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Outcomes – Differentiation
Research synthesis is AI-generated, human reviewed. Updated 09/2025.
Displaying 121 - 150 of 519
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
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
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
An Outcome-Based Educational Recommender System
Nursultan Askarbekuly, Timur Fayzrakhmanov, Sladjan Babarogic, Ivan Lukovic. (09/2025). arXiv. http://arxiv.org/pdf/2509.18186v1
Comparative Analysis of STEM and non-STEM Teachers' Needs for Integrating AI into Educational Environments
Bahare Riahi, Veronica Catete. (09/2025). arXiv. http://arxiv.org/pdf/2509.16276v1
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-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
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
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
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
Bridging Cultural Distance Between Models Default and Local Classroom Demands: How Global Teachers Adopt GenAI to Support Everyday Teaching Practices
Ruiwei Xiao, Qing Xiao, Xinying Hou, Hanqi Jane Li, Phenyo Phemelo Moletsane, Hong Shen, John Stamper. (09/2025). arXiv. http://arxiv.org/pdf/2509.10780v1
Do Teachers Dream of GenAI Widening Educational (In)equality? Envisioning the Future of K-12 GenAI Education from Global Teachers' Perspectives
Ruiwei Xiao, Qing Xiao, Xinying Hou, Phenyo Phemelo Moletsane, Hanqi Jane Li, Hong Shen, John Stamper. (09/2025). arXiv. http://arxiv.org/pdf/2509.10782v1
Emerging Patterns of GenAI Use in K-12 Science and Mathematics Education
Lief Esbenshade, Shawon Sarkar, Drew Nucci, Ann Edwards, Sarah Nielsen, Joshua M. Rosenberg, Alex Liu, Zewei (Victor) Tian, Min Sun, Zachary Zhang, Thomas Han, Yulia Lapicus, Kevin He. (09/2025). arXiv. http://arxiv.org/pdf/2509.10747v1
GenAI Voice Mode in Programming Education
Sven Jacobs, Natalie Kiesler. (09/2025). arXiv. http://arxiv.org/pdf/2509.10596v1
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
Feedback 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. http://arxiv.org/pdf/2509.08516v1
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
The ends of tests: Possibilities for transformative assessment and learning with generative AI
Bill Cope, Mary Kalantzis, Akash Kumar Saini. (09/2025). Unesco. https://www.unesco.org/en/articles/ai-and-future-education-disruptions-dilemmas…
Skill-based Explanations for Serendipitous Course Recommendation
Hung Chau, Run Yu, Zachary Pardos, Peter Brusilovsky. (08/2025). arXiv. http://arxiv.org/pdf/2508.19569v1
Prompting 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. http://arxiv.org/pdf/2508.20217v1
Automatic 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. http://arxiv.org/pdf/2508.19475v1
MAB Optimizer for Estimating Math Question Difficulty via Inverse CV without NLP
Surajit Das, Gourav Roy, Aleksei Eliseev, Ram Kumar Rajendran. (08/2025). arXiv. http://arxiv.org/pdf/2508.19014v1
Who 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. http://arxiv.org/pdf/2508.18925v1
Exploring Generative Artificial Intelligence (GenAI) and AI Agents in Research and Teaching - Concepts and Practical Cases.
Jussi S. Jauhiainen, Aurora Toppari. (08/2025). arXiv. http://arxiv.org/pdf/2508.16701v2
Toward Generalized Autonomous Agents: A Neuro-Symbolic AI Framework for Integrating Social and Technical Support in Education
Ryan Hare, Ying Tang. (08/2025). arXiv. http://arxiv.org/pdf/2508.18406v1
Detecting Struggling Student Programmers using Proficiency Taxonomies
Noga Schwartz, Roy Fairstein, Avi Segal, Kobi Gal. (08/2025). arXiv. http://arxiv.org/pdf/2508.17353v1
ZPD-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. http://arxiv.org/pdf/2508.14377v2
AI-Supported Mini-Labs: Combining Smartphone-Based Experiments and Multimodal AI
Jochen Kuhn, David J. Rakestraw, Stefan Stefan KŸchemann, Patrik Vogt. (08/2025). arXiv. http://arxiv.org/pdf/2508.16320v1
