Outcomes – Other Academic
Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 451 - 480 of 661
"Don't Forget the Teachers": Towards an Educator-Centered Understanding of Harms from Large Language Models in Education
Emma Harvey, Allison Koenecke, RenŽ F. Kizilcec. (02/2025). arXiv. https://arxiv.org/pdf/2502.14592v1
Unveiling Scoring Processes: Dissecting the Differences between LLMs and Human Graders in Automatic Scoring
Xuansheng Wu, Padmaja Pravin Saraf, Gyeonggeon Lee, Ehsan Latif, Ninghao Liu, Xiaoming Zhai. (02/2025). arXiv. http://arxiv.org/pdf/2407.18328v2
SocratiQ: A Generative AI-Powered Learning Companion for Personalized Education and Broader Accessibility
Jason Jabbour, Kai Kleinbard, Olivia Miller, Robert Haussman, Vijay Janapa Reddi. (02/2025). arXiv. https://arxiv.org/pdf/2502.00341
The Imitation Game for Educational AI
Shashank Sonkar, Naiming Liu, Xinghe Chen, Richard G. Baraniuk. (02/2025). arXiv. https://arxiv.org/pdf/2502.15127
Position: LLMs Can be Good Tutors in Foreign Language Education
Jingheng Ye, Shen Wang, Deqing Zhou, Yibo Yan, Kun Wang, Hai-Tao Zheng, Zenglin Xu, Irwin King, Philip S. Yu, Qingsong Wen. (02/2025). arXiv. https://arxiv.org/pdf/2502.05467
MindCraft: Revolutionizing Education through AI-Powered Personalized Learning and Mentorship for Rural India
Arihant Bardia, Aayush Agrawal. (02/2025). arXiv. https://www.arxiv.org/abs/2502.05826
Towards Adaptive Feedback with AI: Comparing the Feedback Quality of LLMs and Teachers on Experimentation Protocols
Kathrin Sessler, Arne Bewersdorff, Claudia Nerdel, Enkelejda Kasneci. (02/2025). arXiv. https://arxiv.org/pdf/2502.12842
VTutor: An Open-Source SDK for Generative AI-Powered Animated Pedagogical Agents with Multi-Media Output
Eason Chen, Chenyu Lin, Xinyi Tang, Aprille Xi, Canwen Wang, Jionghao Lin, Kenneth R. Koedinger. (02/2025). arXiv. https://arxiv.org/pdf/2502.04103
Understanding Generative AI Risks for Youth: A Taxonomy Based on Empirical Data
Yaman Yu, Yiren Liu, Jacky Zhang, Yun Huang, Yang Wang. (02/2025). arXiv. https://www.arxiv.org/abs/2502.16383
Auto-Evaluation: A Critical Measure in Driving Improvements in Quality and Safety of AI-Generated Lesson Resources
Hannah-Beth Clark, Margaux Dowland, Laura Benton, Reka Budai, Ibrahim Kaan Keskin, Emma Searle, Matthew Gregory, Mark Hodierne, William Gayne, John Roberts. (01/2025). arXiv. https://arxiv.org/pdf/2502.10410
The effectiveness of ChatGPT in assisting high school students in programming learning: evidence from a quasi-experimental research
Tzu-Chi Yang, Yi-Chuan Hsu, Jiun-Yu Wu. (01/2025). Interactive Learning Environments. https://www.tandfonline.com/doi/full/10.1080/10494820.2025.2450659?src=#:~:text…
Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning
David Baidoo-Anu, Leticia Owusu Ansah. (01/2025). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4337484
TutorLLM: Customizing Learning Recommendations with Knowledge Tracing and Retrieval-Augmented Generation
Zhaoxing LI, Vahid Yazdanpanah, Jindi Wang, Wen Gu, Lei Shi, Alexandra I. Cristea, Sarah Kiden, Sebastian Stein. (01/2025). arXiv. https://arxiv.org/pdf/2502.15709
A Novel Approach to Scalable and Automatic Topic-Controlled Question Generation in Education
Ziqing Li, Mutlu Cukurova, Sahan Bulathwela. (01/2025). arXiv. http://arxiv.org/pdf/2501.05220v1
A Zero-Shot LLM Framework for Automatic Assignment Grading in Higher Education
