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Research synthesis is AI-generated, human reviewed. Updated 09/2025.
Displaying 181 - 210 of 560
Predicting ChatGPT Use in Assignments: Implications for AI-Aware Assessment Design
Surajit Das, Aleksei Eliseev. (08/2025). arXiv. http://arxiv.org/pdf/2508.12013v1
From Misunderstandings To Learning Opportunities: Leveraging Generative AI In Discussion Forums To Support Student Learning
Stanislav Pozdniakov, Jonathan Brazil, Oleksandra Poquet, Stephan Krusche, Santiago Berrezueta-Guzman, Shazia Sadiq, Hassan Khosravi. (08/2025). arXiv. http://arxiv.org/pdf/2508.11150v1
Exploring the Application of Visual Question Answering (VQA) for Classroom Activity Monitoring
Sinh Trong Vu, Hieu Trung Pham, Dung Manh Nguyen, Hieu Minh Hoang, Nhu Hoang Le, Thu Ha Pham, Tai Tan Mai. (08/2025). arXiv. http://arxiv.org/pdf/2507.22369v2
Mathematical Computation and Reasoning Errors by Large Language Models
Liang Zhang, Edith Aurora Graf. (08/2025). arXiv. http://arxiv.org/pdf/2508.09932v2
Listening with Language Models: Using LLMs to Collect and Interpret Classroom Feedback
Sai Siddartha Maram, Ulia Zaman, Magy Seif El-Nasr. (08/2025). arXiv. http://arxiv.org/pdf/2508.11707v1
Next-Gen Education: Enhancing AI for Microlearning
Saha, S., Rahbari, F., Sadique, F., Velamakanni, S. K. C., Farooque, M., Rothwell, W. J.. (08/2025). arXiv. http://arxiv.org/pdf/2508.11704v1
Securing Educational LLMs: A Generalised Taxonomy of Attacks on LLMs and DREAD Risk Assessment
Farzana Zahid, Anjalika Sewwandi, Lee Brandon, Vimal Kumar, Roopak Sinha. (08/2025). arXiv. http://arxiv.org/pdf/2508.08629v1
CODAE: Adapting Large Language Models for Education via Chain-of-Thought Data Augmentation
Shuzhou Yuan, William LaCroix, Hardik Ghoshal, Ercong Nie, Michael FŠrber. (08/2025). arXiv. http://arxiv.org/pdf/2508.08386v1
The Alongside Digital Wellness Program For Youth: Longitudinal Pre-Post Outcomes Study
Katherine Cohen, MA; Andy Rapoport, MPH; Elsa Friis, PhD; Shannon Hill, MPH; Sergey Feldman, PhD; Jessica Schleider, PhD. (08/2025). JMIR Formative Research. https://formative.jmir.org/2025/1/e73180
Assessing the Quality of AI-Generated Exams: A Large-Scale Field Study
Calvin Isley, Joshua Gilbert, Evangelos Kassos, Michaela Kocher, Allen Nie, Emma Brunskill, Ben Domingue, Jake Hofman, Joscha Legewie, Teddy Svoronos, Charlotte Tuminelli, Sharad Goel. (08/2025). arXiv. http://arxiv.org/pdf/2508.08314v1
Towards Reliable Generative AI-Driven Scaffolding: Reducing Hallucinations and Enhancing Quality in Self-Regulated Learning Support
Keyang Qian, Shiqi Liu, Tongguang Li, Mladen Rakovic, Xinyu Li, Rui Guan, Inge Molenaar, Sadia Nawaz, Zachari Swiecki, Lixiang Yan, Dragan Ga_evic. (08/2025). arXiv. http://arxiv.org/pdf/2508.05929v1
Dean of LLM Tutors: Exploring Comprehensive and Automated Evaluation of LLM-generated Educational Feedback via LLM Feedback Evaluators
Keyang Qian, Yixin Cheng, Rui Guan, Wei Dai, Flora Jin, Kaixun Yang, Sadia Nawaz, Zachari Swiecki, Guanliang Chen, Lixiang Yan, Dragan Ga_evic. (08/2025). arXiv. http://arxiv.org/pdf/2508.05952v1
SCALEFeedback: A Large-Scale Dataset of Synthetic Computer Science Assignments for LLM-generated Educational Feedback Research
Keyang Qian, Kaixun Yang, Wei Dai, Flora Jin,Yixin Cheng, Rui Guan, Sadia Nawaz, Zachari Swiecki, Guanliang Chen, Lixiang Yan, Dragan Ga_evic. (08/2025). arXiv. http://arxiv.org/pdf/2508.05953v1
Learning by Teaching: Engaging Students as Instructors of Large Language Models in Computer Science Education
Xinming Yang, Haasil Pujara, Jun Li. (08/2025). arXiv. http://arxiv.org/pdf/2508.05979v1
Between Tool and Trouble: Student Attitudes Toward AI in Programming Education
