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Main Authors: Li, Ming, Xie, Qin, Enkhtur, Ariunaa, Meng, Shuoyang, Chen, Lilan, Yamamoto, Beverley Anne, Cheng, Fei, Murakami, Masayuki
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2504.02636
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author Li, Ming
Xie, Qin
Enkhtur, Ariunaa
Meng, Shuoyang
Chen, Lilan
Yamamoto, Beverley Anne
Cheng, Fei
Murakami, Masayuki
author_facet Li, Ming
Xie, Qin
Enkhtur, Ariunaa
Meng, Shuoyang
Chen, Lilan
Yamamoto, Beverley Anne
Cheng, Fei
Murakami, Masayuki
contents As generative AI (GAI) becomes more integrated into higher education, universities are actively exploring its governance and issuing guidelines to promote responsible use, reflecting varied stages of adoption and orientations. This study undertakes a comparative analysis of current GAI guidelines issued by leading universities in the United States, Japan, and China. Based on these findings, the study proposes a University Policy Development Framework for GAI (UPDF-GAI) to provide both theoretical insights and practical guidance for universities in developing and refining their GAI policies. This study adopts five domains from the extended Technology Acceptance Model. A qualitative content analysis of 124 policy documents from 110 universities was conducted, employing thematic coding to synthesize 20 key themes. These domains and themes form the foundation of the UPDF-GAI framework. The analysis reveals varying priorities and focus of GAI policy of universities in different countries. U.S. universities emphasize faculty autonomy, practical application, and policy adaptability, shaped by cutting-edge research and peer collaboration. Japanese universities take a government-regulated approach, prioritizing ethics and risk management, but provide limited support for AI implementation and flexibility. Chinese universities follow a centralized, government-led model, focusing on technology application over early policy development, while actively exploring GAI integration in education and research. The framework facilitates universities in formulating GAI policies by balancing its values and risks, providing multi-level support, proactively responding to societal impacts, and strengthening self-efficacy. In doing so, it enables the development of sustainable and context-sensitive policies that enhance digital competitiveness and advance preparedness for AI-driven education.
format Preprint
id arxiv_https___arxiv_org_abs_2504_02636
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Framework for Developing University Policies on Generative AI Governance: A Cross-national Comparative Study
Li, Ming
Xie, Qin
Enkhtur, Ariunaa
Meng, Shuoyang
Chen, Lilan
Yamamoto, Beverley Anne
Cheng, Fei
Murakami, Masayuki
Computers and Society
As generative AI (GAI) becomes more integrated into higher education, universities are actively exploring its governance and issuing guidelines to promote responsible use, reflecting varied stages of adoption and orientations. This study undertakes a comparative analysis of current GAI guidelines issued by leading universities in the United States, Japan, and China. Based on these findings, the study proposes a University Policy Development Framework for GAI (UPDF-GAI) to provide both theoretical insights and practical guidance for universities in developing and refining their GAI policies. This study adopts five domains from the extended Technology Acceptance Model. A qualitative content analysis of 124 policy documents from 110 universities was conducted, employing thematic coding to synthesize 20 key themes. These domains and themes form the foundation of the UPDF-GAI framework. The analysis reveals varying priorities and focus of GAI policy of universities in different countries. U.S. universities emphasize faculty autonomy, practical application, and policy adaptability, shaped by cutting-edge research and peer collaboration. Japanese universities take a government-regulated approach, prioritizing ethics and risk management, but provide limited support for AI implementation and flexibility. Chinese universities follow a centralized, government-led model, focusing on technology application over early policy development, while actively exploring GAI integration in education and research. The framework facilitates universities in formulating GAI policies by balancing its values and risks, providing multi-level support, proactively responding to societal impacts, and strengthening self-efficacy. In doing so, it enables the development of sustainable and context-sensitive policies that enhance digital competitiveness and advance preparedness for AI-driven education.
title A Framework for Developing University Policies on Generative AI Governance: A Cross-national Comparative Study
topic Computers and Society
url https://arxiv.org/abs/2504.02636