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Research synthesis is AI-generated, human reviewed. Updated 09/2025.
Displaying 181 - 210 of 676
AutoSCORE: Enhancing Automated Scoring with Multi-Agent Large Language Models via Structured Component Recognition
Yun Wang, Zhaojun Ding, Xuansheng Wu, Siyue Sun, Ninghao Liu, Xiaoming Zhai. (09/2025). arXiv. http://arxiv.org/pdf/2509.21910v1
Comparing RAG and GraphRAG for Page-Level Retrieval Question Answering on Math Textbook
Eason Chen, Chuangji Li, Shizhuo Li, Zimo Xiao, Jionghao Lin, Kenneth R. Koedinger. (09/2025). arXiv. http://arxiv.org/pdf/2509.16780v2
Malaysia's AI-Driven Education Landscape: Policies, Applications, and Comparative Insights For A Digital Future
Fadhilah Jamaluddin, Ahmad Hakiim Jamaluddin, Faridzah Jamaluddin, Faathirah Jamaluddin. (09/2025). arXiv. http://arxiv.org/pdf/2509.21858v1
AI Ethics Education in India: A Syllabus-Level Review of Computing Courses
Anshu M Mittal, PD Parthasarathy, Swaroop Joshi. (09/2025). arXiv. http://arxiv.org/pdf/2509.22329v1
A Meta-Analysis Of LLM Effects On Students Across Qualification, Socialization, And Subjectification
Jiayu Huang, Ruoxin Ritter Wang, Jen-Hao Liu, Boming Xia, Yue Huang, Ruoxi Sun, Jason (Minhui) Xue, Jinan Zou. (09/2025). arXiv. http://arxiv.org/pdf/2509.22725v1
Designing for Novice Debuggers: A Pilot Study on an Al-Assisted Debugging Tool
Oka Kurniawan, Erick Chandra, Christopher M. Poskitt, Yannic Noller, Kenny Tsu Wei Choo, Cyrille Jegourel. (09/2025). arXiv. http://arxiv.org/pdf/2509.21067v1
Analysis of instruction-based LLMs' capabilities to score and judge text-input problems in an academic setting
Valeria Ramirez-Garcia, David de-Fitero-Dominguez, Antonio Garcia-Cabot, Eva Garcia-Lopez. (09/2025). arXiv. http://arxiv.org/pdf/2509.20982v1
Enhancing Python Programming Education with an AI-Powered Code Helper: Design, Implementation, and Impact
Sayed Mahbub Hasan Amiri, Md Mainul Islam. (09/2025). arXiv. http://arxiv.org/pdf/2509.20518v1
The AI Literacy Heptagon: A Structured Approach to AI Literacy in Higher Education
Veronika Hackl, Alexandra Elena Muller, Maximilian Sailer. (09/2025). arXiv. http://arxiv.org/pdf/2509.18900v1
AI Academy: Building Generative AI Literacy in Higher Ed Instructors
Si Chen, Xiuxiu Tang, Alison Cheng, Nitesh Chawla, G. Alex Ambrose, Ronald Metoyer. (09/2025). arXiv. http://arxiv.org/pdf/2509.11999v2
Bringing Pedagogy into Focus: Evaluating Virtual Teaching Assistants' Question-Answering in Asynchronous Learning Environments
Li Siyan, Zhen Xu, Vethavikashini Chithrra Raghuram, Xuanming Zhang, Renzhe Yu, Zhou Yu. (09/2025). arXiv. http://arxiv.org/pdf/2509.17961v1
OnlineMate: An LLM-Based Multi-Agent Companion System for Cognitive Support in Online Learning
Xian Gao, Zongyun Zhang, Ting Liu, Yuzhuo Fu. (09/2025). arXiv. http://arxiv.org/pdf/2509.14803v2
Generative AI alone may not be enough: Evaluating AI Support for Learning Mathematical Proof
Eason Chen, Sophia Judicke, Kayla Beigh, Xinyi Tang, Zimo Xiao, Chuangji Li, Shizhuo Li, Reed Luttmer, Shreya Singh, Maria Yampolsky, Naman Parikh, Yi Zhao, Meiyi Chen, Scarlett Huang, Anishka Mohanty, Gregory Johnson, John Mackey, Jionghao Lin, Ken Koedinger. (09/2025). arXiv. http://arxiv.org/pdf/2509.16778v1
From Service-Oriented Computing to Metaverse Services: A Framework for Inclusive and Immersive Learning for Neurodivergent Students
Rachid Hamadi, Abdelmounaam Rezgui, Ali Darejeh. (09/2025). arXiv. http://arxiv.org/pdf/2509.15545v1
DeliverC: Teaching Pointers through GenAI-Powered Game-Based Learning
Wyatt Petula, Anushcka Joshi, Peggy Tu, Amrutha Somasundar, Suman Saha. (09/2025). arXiv. http://arxiv.org/pdf/2509.14496v1
AI as a teaching tool and learning partner
S Watterson, S Atkinson, E Murray, A McDowell. (09/2025). arXiv. http://arxiv.org/pdf/2509.13899v1
AI-driven formative assessment and adaptive learning in data-science education: Evaluating an LLM-powered virtual teaching assistant
Fadjimata I.Anaroua, Qing Li, Yan Tang, Hong P.Liu. (09/2025). arXiv. http://arxiv.org/pdf/2509.20369v1
Perspectives and potential issues in using artificial intelligence for computer science education
Juho Vepsalainen, Petri Juntunen. (09/2025). arXiv. http://arxiv.org/pdf/2509.13730v1
Gen AI In Proof-Based Math Courses: A Pilot Study
Hannah Klawa, Shraddha Rajpal, Cigole Thomas. (09/2025). arXiv. http://arxiv.org/pdf/2509.13570v1
Exploring Conversational Design Choices in LLMs for Pedagogical Purposes: Socratic and Narrative Approaches for Improving Instructor's Teaching Practice
SI CHEN, ISABEL R. MOLNAR, PEIYU LI, ADAM ACUNIN, TING HUA, ALEX AMBROSE, NITESH V. CHAWLA, RONALD METOYER. (09/2025). arXiv. http://arxiv.org/pdf/2509.12107v1
A GPU-Accelerated RAG-Based Telegram Assistant for Supporting Parallel Processing Students
Guy Tel-Zur. (09/2025). arXiv. http://arxiv.org/pdf/2509.11947v1
Prompting the Professoriate: A Qualitative Study of Instructor Perspectives on LLMs in Data Science Education*
Ana Elisa Lopez-Miranda, Tiffany Timbers, Rohan Alexander. (09/2025). arXiv. http://arxiv.org/pdf/2509.12283v1
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. http://arxiv.org/pdf/2509.10647v1
Machine Unlearning for Responsible and Adaptive AI in Education
Betty Mayeku, Sandra Hummel, Parisa Memarmoshrefi. (09/2025). arXiv. http://arxiv.org/pdf/2509.10590v1
Automated Classification of Tutors' Dialogue Acts Using Generative AI: A Case Study Using the CIMA Corpus
Liqun He, Jiaqi Xu. (09/2025). arXiv. http://arxiv.org/pdf/2509.09125v1
Aesthetic 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. http://arxiv.org/pdf/2509.10576v1
Deploying 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. http://arxiv.org/pdf/2509.08950v1
Automatic Detection of Inauthentic Templated Responses in English Language Assessments
Yashad Samant, Lee Becker, Scott Hellman, Bradley Behan, Sarah Hughes, Joshua Southerland. (09/2025). arXiv. http://arxiv.org/pdf/2509.08355v1
