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<p>The impact of productive AI on higher education garners significant attention among Chinese scholars. However, existing studies often lack empirical evidence of its actual usage by domestic users. Through investigating the respective variables that explain Chinese college students’ intention and behavior to use generative AI, the current research contributes new knowledge regarding this phenomenon. The following findings are from our analysis of the data according to the Technology Acceptance Model (TAM) and the AISAS Consumer Behavior Analysis Model: (1) Subjective cognition and experience sharing positively shape college students’ perceptions of the ease of use of generative AI. Perceived ease of use fully mediates the influence of subjective cognition and experience sharing on perceived usefulness. (2) There is a very high intention among college students to use generative AI, but variations exist against various demographic characteristics. (3) Intentions affect the generative AI use in terms of the perceived utility and user-friendliness among college students. This study clarifies the inherent processes through which subjective perception and experience of domestic college students regarding generative AI influence their intention toward adoption.</p>

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Exploring college students’ intentions to use generative artificial intelligence in China: analysis on TAM and AISAS models

  • 期刊论文

  • 发表日期：

    2026年4月7日

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  • Yongping Li,
  • Yixue Deng,
  • Xinyi Huang,
  • Jingying Huang

摘要

The impact of productive AI on higher education garners significant attention among Chinese scholars. However, existing studies often lack empirical evidence of its actual usage by domestic users. Through investigating the respective variables that explain Chinese college students’ intention and behavior to use generative AI, the current research contributes new knowledge regarding this phenomenon. The following findings are from our analysis of the data according to the Technology Acceptance Model (TAM) and the AISAS Consumer Behavior Analysis Model: (1) Subjective cognition and experience sharing positively shape college students’ perceptions of the ease of use of generative AI. Perceived ease of use fully mediates the influence of subjective cognition and experience sharing on perceived usefulness. (2) There is a very high intention among college students to use generative AI, but variations exist against various demographic characteristics. (3) Intentions affect the generative AI use in terms of the perceived utility and user-friendliness among college students. This study clarifies the inherent processes through which subjective perception and experience of domestic college students regarding generative AI influence their intention toward adoption.