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Teaching – Assessment and Feedback
Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 181 - 210 of 795
Beyond The AI Tutor: Social Learning With LLM Agents
Harsh Kumar, Jonathan Vincentius, Zi Kang (Jace) Mu, Ashton Anderson. (04/2026). arXiv. https://arxiv.org/abs/2604.02677v1
Grounding AI-in-Education Development in Teachers' Voices: Findings from a National Survey in Indonesia
Nurul Aisyah, Muhammad Dehan Al Kautsar, Arif Hidayat, and Fajri Koto. (04/2026). arXiv. https://arxiv.org/abs/2604.01630v1
How Motivation Relates To Generative AI Use: A Large-Scale Survey Of Mexican High School Students
Echo Zexuan Pan, Danny Glick, Ying Xu. (04/2026). arXiv. https://arxiv.org/abs/2603.19263v2
Benchmarking Educational Llms With Analytics: A Case Study On Gender Bias In Feedback
Yishan Du, Conrad Borchers, Mutlu Cukurova. (04/2026). arXiv. https://arxiv.org/abs/2511.08225v2
Evaluating Vision-Language And Large Language Models For Automated Student Assessment In Indonesian Classrooms
Nurul Aisyah, Muhammad Dehan Al Kautsar, Arif Hidayat, Raqib Chowdhury, and Fajri Koto. (04/2026). arXiv. https://arxiv.org/abs/2506.04822v3
Evaluating A Data-Driven Redesign Process For Intelligent Tutoring Systems
Qianru Lyu, Conrad Borchers, Meng Xia, Karen Xiao, Paulo F. Carvalho, Kenneth R. Koedinger, and Vincent Aleven. (03/2026). arXiv. https://arxiv.org/abs/2603.29094v1
Practitioner Voices Summit: How Teachers Evaluate AI Tools Through Deliberative Sensemaking
Dorottya Demszky, Christopher Mah, Helen Higgins. (03/2026). arXiv. https://arxiv.org/abs/2603.22588v3
Evaluating LLMs For Answering Student Questions In Introductory Programming Courses
Thomas Van Mullem, Bart Mesuere, Peter Dawyndt. (03/2026). arXiv. https://arxiv.org/abs/2603.28295v1
Understanding Teacher Revisions Of Large Language Model-Generated Feedback
Conrad Borchers, Luiz Rodrigues, Newarney Torrezao da Costa, Cleon Xavier, Rafael Ferreira Mello. (03/2026). arXiv. https://arxiv.org/abs/2603.27806v1
Learning To Program Alongside AI: Critical Thinking, AI Ethics, And Gendered Patterns Of German Secondary School Students
Isabella Graßl. (03/2026). arXiv. https://arxiv.org/abs/2603.24197v2
Artificial Intelligence In Secondary Education: Educational Affordances And Constraints Of ChatGPT-4O Use
Tryfon Sivenas, Panagiota Maragkaki. (03/2026). arXiv. https://arxiv.org/abs/2602.13717v2
Exploring The Integration Of Extended Reality And Artificial Intelligence (AI) For Remote STEM Education And Assessment
Shadeeb Hossain, Neda Adib, Natalie Sommer. (03/2026). arXiv. https://arxiv.org/abs/2509.03812v2
Beyond Detection: Rethinking Education In The Age Of AI-Writing
Maria Marina, Alexander Panchenko, and Vasily Konovalov. (03/2026). arXiv. https://arxiv.org/abs/2603.25329v1
To Use Or Not To Use: Investigating Student Perceptions Of Faculty Generative AI Usage In Higher Education
Jie Gao, Jiayi Zhang, Dan Chen. (03/2026). arXiv. https://arxiv.org/abs/2603.25932v1
The Landscape Of AI In Science Education: What Is Changing And How To Respond
Xiaoming Zhai, Kent Crippen. (03/2026). arXiv. https://arxiv.org/abs/2602.18469v2
An Experimental Evaluation Of An AI-Powered Interactive Learning Platform
Courtney Heldreth, Diana Akrong, Laura M. Vardoulakis, Nicole E. Miller, Yael Haramaty, Lidan Hackmon, Lior Belinsky, Abraham Ortiz Tapia, Lucy Tootill, Scott Siebert. (03/2026). arXiv. https://arxiv.org/abs/2509.18664v2
