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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.02636 |
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| _version_ | 1866912715759419392 |
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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 |