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Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 751 - 780 of 898
To accept or not to accept? An IRT-TOE Framework to Understand Educators' Resistance to Generative AI in Higher Education
Jan-Erik Kalmus, Anastasija Nikiforova. (07/2024). arXiv. https://arxiv.org/pdf/2407.20130
Explainable Artificial Intelligence for Quantifying Interfering and High-Risk Behaviors in Autism Spectrum Disorder in a Real-World Classroom Environment Using Privacy-Preserving Video Analysis
Barun Das, Conor Anderson, Tania Villavicencio, Johanna Lantz, Jenny Foster, Theresa Hamlin, Ali Bahrami Rad, Gari D. Clifford, Hyeokhyen Kwon. (07/2024). arXiv. http://arxiv.org/pdf/2407.21691v1
Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model Tutors
Nico Daheim, Jakub Macina, Manu Kapur, Iryna Gurevych, Mrinmaya Sachan. (07/2024). arXiv. http://arxiv.org/pdf/2407.09136v1
Evaluating Contextually Personalized Programming Exercises Created with Generative AI
Evanfiya Logacheva, Arto Hellas, James Prather, Sami Sarsa, Juho Leinonen. (06/2024). arXiv. http://arxiv.org/pdf/2407.11994v1
Generative Al and Digital Neocolonialism in Global Education: Towards an Equitable Framework
Matthew Nyaaba, Alyson Wright, Gyu Lim Choi. (06/2024). arXiv. http://arxiv.org/pdf/2406.02966v3
AI AGENTS AND EDUCATION: SIMULATED PRACTICE AT SCALE
Ethan Mollick, Lilach Mollick, Natalie Bach, LJ Ciccarelli, Ben Przystanski, Daniel Ravipinto. (06/2024). arXiv. https://arxiv.org/pdf/2407.12796
Beyond Answers: Large Language Model-Powered Tutoring System in Physics Education for Deep Learning and Precise Understanding
Zhoumingju Jiang, Mengjun Jiang. (06/2024). arXiv. http://arxiv.org/pdf/2406.10934v1
How Effective is GPT-4 Turbo in Generating School-Level Questions from Textbooks Based on Bloom's Revised Taxonomy?
Subhankar Maity, Aniket Deroy, Sudeshna Sarkar. (06/2024). arXiv. http://arxiv.org/pdf/2406.15211v1
Responsible Adoption of Generative AI in Higher Education: Developing a “Points to Consider” Approach Based on Faculty Perspectives
Ravit Dotan, Lisa S. Parker, John G. Radzilowicz. (06/2024). arXiv. https://arxiv.org/pdf/2406.01930
Human-AI Collaborative Essay Scoring: A Dual-Process Framework with LLMs
Changrong Xiao, Wenxing Ma, Qingping Song, Sean Xin Xu, Kunpeng Zhang, Yufang Wang, Qi Fu. (06/2024). arXiv. https://arxiv.org/pdf/2401.06431
The Rise of Artificial Intelligence in Educational Measurement: Opportunities and Ethical Challenges
Okan Bulut, Maggie Beiting-Parrish, Jodi M. Casabianca, Sharon C. Slater, Hong Jiao, Dan Song, Christopher Ormerod, Deborah Gbemisola Fabiyi, Rodica Ivan, Cole Walsh, Oscar Rios, Joshua Wilson, Seyma N. Yildirim-Erbasli, Tarid Wongvorachan, Joyce Xinle Liu, Bin Tan, Polina Morilova. (06/2024). arXiv. http://arxiv.org/pdf/2406.18900v1
Harvard Undergraduate Survey on Generative AI
Shikoh Hirabayashi, Rishab Jain, Nikola Jurkovic, Gabriel Wu. (06/2024). arXiv. https://arxiv.org/pdf/2406.00833
Systematic review of research on artificial intelligence in K-12 education (2017-2022)
Florence Martin, Min Zhuang, Darlene Schaefer. (06/2024). ScienceDirect. https://www.sciencedirect.com/science/article/pii/S2666920X23000747
Using Llms To Bring Evidence-Based Feedback Into The Classroom: AI-Generated Feedback Increases Secondary Students' Text Revision, Motivation, And Positive Emotions
Jennifer Meyer, Thorben Jansen, Ronja Schiller, Lucas W. Liebenow, Marlene Steinbach, Andrea Horbach, Johanna Fleckenstein. (06/2024). Computers and Education: Artificial Intelligence. https://www.sciencedirect.com/science/article/pii/S2666920X23000784
What Conversational AI Can (and Can't) Tell Us About Peer Interaction in Higher Education
