Post-Secondary
Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 781 - 810 of 911
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…
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
The Role of Al in Peer Support for Young People: A Study of Preferences for Human- and Al-Generated Responses
Jordyn Young, Laala M Jawara, Diep N Nguyen, Brian Daly, Jina Huh-Yoo, Afsaneh Razi. (05/2024). arXiv. http://arxiv.org/pdf/2405.02711v1
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
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
An Automatic Question Usability Evaluation Toolkit
Steven Moore, Eamon Costello, Huy A. Nguyen, John Stamper. (05/2024). arXiv. http://arxiv.org/pdf/2405.20529v1
JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models
Kun Zhou, Beichen Zhang, Jiapeng Wang, Zhipeng Chen, Wayne Xin Zhao, Jing Sha, Zhichao Sheng, Shijin Wang, Ji-Rong Wen. (05/2024). arXiv. http://arxiv.org/pdf/2405.14365v1
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
Desirable Characteristics for AI Teaching Assistants in Programming Education
Paul Denny, Stephen MacNeil, Jaromir Savelka, Leo Porter, Andrew Luxton-Reilly. (05/2024). arXiv. https://arxiv.org/pdf/2405.14178
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
The AI Collaborator: Bridging Human-Ai Interaction In Educational And Professional Settings
Mohammad Amin Samadi, Spencer JaQuay, Nia Nixon, Jing Gu. (05/2024). arXiv. http://arxiv.org/pdf/2405.10460v1
AI Tutoring Outperforms Active Learning
Gregory Kestin, Kelly Miller, Anna Klales, Timothy Milbourne, Gregorio Ponti. (05/2024). Research Square. https://www.researchsquare.com/article/rs-4243877/v1
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
Remote Possibilities: Where There Is a WIL, Is There a Way? AI Education for Remote Learners in a New Era of Work-Integrated-Learning
Derek Jacoby, Saiph Savage, Yvonne Coady. (04/2024). arXiv. http://arxiv.org/pdf/2402.12667v2
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
The Evolution of Learning: Assessing the Transformative Impact of Generative AI on Higher Education
Stefanie Krause, Bhumi Hitesh Panchal, Nikhil Ubhel. (04/2024). arXiv. https://arxiv.org/pdf/2404.10551
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
Instructors as Innovators: A future-focused approach to new AI learning opportunities, with prompts
Dr. Ethan Mollick, Dr. Lilach Mollick. (04/2024). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4802463
Exploring How Multiple Levels of GPT-Generated Programming Hints Support or Disappoint Novices
Ruiwei Xiao, Xinying Hou, John Stamper. (04/2024). arXiv. http://arxiv.org/pdf/2404.02213v1
The GPT Surprise: Offering Large Language Model Chat in a Massive Coding Class Reduced Engagement but Increased Adopters' Exam Performances
Allen Nie, Yash Chandak, Miroslav Suzara, Ali Malik, Juliette Woodrow, Matt Peng, Mehran Sahami, Emma Brunskill, Chris Piech. (04/2024). MyIDEAS. https://ideas.repec.org/p/osf/osfxxx/qy8zd.html
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
Clue-Instruct: Text-Based Clue Generation for Educational Crossword Puzzles
Andrea Zugarini, Kamyar Zeinalipour, Surya Sai Kadali, Marco Maggini, Marco Gori, Leonardo Rigutini. (04/2024). arXiv. http://arxiv.org/pdf/2404.06186v1
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
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
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
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
The future of generative AI chatbots in higher education
Joshua Ebere Chukwuere. (03/2024). arXiv. https://arxiv.org/pdf/2403.13487
From Guidelines to Governance: A Study of AI Policies in Education
Aashish Ghimire, John Edwards. (03/2024). arXiv. https://arxiv.org/pdf/2403.15601
Using Generative Text Models to Create Qualitative Codebooks for Student Evaluations of Teaching
Andrew Katz, Mitch Gerhardt, Michelle Soledad. (03/2024). arXiv. http://arxiv.org/pdf/2403.11984v1
