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Outcomes – Other Academic
Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 31 - 60 of 796
"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
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
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
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
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
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
Data Comics For Education: Evaluating Effectiveness, Benefits, And The Ethics Of AI-Assisted Creation
Zirui Shan, Vanessa Echeverria, Yuheng Li, Yi-Shan Tsai, Roberto Martinez-Maldonado. (07/2026). arXiv. https://arxiv.org/abs/2607.02361v1
Deanllm: A Framework For Automated Quality Review Of AI-Generated Feedback
Keyang Qian, Yixin Cheng, Rui Guan, Wei Dai, Flora Ji-Yoon Jin, Kaixun Yang, Sadia Nawaz, Zachari Swiecki, Guanliang Chen, Lixiang Yan, Dragan Gasevic. (07/2026). arXiv. https://arxiv.org/abs/2508.05952v2
The Generative AI Learning Penalty: Evidence from Chinese Secondary Education
David Stromberg, Victor Lei, Yanhui Wu. (07/2026). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6868618
Assessment Design In The Genai Era: The X1-X2-X3 Assessment Pattern For Testing Students' AI Literacy, Learning Outcomes, And Reflection
Riasat Islam, Thomas Roelleke. (07/2026). arXiv. https://arxiv.org/abs/2608.12351v1
Let’s Chat: Leveraging Chatbot Outreach for Improved Course Performance
Katharine E. Meyer, Lindsay C. Page, Catherine Mata, Eric Smith, Brendan Tyler Walsh, Candice L. Fifield, Michelle Tyson, Amy E. Eremionkhale, Michael Evans, Shelby Frost, Eye Eoun Jung. (07/2026). NBER. https://www.nber.org/papers/w35397?utm_campaign=ntwh&utm_medium=email&utm_sourc…
LLM-As-A-Judge Validity In Physics Assessment Depends More On The Task Than The Model
Will Yeadon, Tom Hardy, Paul Mackay, and Elise Agra. (06/2026). arXiv. https://arxiv.org/abs/2603.14732v2
Evaluating Interactivity: Toward Automated Assessment Of AI-Generated Explorable Explanations
Xiaozao Wang, Zhewei Wang, Hongyi Wen. (06/2026). arXiv. https://arxiv.org/abs/2606.31012v1
Teaching Students To Question The Machine: Short-Term Effects Of An AI Literacy Workshop On Middle-School Students' Regulation Of LLM Interaction
Olivier Clerc, Rania Abdelghani, Chloé Desvaux, Eliott Poisson, Pierre-Yves Oudeyer, Helene Sauzeon. (06/2026). arXiv. https://arxiv.org/abs/2604.01955v3
To Tab Or Not To Tab: Measuring Critical Engagement In AI Code Completion Tools Using Behavioral Signals And Attention Checks
Jessica Hutchison, Ian Tyler Applebaum, Kenneth Angelikas, Kush Rakesh Patel, Phuoc Nguyen, Antonio Lazaro, Nicholas Rucinski, Rahad Arman Nabid, Stephen MacNeil. (06/2026). arXiv. https://arxiv.org/abs/2606.30549v1
AI In The Wild: A Large Scale Analysis Of Authentic Interactions Of College Students With Generative AI
Taelin Karidi, Ofra Amir, Ido Roll. (06/2026). arXiv. https://arxiv.org/abs/2606.29442v1
Exploring The Value Of Diverse LLM Explanations In Introductory Programming
Seth Bernstein, Paul Denny, Juho Leinonen, Kush Patel, Rayhona Nasimova, Matt Littlefield, Stephen MacNeil. (06/2026). arXiv. https://arxiv.org/abs/2606.28882v1
Arapai: An Offline-First LLM Architecture For Adaptive Learning In Low-Connectivity Environments
Joseph Walusimbi, Ann Move Oguti, Joshua Benjamin Ssentongo, and Keith Ainebyona. (06/2026). arXiv. https://arxiv.org/abs/2603.03339v7
The Effortless Trap: Productive Struggle, AI, And The Illusion Of Learning
Mario Brcic, Stjepan Frljic. (06/2026). arXiv. https://arxiv.org/abs/2606.26181v1
The Impact Of Generative Artificial Intelligence On Academic Development Of Chinese Students In Humanities And Social Sciences
Lei Fan, Fangxue Liu. (06/2026). arXiv. https://arxiv.org/abs/2606.24104v1
LecturaRaagents: A Multi-Agent Framework For Adaptive Personalized AI-Assisted Learning And Embodied Teaching
Jaward Sesay, Yue Yu, Siwei Dong, Guangyao Chen, Börje F. Karlsson. (06/2026). arXiv. https://arxiv.org/abs/2606.16428v2
AI-Assisted Help-Seeking Trajectories In Programming Education From An Srl-Informed Perspective
Boxuan Ma, Huiyong Li, Gen Li, Li Chen, Atsushi Shimada, Shin'ichi Konomi. (06/2026). arXiv. https://arxiv.org/abs/2606.22809v1
Students' Perception Accuracy Of Partners' AI Use And Its Relation To Collaboration Performance
Laura Graf, Ramona Beinstingel, Stephan Krusche, Oleksandra Poquet. (06/2026). arXiv. https://arxiv.org/abs/2606.23237v1
Supporting Tutors In The Gig Economy With Automated Feedback: A Case Study On Ringle
Yeon Su Park, Sieun Kim, Keighley Overbay, Seoyoung Kim, Sewook Wee, Daho Jung and Juho Kim. (06/2026). arXiv. https://arxiv.org/abs/2606.22609v1
Do Gains From Generative AI-Enabled Adaptive Pretesting Persist? Evidence From A Retention Study
Mahir Akgun, Sacip Toker. (06/2026). arXiv. https://arxiv.org/abs/2606.22328v1
Engagement Intensity As A Learner-Modeling Signal For Adaptive AI Ethics Instruction
Yongkyung Oh, Lynn Talton, Alex Bui. (06/2026). arXiv. https://arxiv.org/abs/2606.18548v1
Analytics For Quality Assurance For Item Pools (Aquap): Monitoring And Maintaining Item Bank Health In AI-Driven Assessment Systems
Alina A. von Davier, Xiaowan Zhang, Yigal Attali, Yena Park, Jacqueline Church, Andrew Runge, Geoff LaFlair, Alexander Tsigler. (06/2026). arXiv. https://arxiv.org/abs/2606.18536v1
Using AI In Engineering Education: A Balancing Act, Driven By Clear Purpose
Olya Kudina. (06/2026). arXiv. https://arxiv.org/abs/2606.16626v1