Vanessa Peters, Emily Pressler, Julie Neisler, Barbara Means. (06/2024). ISLS Repository. https://repository.isls.org/handle/1/11077
Knowledge Distillation of LLMs for Automatic Scoring of Science Assessments
Ehsan Latif, Luyang Fang, Ping Ma, Xiaoming Zhai. (06/2024). arXiv. http://arxiv.org/pdf/2312.15842v3
A GPT-based Code Review System for Programming Language Learning
Lee Dong-Kyu. (06/2024). arXiv. http://arxiv.org/pdf/2407.04722v1
Bringing Generative AI to Adaptive Learning in Education
Hang Li, Tianlong Xu, Chaoli Zhang, Eason Chen, Jing Liang, Xing Fan, Haoyang Li, Jiliang Tang, Qingsong Wen. (06/2024). arXiv. https://arxiv.org/pdf/2402.14601
ChatGPT-generated help produces learning gains equivalent to human tutor-authored help on mathematics skills
Zachary A. Pardos, Shreya Bhandari. (05/2024). PLOS ONE. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0304013
Developing generative AI chatbots conceptual framework for higher education
Joshua Ebere Chukwuere. (05/2024). arXiv. https://arxiv.org/pdf/2403.19303
Artificial Intelligence and Educational Measurement: Opportunities and Threats
Andrew D. Ho. (05/2024). DASH Harvard. https://dash.harvard.edu/bitstream/handle/1/37379195/AI%20and%20Educational%20M…
Evaluating Students' Open-ended Written Responses with LLMs: Using the RAG Framework for GPT-3.5, GPT-4, Claude-3, and Mistral-Large
Jussi S. Jauhiainen, Agust’n Garagorry Guerra. (05/2024). arXiv. http://arxiv.org/pdf/2405.05444v1
How Can I Get It Right? Using GPT to Rephrase Incorrect Trainee Responses
Jionghao Lin, Zifei Han, Danielle R. Thomas, Ashish Gurung, Shivang Gupta, Vincent Aleven, Kenneth R. Koedinger. (05/2024). arXiv. http://arxiv.org/pdf/2405.00970v1
Evaluating and Optimizing Educational Content with Large Language Model Judgments
Joy He-Yueya, Noah D. Goodman, Emma Brunskill. (05/2024). arXiv. http://arxiv.org/pdf/2403.02795v2
Classroom Education Plan Essa Evidence Packet
QoreInsights. (05/2024). LXD Research. https://www.researchgate.net/publication/382150661_QoreInsights_ESSA_Evidence_P…
Can Large Language Models Make the Grade? An Empirical Study Evaluating LLMs Ability to Mark Short Answer Questions in K-12 Education
Owen Henkel, Libby Hills, Adam Boxer, Bill Roberts, Zach Levonian. (05/2024). ACM Digital Library. https://dl.acm.org/doi/pdf/10.1145/3657604.3664693
Towards A Human-in-the-Loop LLM Approach to Collaborative Discourse Analysis
Clayton Cohn, Caitlin Snyder, Justin Montenegro, Gautam Biswas. (05/2024). arXiv. http://arxiv.org/pdf/2405.03677v1
FOKE: A Personalized And Explainable Education Framework Integrating Foundation Models, Knowledge Graphs, And Prompt Engineering
Silan Hu, Xiaoning Wang. (05/2024). arXiv. http://arxiv.org/pdf/2405.03734v1
Capabilities of Gemini Models in Medicine
Khaled Saab, Tao Tu, Wei-Hung Weng, Ryutaro Tanno, David Stutz, Ellery Wulczyn, Fan Zhang, Tim Strother, Chunjong Park, Elahe Vedadi, Juanma Zambrano Chaves, Szu-Yeu Hu, Mike Schaekermann, Aishwarya Kamath, Yong Cheng, David G.T. Barrett, Cathy Cheung, Basil Mustafa, Anil Palepu, Daniel McDuff, Le Hou, Tomer Golany, Luyang Liu, Jean-baptiste Alayrac, Neil Houlsby, Nenad Tomasev, Jan Freyberg, Charles Lau, Jonas Kemp, Jeremy Lai, Shekoofeh Azizi, Kimberly Kanada, SiWai Man, Kavita Kulkarni, Ruoxi Sun, Siamak Shakeri, Luheng He, Ben Caine, Albert Webson, Natasha Latysheva, Melvin Johnson, Philip Mansfield, Jian Lu, Ehud Rivlin, Jesper Anderson, Bradley Green, Renee Wong, Jonathan Krause, Jonathon Shlens, Ewa Dominowska, S. M. Ali Eslami, Katherine Chou, Claire Cui, Oriol Vinyals, Koray Kavukcuoglu, James Manyika, Jeff Dean, Demis Hassabis, Yossi Matias, Dale Webster, Joelle Barral, Greg Corrado, Christopher Semturs, S. Sara Mahdavi, Juraj Gottweis, Alan Karthikesalingam, Vivek Natarajan. (05/2024). arXiv. http://arxiv.org/pdf/2404.18416v2