Calvin Yeung, Jeff Yu, King Chau Cheung, Tat Wing Wong, Chun Man Chan, Kin Chi Wong, Keisuke Fujii. (01/2025). arXiv. https://arxiv.org/pdf/2501.14305
Fine-tuning ChatGPT for Automatic Scoring of Written Scientific Explanations in Chinese
Jie Yang, Ehsan Latif, Yuze He, Xiaoming Zhai. (01/2025). arXiv. http://arxiv.org/pdf/2501.06704v1
Bridging the Early Science Gap with Artificial Intelligence Evaluating Large Language Models as Tools for Early Childhood Science Education
Annika Bush, Amin Alibakhshi. (01/2025). arXiv. http://arxiv.org/pdf/2501.01192v2
Personalized Parsons Puzzles as Scaffolding Enhance Practice Engagement Over Just Showing LLM-Powered Solutions
Xinying Hou, Zihan Wu, Xu Wang, Barbara J. Ericson. (01/2025). arXiv. http://arxiv.org/pdf/2501.09210v1
Debugging Without Error Messages: How LLM Prompting Strategy Affects Programming Error Explanation Effectiveness
Audrey Salmon, Katie Hammer, Eddie Antonio Santos, Brett A. Becker. (01/2025). arXiv. http://arxiv.org/pdf/2501.05706v1
Enhancing textual textbook question answering with large language models and retrieval augmented generation
Hessa A. Alawwad, Areej Alhothali, Usman Naseem, Ali Alkhathlan, Amani Jamal. (01/2025). arXiv. http://arxiv.org/pdf/2402.05128v3
iLLuMinaTE: An LLM-XAI Framework Leveraging Social Science Explanation Theories Towards Actionable Student Performance Feedback
Vinitra Swamy, Davide Romano, Bhargav Srinivasa Desikan, Oana-Maria Camburu, Tanja Kaser. (01/2025). arXiv. http://arxiv.org/pdf/2409.08027v2
Evaluating GenAI for Simplifying Texts for Education: Improving Accuracy and Consistency for Enhanced Readability
Stephanie L. Day, Jacapo Cirica, Steven R. Clapp, Veronika Penkova, Amy E. Giroux, Abbey Banta, Catherine Bordeau, Poojitha Mutteneni, Ben D. Sawyer. (01/2025). arXiv. http://arxiv.org/pdf/2501.09158v1
Exploring Iterative Enhancement for Improving Learnersourced Multiple-Choice Question Explanations with Large Language Models
Qiming Bao, Juho Leinonen, Alex Yuxuan Peng, Wanjun Zhong, Ga‘l Gendron, Tim Pistotti, Alice Huang, Paul Denny, Michael Witbrock, Jiamou Liu. (01/2025). arXiv. http://arxiv.org/pdf/2309.10444v5
Generative AI in Education: From Foundational Insights to the Socratic Playground for Learning
Xiangen Hu, Sheng Xu, Richard Tong, & Art Graesser. (01/2025). arXiv. http://arxiv.org/pdf/2501.06682v1
Generating Plausible Distractors for Multiple-Choice Questions via Student Choice Prediction
Yooseop Lee, Suin Kim, Yohan Jo. (01/2025). arXiv. https://arxiv.org/pdf/2501.13125
Learning-By-Teaching With ChatGPT: The Effect Of Teachable ChatGPT Agent On Programming Education
Angxuan Chen, Yuang Wei, Huixiao Le, Yan Zhang. (12/2024). arXiv. https://arxiv.org/pdf/2412.15226
AI in Education: Rationale, Principles, and Instructional Implications
Eyvind Elstad. (12/2024). arXiv. http://arxiv.org/pdf/2412.12116v1
Who is Helping Whom? Student Concerns about AI-Teacher Collaboration in Higher Education Classrooms
Bingyi Han, Simon Coghlan, George Buchanan, Dana McKay. (12/2024). arXiv. https://arxiv.org/pdf/2412.14469
A Self-Efficacy Theory-based Study on the Teachers' Readiness to Teach Artificial Intelligence in Public Schools in Sri Lanka
Chathura Rajapakse,Wathsala Ariyarathna,Shanmugalingam Selvakan. (12/2024). arXiv. https://arxiv.org/pdf/2412.19425
ActiveAI: Enabling K-12 AI Literacy Education & Analytics at Scale
Ruiwei Xiao, Ying-Jui Tseng, Hanqi Li, Hsuan Nieu, Guanze Liao, John Stamper, Kenneth R. Koedinger. (12/2024). arXiv. https://arxiv.org/pdf/2412.14200
