Research Study Repository
Research synthesis is AI-generated, human reviewed. Updated 04/2026.
Showing 541 - 570 of 1278 results
Humanizing Automated Programming Feedback: Fine-Tuning Generative Models with Student-Written Feedback
Victor-Alexandru Padurean, Tung Phung, Nachiket Kotalwar, Michael Liut, Juho Leinonen, Paul Denny, Adish Singla. (09/2025). 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
Study design: Descriptive – Product Development, Technical – ComputationalGenAI Voice Mode in Programming Education
Sven Jacobs, Natalie Kiesler. (09/2025). arXiv.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? High School (9-12)
Why use AI? Outcomes – Differentiation, Other
Study design: Descriptive – Implementation and Use, Descriptive – Product Development, Quantitative – OthersMachine Unlearning for Responsible and Adaptive AI in Education
Betty Mayeku, Sandra Hummel, Parisa Memarmoshrefi. (09/2025). arXiv.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support, Analyzing
Who is the user? Student, Educator
Which age? Post-Secondary
Why use AI? Outcomes – Differentiation, Reimagined Schooling, Other
Study design: Systematic ReviewMusicScaffold: Bridging Machine Efficiency and Human Growth in Adolescent Creative Education through Generative AI
Zhejing Hu, Yan Liu, Zhi Zhang, Gong Chen, Bruce X.B. Yu, Junxian Li, Jiannong Cao. (09/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Middle School (6-8)
Why use AI? Outcomes – Social Emotional, Outcomes – Durable Skills
Study design: Impact – Randomized Controlled TrialAesthetic Experience and Educational Value in Co-creating Art with Generative AI: Evidence from a Survey of Young Learners
Chengyuan Zhang, Suzhe Xu. (09/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Implementation and UseAutomated Classification of Tutors' Dialogue Acts Using Generative AI: A Case Study Using the CIMA Corpus
Liqun He, Jiaqi Xu. (09/2025). arXiv.
What is the application? Analyzing
Who is the user? Educator, Others
Which age? Post-Secondary
Why use AI? Efficiency
Study design: Technical – ComputationalAutomatic Detection of Inauthentic Templated Responses in English Language Assessments
Yashad Samant, Lee Becker, Scott Hellman, Bradley Behan, Sarah Hughes, Joshua Southerland. (09/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Post-Secondary, Adult
Why use AI? Other
Study design: Technical – ComputationalFeedback That Clicks: Introductory Physics Students' Valued Features in AI Feedback Generated From Self-Crafted and Engineered Prompts
Amogh Sirnoorkar, N. Sanjay Rebello. (09/2025). arXiv.
What is the application? 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 – Implementation and Use, Quantitative – OthersDeploying AI for Signal Processing education: Selected challenges and intriguing opportunities
Jarvis Haupt, Qin Lu, Yanning Shen, Jia Chen, Yue Dong, Dan McCreary, Mehmet Akcakaya, Georgios B. Giannakis. (09/2025). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support, Analyzing
Who is the user? Student, Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation, Reimagined Schooling
Study design: Descriptive – Product Development, Technical – Computational, Systematic ReviewYouthSafe: A Youth-Centric Safety Benchmark and Safeguard Model for Large Language Models
Yaman Yu, Yiren Liu, Jacky Zhang, Yun Huang, Yang Wang. (09/2025). arXiv.
What is the application? Communicating / Social Tools
Who is the user? Student
Which age? High School (9-12), Post-Secondary
Why use AI? Outcomes – Social Emotional, Other
Study design: Technical – ComputationalThe ends of tests: Possibilities for transformative assessment and learning with generative AI
Bill Cope, Mary Kalantzis, Akash Kumar Saini. (09/2025). Unesco.
What is the application? Teaching – Assessment and Feedback
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 DevelopmentUnderstanding, Protecting, and Augmenting Human Cognition with Generative AI: A Synthesis of the CHI 2025 Tools for Thought Workshop
Lev Tankelevitch, Elena L. Glassman, Jessica He, Aniket Kittur, Mina Lee, Srishti Palani, Advait Sarkar, Gonzalo Ramos, Yvonne Rogers, Hari Subramonyam. (08/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Professional Learning, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary, Adult
Why use AI? Outcomes – Social Emotional, Outcomes – Durable Skills
Study design:MathBuddy: A Multimodal System for Affective Math Tutoring
Debanjana Kar, Leopold B¬öss, Dacia Braca, Sebastian Maximilian Dennerlein, Nina Christine Hubig, Philipp Wintersberger, Yufang Hou. (08/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? High School (9-12), Post-Secondary, Adult
Why use AI? Outcomes – Numeracy, Outcomes – Social Emotional
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersDo Students Rely on AI? Analysis of Student-ChatGPT Conversations from a Field Study
Jiayu Zheng, Lingxin Hao, Kelun Lu, Ashi Garg, Mike Reese, Melo-Jean Yap, I-Jeng Wang, Xingyun Wu, Wenrui Huang, Jenna Hoffman, Ariane Kelly, My Le, Ryan Zhang, Yanyu Lin, Muhammad Faayez, Anqi Liu. (08/2025). 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: Quantitative – OthersInstructional Agents: LLM Agents on Automated Course Material Generation for Teaching Faculties
Huaiyuan Yao, Wanpeng Xu, Justin Turnau, Nadia Kellam, Hua Wei. (08/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic, Reimagined Schooling
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersSkill-based Explanations for Serendipitous Course Recommendation
Hung Chau, Run Yu, Zachary Pardos, Peter Brusilovsky. (08/2025). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student
Which age? Post-Secondary
Why use AI? Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Product Development, Impact – Randomized Controlled Trial, Technical – ComputationalPrompting Strategies for Language Model-Based Item Generation in K-12 Education: Bridging the Gap Between Small and Large Language Models
Mohammad Amini, Babak Ahmadi, Xiaomeng Xiong, Yilin Zhang, Christopher Qiao. (08/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Differentiation
Study design: Technical – ComputationalAutomatic Question & Answer Generation Using Generative Large Language Model (LLM)
A.S.M Mehedi Hasan, Md. Alvee Ehsan, Kefaya Benta Shahnoor, Syeda Sumaiya Tasneem. (08/2025). 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, Adult
Why use AI? Efficiency, Outcomes – Differentiation, Outcomes – Durable Skills, Other
Study design: Technical – ComputationalMAB Optimizer for Estimating Math Question Difficulty via Inverse CV without NLP
Surajit Das, Gourav Roy, Aleksei Eliseev, Ram Kumar Rajendran. (08/2025). arXiv.