Evaluating Adaptive And Generative AI-Based Feedback And Recommendations In A Knowledge-Graph-Integrated Programming Learning System
Lalita Na Nongkhai, Jingyun Wang, Adam Wynn, Takahiko Mendori. (03/2026). arXiv. https://arxiv.org/abs/2603.24940v1
Three Years With Classroom AI In Introductory Programming: Shifts In Student Awareness, Interaction, And Performance
Boxuan Ma, Huiyong Li, Gen Li, Li Chen, Cheng Tang, Atsushi Shimada, and Shin'ichi Konomi. (03/2026). arXiv. https://arxiv.org/abs/2603.22672v1
Beyond Accuracy: Towards A Robust Evaluation Methodology For AI Systems For Language Education
James Edgell, Wm. Matthew Kennedy, Isaac Pattis, Ben Knight, Danielle Carvalho, Elizabeth Wonnacott. (03/2026). arXiv. https://arxiv.org/abs/2603.20088v1
AI In Work-Based Learning: Understanding The Purposes And Effects Of Intelligent Tools Among Student Interns
John Paul P. Miranda, Rhiziel P. Manalese, Sheila M. Geronimo, Vernon Grace M. Maniago, Charlie K. Padilla, Aileen P. De Leon, Santa L. Merle, Mark Anthony A. Castro. (03/2026). arXiv. https://arxiv.org/abs/2603.28786v1
Explainability And Certification Of AI-Generated Educational Assessments
Antoun Yaacoub, Zainab Assaghir, Anuradha Kar. (03/2026). arXiv. https://arxiv.org/abs/2604.09622v1
Guide: Genai Units In Digital Design Education
Weihua Xiao, Jason Blocklove, Matthew DeLorenzo, Johann Knechtel, Ozgur Sinanoglu, Kanad Basu, Jeyavijayan Rajendran, Siddharth Garg, Ramesh Karri. (03/2026). arXiv. https://arxiv.org/abs/2603.17296v1
Practicing With Language Models Cultivates Human Empathic Communication
Aakriti Kumar, Nalin Poungpeth, Diyi Yang, Bruce Lambert, Matthew Groh. (03/2026). arXiv. https://arxiv.org/pdf/2603.15245
Criterion-Referenceability Determines LLM-As-A-Judge Validity Across Physics Assessment Formats
Will Yeadon, Tom Hardy, Paul Mackay, and Elise Agra. (03/2026). arXiv. https://arxiv.org/abs/2603.14732v1
Effective Personalized AI Tutors Via Llm-Guided Reinforcement Learning
Angel Tsai-Hsuan Chung, Botong Zhang, Ling-Chieh Kung, Hamsa Bastani, Osbert Bastani. (03/2026). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6423358
Survey Of Computerized Adaptive Testing: A Machine Learning Perspective
Yan Zhuang, Qi Liu, Haoyang Bi, Zhenya Huang, Weizhe Huang, Jiatong Li, Junhao Yu, Zirui Liu, Zirui Hu, Yuting Hong, Zachary A. Pardos, Haiping Ma, Mengxiao Zhu, Shijin Wang, Enhong Chen. (03/2026). arXiv. https://arxiv.org/abs/2404.00712v4
The Rigid Framework: Research-Integrated, Generative AI-Mediated Instructional Design
Yerin Kwak, Zachary A. Pardos. (03/2026). arXiv. https://arxiv.org/abs/2603.12781v1
Scaling Laws For Educational AI Agents
Mengsong Wu, Hao Hao, Shuzhen Bi, Keqian Li, Wentao Liu, Siyu Song, Hongbo Zhao, and Aimin Zhou. (03/2026). arXiv. https://arxiv.org/abs/2603.11709v1
The Future Of Feedback: How Can AI Help Transform Feedback To Be More Engaging, Effective, And Scalable?
Jennifer Meyer, Olaf Kuller, Thorben Jansen, Johanna Fleckenstein, Michael W. Asher, Sarah Bichler, Laura Brandl, Jasmin Breitwieser, Kai S. Cortina, Mutlu Cukurova, Martin Daumiller, Hannah Deininger, Frank Fischer, Dragan Gasevic, Jeanine Grutter, Anna Hilz, Ioana Jivet, Jelena Jovanovic, Rene F. Kizilcec, Livia Kuklick, Marlit Annalena Lindner, Anastasiya Lipnevich, Ute Mertens, Detmar Meurers, Kou Murayama, Tanya Nazaretsky, Knut Neumann, Ernesto Panadero, Maciej Pankiewicz, Zachary A. Pardos, Chris Piech, Hannah Punjer, Nikol Rummel, Marlene Steinbach, Olga Viberg, Naomi Winstone. (03/2026). arXiv. https://arxiv.org/abs/2603.12463v1
