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Research synthesis is AI-generated, human reviewed. Updated 09/2025.
Displaying 361 - 390 of 476
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
A GPT-based Code Review System for Programming Language Learning
Lee Dong-Kyu. (06/2024). arXiv. http://arxiv.org/pdf/2407.04722v1
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
Math Multiple Choice Question Generation via Human-Large Language Model Collaboration
Jaewook Lee, Digory Smith, Simon Woodhead, Andrew Lan. (05/2024). arXiv. http://arxiv.org/pdf/2405.00864v1
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
Realizing Visual Question Answering for Education: GPT-4V as a Multimodal AI
Gyeong-Geon Lee, Xiaoming Zhai. (05/2024). arXiv. https://arxiv.org/pdf/2405.07163
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
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
Grade Like a Human: Rethinking Automated Assessment with Large Language Models
Wenjing Xie, Juxin Niu, Chun Jason Xue, Nan Guan. (05/2024). arXiv. https://arxiv.org/pdf/2405.19694
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…
Generative AI in Higher Education: A Global Perspective of Institutional Adoption Policies and Guidelines
Yueqiao Jin, Lixiang Yan, Vanessa Echeverria, Dragan Gasevic, Roberto Martinez-Maldonado. (05/2024). arXiv. https://arxiv.org/pdf/2405.11800
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
LLMs can Find Mathematical Reasoning Mistakes by Pedagogical Chain-of-Thought
Zhuoxuan Jiang, Haoyuan Peng, Shanshan Feng, Fan Li, Dongsheng Li. (05/2024). arXiv. http://arxiv.org/pdf/2405.06705v1
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
Developing generative AI chatbots conceptual framework for higher education
Joshua Ebere Chukwuere. (05/2024). arXiv. https://arxiv.org/pdf/2403.19303
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
Large Language Models for Education: A Survey
Hanyi Xu, Wensheng Gan, Zhenlian Qi, Jiayang Wu and Philip S. Yu. (05/2024). arXiv. http://arxiv.org/pdf/2405.13001v1
AI AND PERSONALIZED LEARNING: BRIDGING THE GAP WITH MODERN EDUCATIONAL GOALS
Kristjan-Julius Laak, Jaan Aru. (04/2024). arXiv. https://arxiv.org/pdf/2404.02798
Pros and Cons of Artificial Intelligence-ChatGPT Adoption in Education Settings: A Literature Review and Future Research Agendas
Idria Maita, Saide Saide, Afifah Mesha Putri, Didi Muwardi. (04/2024). IEEE. https://ieeexplore.ieee.org/document/10510580
Designing Child-Centric AI Learning Environments: Insights from LLM-Enhanced Creative Project-Based Learning
Siyu Zha, Yuehan Qiao, Qingyu Hua, Zhongsheng Li, Jiangtao Gong, Yingqing Xu. (04/2024). arXiv. http://arxiv.org/pdf/2403.16159v2
Can Autograding of Student-Generated Questions Quality by ChatGPT Match Human Experts?
Kangkang Li, Qian Yang, Xianmin Yang. (04/2024). IEEE. https://ieeexplore.ieee.org/document/10510637
Bridging the Novice-Expert Gap via Models of Decision-Making: A Case Study on Remediating Math Mistakes
Rose E. Wang, Qingyang Zhang, Carly Robinson, Susanna Loeb, Dorottya Demszky. (04/2024). arXiv. http://arxiv.org/pdf/2310.10648v3
The AI Companion in Education: Analyzing the Pedagogical Potential of ChatGPT in Computer Science and Engineering
Zhangying He, Mehrdad Aliasgari, Thomas Nguyen, Setareh Rafatirad, Tahereh Miari, Hossein Sayadi. (04/2024). arXiv. https://arxiv.org/pdf/2407.05205
AI and Machine Learning for Next Generation Science Assessments
Xiaoming Zhai. (04/2024). arXiv. http://arxiv.org/pdf/2405.06660v1
Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges
Qingyao Li, Lingyue Fu, Weiming Zhang, Xianyu Chen, Jingwei Yu, Wei Xia, Weinan Zhang, Ruiming Tang, Yong Yu. (04/2024). arXiv. http://arxiv.org/pdf/2401.08664v3
Large Language Models for Education: A Survey and Outlook
Shen Wang, Tianlong Xu, Hang Li, Chaoli Zhang, Joleen Liang, Jiliang Tang, Philip S. Yu, Qingsong Wen. (04/2024). arXiv. http://arxiv.org/pdf/2403.18105v2
Teach AI How to Code: Using Large Language Models as Teachable Agents for Programming Education
Hyoungwook Jin, Seonghee Lee, Hyungyu Shin, Juho Kim. (03/2024). arXiv. http://arxiv.org/pdf/2309.14534v3
iScore: Visual Analytics for Interpreting How Language Models Automatically Score Summaries
Adam Coscia, Langdon Holmes, Wesley Morris, Joon Suh Choi, Scott Crossley, Alex Endert. (03/2024). arXiv. http://arxiv.org/pdf/2403.04760v1