What is the application? Teaching – Assessment and Feedback, Analyzing
Who is the user?
Which age? Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical – ComputationalWho Is Lagging Behind: Profiling Student Behaviors with Graph-Level Encoding in Curriculum-Based Online Learning Systems
Qian Xiao, Conn Breathnach, Ioana Ghergulescu, Conor O'Sullivan, Keith Johnston, Vincent Wade. (08/2025). arXiv.
What is the application? Teaching – Assessment and Feedback, Analyzing
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – ComputationalExploring Generative Artificial Intelligence (GenAI) and AI Agents in Research and Teaching - Concepts and Practical Cases.
Jussi S. Jauhiainen, Aurora Toppari. (08/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support, Organizing, Analyzing
Who is the user? Student, Educator, Others
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary, Adult
Why use AI? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Implementation and UseToward Generalized Autonomous Agents: A Neuro-Symbolic AI Framework for Integrating Social and Technical Support in Education
Ryan Hare, Ying Tang. (08/2025). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support, Communicating / Social Tools
Who is the user? Student
Which age? Middle School (6-8), Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Product Development, Technical – ComputationalOpening the 'Can of Worms': A Comparative Case Study of Two ELA Teachers' Formation of AI Literacy Instruction
Christopher Mah, Ibrahim Adisa, Hillary Walker. (08/2025). Journal of Adolescence & Adult Literacy.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Teaching – Professional Learning, Analyzing
Who is the user? Student, Educator
Which age? High School (9-12)
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Implementation and UseDetecting Struggling Student Programmers using Proficiency Taxonomies
Noga Schwartz, Roy Fairstein, Avi Segal, Kobi Gal. (08/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Others
Which age? Post-Secondary
Why use AI? Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Technical – ComputationalExploring AI-Enabled Test Practice, Affect, and Test Outcomes in Language Assessment
Jill Burstein, Ramsey Cardwell, Ping-Lin Chuang, Allison Michalowski, Steven Nydick. (08/2025). arXiv.
What is the application? Teaching – Instructional Materials
Who is the user? Student
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Other Academic
Study design: Quantitative – OthersZPD-SCA: Unveiling the Blind Spots of LLMs in Assessing Students' Cognitive Abilities
Wenhan Dong, Zhen Sun, Yuemeng Zhao, Zifan Peng, Jun Wu, Jingyi Zheng, Yule Liu, Xinlei He*, Yu Wang, Ruiming Wang, Xinyi Huang, Lei Mo*. (08/2025). 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 – Literacy, Outcomes – Differentiation
Study design: Technical – ComputationalGOLDMIND: A Teacher-Centered Knowledge Management System For Higher Education AI Lessons From Iterative Design
Gloria Fern‡ndez-Nieto, Lele Sha, Yuheng Li, Yi-Shan Tsai, Guanliang Chen, Yinwei Wei, Weiqing Wang, Jinchun Wen, Shaveen Singh, Ivan Silva, Yuanfang Li, Dragan Ga_evic, Zachari Swiecki. (08/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Professional Learning, Organizing
Who is the user? Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Product Development, Impact – Quasi–experimental, Quantitative – OthersExplainable AI for Predicting and Understanding Mathematics Achievement: A Cross-National Analysis of PISA 2018
Liu Liu, Dai Rui. (08/2025). arXiv.
What is the application? Analyzing
Who is the user?
Which age? High School (9-12)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical – Computational, Quantitative – OthersFACET: Teacher-Centred LLM-Based Multi-Agent Systems- Towards Personalized Educational Worksheets
Jana Gonnermann-Muller, Jennifer Haase, Konstantin Fackeldey, Sebastian Pokutta. (08/2025). 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 – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersRoboBuddy in the Classroom: Exploring LLM-Powered Social Robots for Storytelling in Learning and Integration Activities
Daniel Tozadore, Nur Ertug, Yasmine Chaker and Mortadha Abderrahim. (08/2025). 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? Efficiency, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Social Emotional
Study design: Descriptive – Implementation and Use, Descriptive – Product Development, Impact – Quasi–experimental
