Abstract #
Generative 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.
Acknowledgements #
The authors thank the participating teachers and school administrators for their time and cooperation in this study.
Funding #
This 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).
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This 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.
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Xin, 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.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-64624-3 Received:
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DOI: https://doi.org/10.1038/s41598-026-64624-3