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Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 871 - 900 of 1118
Autograding Mathematical Induction Proofs with Natural Language Processing
Chenyan Zhao, Mariana Silva, Seth Poulsen. (02/2025). arXiv. http://arxiv.org/pdf/2406.10268v2
SocratiQ: 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. https://arxiv.org/pdf/2502.00341
One Size doesn't Fit All: A Personalized Conversational Tutoring Agent for Mathematics Instruction
Ben Liu, Jihai Zhang, Fangquan Lin, Xu Jia, Min Peng. (02/2025). arXiv. https://doi.org/10.48550/arXiv.2502.12633
Understanding Generative AI Risks for Youth: A Taxonomy Based on Empirical Data
Yaman Yu, Yiren Liu, Jacky Zhang, Yun Huang, Yang Wang. (02/2025). arXiv. https://www.arxiv.org/abs/2502.16383
The 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. http://arxiv.org/pdf/2409.11261v4
The Responsible Development of Automated Student Feedback with Generative AI
Euan D Lindsay, Mike Zhang, Aditya Johri, Johannes Bjerva. (02/2025). arXiv. http://arxiv.org/pdf/2308.15334v3
The Imitation Game for Educational AI
Shashank Sonkar, Naiming Liu, Xinghe Chen, Richard G. Baraniuk. (02/2025). arXiv. https://arxiv.org/pdf/2502.15127
Protecting Human Cognition in the Age of Al
Anjali Singh, Karan Taneja, Zhitong Guan, Avijit Ghosh. (02/2025). arXiv. https://arxiv.org/pdf/2502.12447
Position: 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. https://arxiv.org/pdf/2502.05467
The 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. http://arxiv.org/pdf/2412.00691v2
The effectiveness of ChatGPT in assisting high school students in programming learning: evidence from a quasi-experimental research
Tzu-Chi Yang, Yi-Chuan Hsu, Jiun-Yu Wu. (01/2025). Interactive Learning Environments. https://www.tandfonline.com/doi/full/10.1080/10494820.2025.2450659?src=#:~:text…
IntelliChain: 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. https://arxiv.org/pdf/2502.00010
Personalized Parsons Puzzles as Scaffolding Enhance Practice Engagement Over Just Showing LLM-Powered Solutions
Xinying Hou, Zihan Wu, Xu Wang, Barbara J. Ericson. (01/2025). arXiv. http://arxiv.org/pdf/2501.09210v1
iLLuMinaTE: 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. http://arxiv.org/pdf/2409.08027v2
Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning
David Baidoo-Anu, Leticia Owusu Ansah. (01/2025). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4337484
TutorLLM: 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. https://arxiv.org/pdf/2502.15709
A Review of Artificial Intelligence Interventions for Students with Autism Spectrum Disorder
Sofia Kotsi, Spyridoula Handrinou, Georgia Iatraki, Spyridon-Georgios Soulis. (01/2025). MDPI. https://www.mdpi.com/2673-7272/5/1/7
Debugging Without Error Messages: How LLM Prompting Strategy Affects Programming Error Explanation Effectiveness
Audrey Salmon, Katie Hammer, Eddie Antonio Santos, Brett A. Becker. (01/2025). arXiv. http://arxiv.org/pdf/2501.05706v1
Predicting Long-Term Student Outcomes from Short-Term EdTech Log Data
Ge Gao, Amelia Leon, Andrea Jetten, Jasmine Turner, Husni Almoubayyed, Stephen Fancsali, Emma Brunskill. (01/2025). arXiv. https://arxiv.org/abs/2412.15473
Exploring 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. http://arxiv.org/pdf/2309.10444v5
Generative AI in Education: From Foundational Insights to the Socratic Playground for Learning
Xiangen Hu, Sheng Xu, Richard Tong, & Art Graesser. (01/2025). arXiv. http://arxiv.org/pdf/2501.06682v1
Revolutionizing Undergraduate Learning: CourseGPT and Its Generative AI Advancements
Ahmad M. Nazar, Mohamed Y. Selim, Ashraf Gaffar, Shakil Ahmed. (12/2024). arXiv. https://arxiv.org/pdf/2407.18310
AI in Education: Rationale, Principles, and Instructional Implications
Eyvind Elstad. (12/2024). arXiv. http://arxiv.org/pdf/2412.12116v1
The Evolving Usage of GenAI by Computing Students
Irene Hou, Hannah Vy Nguyen, Owen Man, Stephen MacNeil. (12/2024). arXiv. https://arxiv.org/pdf/2412.16453
"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. https://arxiv.org/pdf/2412.17243
Scaffold or Crutch? Examining College Students' Use and Views of Generative AI Tools for STEM Education
Karen D. Wang, Zhangyang Wu, L'Nard Tufts II, Carl Wieman, Shima Salehi, Nick Haber. (12/2024). arXiv. https://arxiv.org/pdf/2412.02653
Generative AI as a lab partner: a case study
Sebastian Kilde-Westberg, Andreas Johansson, Jonas Enger. (12/2024). arXiv. https://arxiv.org/pdf/2412.11300
"Give me the code" - Log Analysis of First-Year CS Students' Interactions With GPT
Pedro Alves, Bruno Pereira Cipriano. (12/2024). arXiv. http://arxiv.org/pdf/2411.17855v2
Who is Helping Whom? Student Concerns about AI-Teacher Collaboration in Higher Education Classrooms
Bingyi Han, Simon Coghlan, George Buchanan, Dana McKay. (12/2024). arXiv. https://arxiv.org/pdf/2412.14469