Sergio Rojas-Galeano, Julian Tejada, Fernando Marmolejo-Ramos. (08/2025). arXiv. http://arxiv.org/pdf/2508.05999v1
From Cognitive Relief to Affective Engagement: An Empirical Comparison of AI Chatbots and Instructional Scaffolding in Physics Education
E. Becker, J. Wunsche, J. M. Veith, J. Schrader, P. Bitzenbauer. (08/2025). arXiv. http://arxiv.org/pdf/2508.06254v1
Beyond Automation: Socratic AI, Epistemic Agency, and the Implications of the Emergence of Orchestrated Multi-Agent Learning Architectures
Peer-Benedikt Degen, Igor Asanov. (08/2025). arXiv. http://arxiv.org/pdf/2508.05116v1
Building Effective Safety Guardrails in AI Education Tools
Hannah-Beth Clark, Laura Benton, Emma Searle, Margaux Dowland, Matthew Gregory, Will Gayne, John Roberts. (08/2025). arXiv. http://arxiv.org/pdf/2508.05360v1
Fine-tuning for Better Few Shot Prompting: An Empirical Comparison for Short Answer Grading
Joel Walsh, Siddarth Mamidanna, Benjamin Nye, Mark Core and Daniel Auerbach. (08/2025). arXiv. http://arxiv.org/pdf/2508.04063v1
InqEduAgent: Adaptive AI Learning Partners with Gaussian Process Augmentation
Tian-Fang Zhao, Wen-Xi Yang, Guan Liu, Liang Yang. (08/2025). arXiv. http://arxiv.org/pdf/2508.03174v2
Personalized Knowledge Transfer Through Generative AI: Contextualizing Learning to Individual Career Goals
Ronja Mehlan, Claudia Hess, Quintus Stierstorfer, Kristina Schaaff. (08/2025). arXiv. http://arxiv.org/pdf/2508.04070v1
Automated Generation Of Curriculum-Aligned Multiple-Choice Questions For Malaysian Secondary Mathematics Using Generative AI
Rohaizah Abdul Wahid, Muhamad Said Nizamuddin Nadim, Suliana Sulaiman, Syahmi Akmal Shaharudin, Muhammad Danial Jupikil, Iqqwan Jasman Su Azlan Su. (08/2025). arXiv. http://arxiv.org/pdf/2508.04442v1
SID: Benchmarking Guided Instruction Capabilities in STEM Education with a Socratic Interdisciplinary Dialogues Dataset
Mei Jiang, Houping Yue, Bingdong Li, Hao Hao, Ying Qian, Bo Jiang, Aimin Zhou. (08/2025). arXiv. http://arxiv.org/pdf/2508.04563v1
When AI Evaluates Its Own Work: Validating Learner-Initiated, AI-Generated Physics Practice Problems
Tobias Geisler, Gerd Kortemeyer. (08/2025). arXiv. http://arxiv.org/pdf/2508.03085v1
When AIs Judge AIs: The Rise of Agent-as-a-Judge Evaluation for LLMs
Fangyi Yu. (08/2025). arXiv. http://arxiv.org/pdf/2508.02994v1
Assessing the Reliability and Validity of Large Language Models for Automated Assessment of Student Essays in Higher Education
Andrea Gaggioli, Giuseppe Casaburi, Leonardo Ercolani, Francesco Collova, Pietro Torre, Fabrizio Davide. (08/2025). arXiv. http://arxiv.org/pdf/2508.02442v1
A Mixed User-Centered Approach to Enable Augmented Intelligence in Intelligent Tutoring Systems: The Case of MathAlde app
Guilherme Guerino, Luiz Rodrigues, Luana Bianchini, Mariana Alves, Marcelo Marinho, Thomaz Veloso, Valmir Macario, Diego Dermeval, Thales Vieira, Ig Bittencourt, Seiji Isotani. (08/2025). arXiv. http://arxiv.org/pdf/2508.00103v2
A Theory of Adaptive Scaffolding for LLM-Based Pedagogical Agents
Clayton Cohn, Surya Rayala, Namrata Srivastava, Joyce Horn Fonteles, Shruti Jain, Xinying Luo, Divya Mereddy, Naveeduddin Mohammed, Gautam Biswas. (08/2025). arXiv. http://arxiv.org/pdf/2508.01503v1
What counts as evidence in AI & ED: Towards Science-for-Policy 3.0
Ilkka Tuomi. (08/2025). European Journal of Education Policy and Practice. https://www.aup-online.com/content/journals/10.5117/EJEP2025.1.001.TUOM
Teaching at Scale: Leveraging AI to Evaluate and Elevate Engineering Education
J.-F. Chamberland, M. Carlisle, A. Jayaraman, K. R. Narayanan, S. Palsole, K. Watson. (08/2025). arXiv. http://arxiv.org/pdf/2508.02731v1
