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Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 31 - 60 of 1023
Student Evaluation Of Repeated AI Feedback Across A Semester Of Writing
Andres Karjus, Janika Leoste, Tiia Õun. (07/2026). arXiv. https://arxiv.org/abs/2607.16115v1
A Tool-Invariant Framework For Teaching And Assessing Computational Methods In The Age Of Agentic AI
Larry Engelhardt. (07/2026). arXiv. https://arxiv.org/abs/2607.15518v1
How Well Does AI-Generated Feedback Work? Intrinsic And Extrinsic Evaluation Across More Than 20,000 Efl Essay Drafts
Steven Coyne, Diana Galvan-Sosa, Ryan Spring, Machi Shimmei, Michael Zock, Keisuke Sakaguchi, Kentaro Inui. (07/2026). arXiv. https://arxiv.org/abs/2607.14591v1
Using AI-Based Learning Assistants In Higher Education: A Large-Scale Descriptive Analysis
Kristina Schaaff, Quintus Stierstorfer, Valerie Hekkel. (07/2026). arXiv. https://arxiv.org/abs/2607.08748v2
Measuring How Students Rely On Generative AI In Academic Writing: Development And Multi-Source Validation Of The Generative AI Reliance Types Scale (Genai-Rts)
Shahin Hossain, Tukhbita Afroz Nawmi. (07/2026). arXiv. https://arxiv.org/abs/2607.14301v1
A Comparative Analysis Of Institutional And Course Generative AI Policies Within Higher Education: Implications For Instruction In Computing Education
Amrita Ganguly, Aditya Johri, Nora McDonald, Areej Ali, Umama Dewan, Aayushi Hingle Collier. (07/2026). arXiv. https://arxiv.org/abs/2607.12296v1
Co-Designing Digital Humans For Online Learning: A Framework For Human-AI Pedagogical Integration
Xiaokang Leil, Ching Christie Pang, Yuyang Jiang, Xin Tong, and Pan Hui. (07/2026). arXiv. https://arxiv.org/abs/2601.17434v2
Generative AI In Higher Education Laboratory Learning: A Qualitative Case Study Of Epistemic Scaffolding And Assessment Boundaries
Matteo Tuveri, Alessandro Riggio. (07/2026). arXiv. https://arxiv.org/abs/2607.11417v1
Uncovering Students' Mental Models Of Generative Artificial Intelligence
Amrita Ganguly, Sai Sharanya Garika, Aditya Johri. (07/2026). arXiv. https://arxiv.org/abs/2607.11692v1
How Annotation Trains Annotators: Competence Development In Social Influence Recognition
Maciej Markiewicz, Beata Bajcar, Wiktoria Mieleszczenko-Kowszewicz, Aleksander Szczƒôsny, Tomasz Adamczyk, Grzegorz Chodak, Karolina Ostrowska, Aleksandra Sawczuk, Jolanta Babiak, Jagoda Szklarczyk, Przemyslaw Kazienko. (07/2026). arXiv. https://arxiv.org/abs/2604.02951v2
Faster Completion, Less Learning: Generative AI Reduced Study Time On Math Problems And The Knowledge They Build
Sina Rismanchian, Hasan Uzun, Jeffrey Matayoshi, Eric Cosyn, Eyad Kurd-Misto. (07/2026). arXiv. https://arxiv.org/abs/2605.21629v3
LLM-Generated Design Problems For Assessing Higher-Order Thinking In Project-Based Learning
Ahmad D. Suleiman, Daqing Hou, Maliha Noushin Raida. (07/2026). arXiv. https://arxiv.org/abs/2607.11032v1
From Chaos To Clarity: A Framework For Program-Level AI Learning Outcomes
Grace Barkhuff, Ian Pruitt, William Gregory Johnson, Rodrigo Borela, Ben Rydal Shapiro, Anu G. Bourgeois. (07/2026). arXiv. https://arxiv.org/abs/2607.12221v1
Learning In Blocks: A Multi Agent Debate Assisted Personalized Adaptive Learning Framework For Language Learning
Nicy Scaria, Silvester John Joseph Kennedy, Deepak Subramani. (07/2026). arXiv. https://arxiv.org/abs/2604.22770v2
