{"slug": "modeling-generative-ai-adoption-and-digital-divide-among-chinese-rural-teachers", "title": "Modeling generative AI adoption and digital divide among Chinese rural teachers", "summary": "A study of 971 rural teachers in Guangxi, China, found that technical support was the strongest factor associated with attitudes toward generative AI adoption (β = 0.515, p < 0.01), followed by perceived usefulness (β = 0.509) and perceived ease of use (β = 0.293), with the model explaining 57.3% of variance in attitudes and 32.3% in usage behavior. The research, published by authors from Guangxi University of Finance and Economics, showed that digital divide conditions significantly moderated the ease-of-use–attitude link, and teachers with lower digital divide conditions reported broader and more advanced GenAI uses, underscoring the need for differentiated policy interventions.", "body_md": "## Abstract\n\nGenerative artificial intelligence (GenAI) is entering schools rapidly, but its uptake may be uneven in under-resourced settings. This study examined factors associated with rural teachers’ GenAI adoption in Guangxi, China, with particular attention to whether digital divide conditions alter key adoption pathways. Drawing on the Contextually Calibrated Technology Adoption Model (CCTAM)—a theoretically motivated re-parameterization of the Technology Acceptance Model that foregrounds resource dependency and multi-dimensional digital inequality as central components—we analyzed survey data from 971 rural teachers using structural equation modeling and moderation analysis. Technical support showed the strongest association with attitudes toward GenAI adoption (β = 0.515, *p* < 0.01), followed by perceived usefulness (β = 0.509, *p* < 0.01) and perceived ease of use (β = 0.293, *p* < 0.01). The model explained 57.3% of the variance in attitudes and 32.3% of the variance in self-reported usage behavior. Digital divide conditions significantly moderated the association between perceived ease of use and attitude, whereas moderation was not supported for the other direct paths to attitude. Teachers facing lower digital divide conditions also reported broader and more pedagogically advanced uses of GenAI. These findings indicate that GenAI adoption in rural schools is associated not only with perceived usefulness and ease of use but also with the resource conditions that support meaningful use, underscoring the need for differentiated policy interventions that prioritize technical support infrastructure and address multi-dimensional digital inequalities in rural educational settings.\n\n## Acknowledgements\n\nThe authors thank the participating teachers and school administrators for their time and cooperation in this study.\n\n## Funding\n\nThis research was supported by the Guangxi Colleges and Universities Humanities and Social Sciences Key Research Base Fund (Project No. 22JDB03), the Guangxi Philosophy and Social Science Planning Research Project (Project No. 21FKS028), and the Guangxi Zhuang Autonomous Region New Medical Research and Practice Project (Project No. XYK202318).\n\n## Author information\n\n### Authors and Affiliations\n\n### Corresponding author\n\n## Ethics declarations\n\n### Competing interests\n\nThe authors declare no competing interests.\n\n### Ethical approval and consent to participate\n\nThis study was approved by the Ethics Committee of Guangxi University of Finance and Economics (Approval No. 20240226). All procedures involving human participants were performed in accordance with relevant institutional and national ethical standards. Informed consent was obtained from all participants prior to data collection. Participation was entirely voluntary, and respondents were informed of their right to decline participation or withdraw at any time without penalty.\n\n### Consent for publication\n\nNot applicable. 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To view a copy of this licence, visit [http://creativecommons.org/licenses/by-nc-nd/4.0/](http://creativecommons.org/licenses/by-nc-nd/4.0/).\n\n## About this article\n\n### Cite this article\n\nXin, Y., Shusheng, D., Weina, H. *et al.* Modeling generative AI adoption among rural teachers: the moderating role of the digital divide in resource-constrained contexts.\n*Sci Rep* (2026). https://doi.org/10.1038/s41598-026-64624-3\n\nReceived:\n\nAccepted:\n\nPublished:\n\nDOI: https://doi.org/10.1038/s41598-026-64624-3", "url": "https://wpnews.pro/news/modeling-generative-ai-adoption-and-digital-divide-among-chinese-rural-teachers", "canonical_source": "https://www.nature.com/articles/s41598-026-64624-3", "published_at": "2026-08-03 19:38:44+00:00", "updated_at": "2026-08-03 19:52:39.057306+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-policy", "ai-ethics"], "entities": ["Guangxi University of Finance and Economics", "Guangxi, China", "Contextually Calibrated Technology Adoption Model (CCTAM)", "Technology Acceptance Model"], "alternates": {"html": "https://wpnews.pro/news/modeling-generative-ai-adoption-and-digital-divide-among-chinese-rural-teachers", "markdown": "https://wpnews.pro/news/modeling-generative-ai-adoption-and-digital-divide-among-chinese-rural-teachers.md", "text": "https://wpnews.pro/news/modeling-generative-ai-adoption-and-digital-divide-among-chinese-rural-teachers.txt", "jsonld": "https://wpnews.pro/news/modeling-generative-ai-adoption-and-digital-divide-among-chinese-rural-teachers.jsonld"}}