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<p>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, <i>p</i> &lt; 0.01), followed by perceived usefulness (β = 0.509, <i>p</i> &lt; 0.01) and perceived ease of use (β = 0.293, <i>p</i> &lt; 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.</p>

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Modeling generative AI adoption among rural teachers: the moderating role of the digital divide in resource-constrained contexts

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月1日

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  • Yang Xin,
  • Deng Shusheng,
  • Hu Weina,
  • Deng Yan

摘要

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.