Commenting With Copilot: A Taxonomy And Multi-Year Analysis Of Student Code-Generation Specifications
Nasser Giacaman, Valerio Terragni, Paul Denny, Viraj Kumar. (07/2026). arXiv. https://arxiv.org/abs/2607.10674v1
Evidence-Decision-Feedback: Theory-Driven Adaptive Scaffolding For LLM Agents
Clayton Cohn, Siyuan Guo, Surya Rayala, Hanchen David Wang, Naveeduddin Mohammed, Umesh Timalsina, Shruti Jain, Angela Eeds, Menton Deweese, Pamela J. Osborn Popp, Rebekah Stanton, Shakeera Walker, Meiyi Ma, Gautam Biswas. (07/2026). arXiv. https://arxiv.org/abs/2602.01415v5
Learning Behavior Accounts For Background-Related Advantage In AI-Assisted Education
Jingwei Yi, Yueqi Xie, Jiyan He, Rui Ye, Junming Huang, Bin Zhu, Sean Rintel, Yu Xie, Xing Xie, Fangzhao Wu. (07/2026). arXiv. https://arxiv.org/abs/2607.10101v1
Indirect And Direct AI Scaffolding For Computational Problem Posing: A Pilot Experience Report
Shayla Sharmin, Mohammad Fahim Abrar, Mohammad Al-Ratrout, Roghayeh Leila Barmaki. (07/2026). arXiv. https://arxiv.org/abs/2607.09628v1
When LLM Tutoring Responses Work: Evidence From Student Programming Conversations
Mohammad Fahim Abrar, Shyala Sharmin, Roghayeh Leila Barmaki. (07/2026). arXiv. https://arxiv.org/abs/2607.09919v1
"Code Is Cheap. Show Me The Talk.": Lessons From Teaching And Managing AI Coding Tool Usage In A Visualization Course
Zhongzheng Xu, Taehyun Yang, Fumeng Yang. (07/2026). arXiv. https://arxiv.org/abs/2607.09938v1
Knowledge-Based Design Requirements For Generative Social Robots In Higher Education
S. Vonschallen, D. Oberle, T. Schmiedel, F. Eyssel. (07/2026). arXiv. https://arxiv.org/abs/2602.12873v5
Flowcode: An AI-Powered Programming Environment For Scaffolding Iteration In Creative Computing Education
Tiffany Tseng, Liliana Hanem Seoror, Jeevika Adda, Meitalia Factor, Rona Darabi, Kiley R Matschke, Tiffany Fu, Annie Lin, Alekhya Maram, Arya Sinha. (07/2026). arXiv. https://arxiv.org/abs/2607.06721v1
When AI Is Wrong On Purpose: How Students Respond To Buggy Genai Code
Victor-Alexandru Pădurean, Kaitlin Riegel, Alkis Gotovos, Jyotika Mahapatra, Ahana Ghosh, Paul Denny, Juho Leinonen, James Prather, Adish Singla. (07/2026). arXiv. https://arxiv.org/abs/2607.05068v1
AIED's Unfinished Mission: Centering Agency And Motivation In The Age Of Effortless Bypass
H. Chad Lane. (07/2026). arXiv. https://arxiv.org/abs/2607.05557v1
Developing An LLM-Based Feedback System Grounded In Evidence-Centered Design To Support Physics Problem Solving
Holger Maus, Fabian Kieser, Stefan Petersen, Peter Wulff, Paul Tschisgale. (07/2026). arXiv. https://arxiv.org/abs/2512.10785v3
Psychological Determinants Of Academic Integrity In The Use Of Generative AI In Higher Education
Ezgi Dagtekin, Ercan Erkalkan. (07/2026). arXiv. https://arxiv.org/abs/2608.14605v1
Reflective Dialogue Or Prompt Refinement? Effects Of Tutor Scaffolding On Students' ndependent LLM Use For Programming
Jérôme Brender, Laila El-Hamamsy, Kim Uittenhove, Aitor Perez, Patrick Jermann, Francesco Mondada, Engin Bumbacher. (07/2026). arXiv. https://arxiv.org/abs/2607.03303v1
From Answer Generators To Reasoning Facilitators: Designing AI Tutors For Mathematical Reasoning In High-Stakes Environments
Harry Feng, Yuan Tian, Erica Zhao. (07/2026). arXiv. https://arxiv.org/abs/2607.01692v1
