughlin. (05/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Student, Educator
Which age? Elementary (PK5)
Why use AI? Efficiency, Outcomes – Other Academic
Study design: Technical – ComputationalEvaluating Software Plagiarism Detection in the Age of AI Automated Obfuscation and Lessons for Academic Integrity
Timur SaŸlam, Larissa Schmid. (05/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic
Study design: Technical – Computational, Quantitative – OthersInvestigating Pedagogical Teacher and Student LLM Agents: Genetic Adaptation Meets Retrieval-Augmented Generation Across Learning Styles
Debdeep Sanyal, Agniva Maiti, Umakanta Maharana, Dhruv Kumar, Ankur Mali, C. Lee Giles, Murari Mandal. (05/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Teaching – Professional Learning
Who is the user? Educator
Which age? High School (9-12), Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Differentiation
Study design: Technical – Computational, Quantitative – OthersFrom Chalkboards to Chatbots: Evaluating the Impact of Generative AI on Learning Outcomes in Nigeria
Mart’n De Simone, Federico Tiberti, Maria Barron Rodriguez, Federico Manolio, Wuraola Mosuro, Eliot Jolomi Dikoru. (05/2025). arXiv.
What is the application? Learning – Student Support, Teaching – Instructional Materials
Who is the user? Student, Educator
Which age? High School (9-12)
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation, Reimagined Schooling
Study design: Impact – Randomized Controlled Trial, Impact – Quasi–experimentalA systematic review of AI-driven intelligent tutoring systems (ITS) in K-12 education
Angélique Létourneau, Marion Deslandes Martineau, Patrick Charland, John Alexander Karran, Jared Boasen, Pierre Majorique L√©ger. (05/2025). npj Science of Learning.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Technical – ComputationalA qualitative systematic review on Al empowered self-regulated learning in higher education
Min Lan, Xiaofeng Zhou. (05/2025). npj Science of Learning.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support, Analyzing
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Literacy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Social Emotional, Outcomes – Durable Skills
Study design: Systematic ReviewLLMs to Support K-12 Teachers in Culturally Relevant Pedagogy: An AI Literacy Example
Jiayi Wang, Ruiwei Xiao, Xinying Hou, Hanqi Li, Ying Jui Tseng, John Stamper, Ken Koedinger. (05/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Professional Learning, Organizing
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation, Reimagined Schooling
Study design: Descriptive – Implementation and Use, Descriptive – Product Development, Quantitative – OthersExploring LLM-Generated Feedback for Economics Essays: How Teaching Assistants Evaluate and Envision Its Use
Xinyi Lu, Aditya Mahesh, Zejia Shen, Mitchell Dudley, Larissa Sano, Xu Wang. (05/2025). 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 – Differentiation
Study design: Descriptive – Implementation and Use, Descriptive – Product DevelopmentChildren's Mental Models of AI Reasoning: Implications for AI Literacy Education
Aayushi Dangol, Robert Wolfe, Runhua Zhao, JaeWon Kim, Trushaa Ramanan, Katie Davis, Julie A. Kientz. (05/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Elementary (PK5), Middle School (6-8)
Why use AI? Outcomes – Durable Skills
Study design: Descriptive – Product Development, Quantitative – OthersMSA at BEA 2025 Shared Task: Disagreement-Aware Instruction Tuning for Multi-Dimensional Evaluation of LLMs as Math Tutors
Baraa Hikal, Mohamed Basem, Islam Oshallah, Ali Hamdi. (05/2025). 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), Post-Secondary
Why use AI? Outcomes – Numeracy
Study design: Technical – ComputationalSlideItRight: Using AI to Find Relevant Slides and Provide Feedback for Open-Ended Questions
Chloe Qianhui Zhao, Jie Cao, Eason Chen, Kenneth R. Koedinger, Jionghao Lin. (05/2025). 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: Impact – Randomized Controlled TrialFrom First Draft to Final Insight: A Multi-Agent Approach for Feedback Generation
Jie Cao, Chloe Qianhui Zhao, Xian Chen, Shuman Wang, Christian Schunn, Kenneth R. Koedinger, Jionghao Lin. (05/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user?
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Social Emotional, Outcomes – Durable Skills
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersKCluster: An LLM-based Clustering Approach to Knowledge Component Discovery
Yumou Wei, Paulo Carvalho, John Stamper. (05/2025). arXiv.
What is the application? 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: Technical – ComputationalVTutor: An Animated Pedagogical Agent SDK that Provide Real Time Multi-Model Feedback
Eason Chen, Chenyu Lin, Yu-Kai Huang, Xinyi Tang, Aprille Xi, Jionghao Lin, Kenneth Koedinger. (05/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary, Adult
Why use AI? Efficiency, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersTowards Actionable Pedagogical Feedback: A Multi-Perspective Analysis of Mathematics Teaching and Tutoring Dialogue
Jannatun Naim, Jie Cao, Fareen Tasneem, Jennifer Jacobs, Brent Milne, Tamara Sumner, James Martin. (05/2025). arXiv.
What is the application? Teaching – Professional Learning
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Implementation and Use, Technical – Computational
