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<p>In the age of Artificial Intelligence (AI), a significant transformation is taking place in art education for university students. AI literacy has become a crucial element for them to navigate the intricate digital landscape. However, existing AI literacy research has primarily focused on general education, STEM education, or workplace contexts, while studies specifically examining AI literacy in art education and creative learning environments remain relatively limited. This study employed the PLS-SEM method to uncover the factors that influence university students’ behavioral intention (BI) to use Generative AI (GenAI), based on the UTAUT model, and to examine the mediating role of AI literacy. This study recruited university students on a voluntary basis who had previously used GenAI to complete art assignments. A total of 703 valid responses were gathered and analyzed using SmartPLS 4 software. The findings revealed that performance expectancy (β = 0.651, <i>p</i> &lt; 0.001), effort expectancy (β = 0.292, <i>p</i> &lt; 0.001), and social influence (β=-0.093, <i>p</i> = 0.009) significantly influenced AI literacy, while AI literacy strongly predicted behavioral intention to use GenAI (β = 0.386, <i>p</i> &lt; 0.001). This research assists educational institutions in understanding how UTAUT-related factors and AI literacy jointly shape students’ behavioral intention to use GenAI in art education. It not only offers a valuable reference for constructing an AI literacy framework for university students majoring in art education in the digital age but also provides a theoretical underpinning for the digital transformation of university art education courses.</p>

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What impact does AI literacy have on university students’ behavioral intention to use generative AI in art education? a quantitative analysis based on the UTAUT model

  • 期刊论文

  • 发表日期：

    2026年7月8日

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  • Jia Ke,
  • Yizhen Gan

摘要

In the age of Artificial Intelligence (AI), a significant transformation is taking place in art education for university students. AI literacy has become a crucial element for them to navigate the intricate digital landscape. However, existing AI literacy research has primarily focused on general education, STEM education, or workplace contexts, while studies specifically examining AI literacy in art education and creative learning environments remain relatively limited. This study employed the PLS-SEM method to uncover the factors that influence university students’ behavioral intention (BI) to use Generative AI (GenAI), based on the UTAUT model, and to examine the mediating role of AI literacy. This study recruited university students on a voluntary basis who had previously used GenAI to complete art assignments. A total of 703 valid responses were gathered and analyzed using SmartPLS 4 software. The findings revealed that performance expectancy (β = 0.651, p < 0.001), effort expectancy (β = 0.292, p < 0.001), and social influence (β=-0.093, p = 0.009) significantly influenced AI literacy, while AI literacy strongly predicted behavioral intention to use GenAI (β = 0.386, p < 0.001). This research assists educational institutions in understanding how UTAUT-related factors and AI literacy jointly shape students’ behavioral intention to use GenAI in art education. It not only offers a valuable reference for constructing an AI literacy framework for university students majoring in art education in the digital age but also provides a theoretical underpinning for the digital transformation of university art education courses.