叶晓晨. 基于SEM的生成式人工智能对高校音乐教师任务 完成度影响模型的构建与检验J. 内江师范学院学报, 2026, 41(3): 72-81. DOI: 10.13603/j.cnki.51-1621/z.2026.03.013
    引用本文: 叶晓晨. 基于SEM的生成式人工智能对高校音乐教师任务 完成度影响模型的构建与检验J. 内江师范学院学报, 2026, 41(3): 72-81. DOI: 10.13603/j.cnki.51-1621/z.2026.03.013
    YE Xiaochen. Development and Validation of a Structural Equation Model: The Impact of Generative Artificial Intelligence on Task Completion among Music Teachers in Higher EducationJ. Journal of Neijiang Normal University, 2026, 41(3): 72-81. DOI: 10.13603/j.cnki.51-1621/z.2026.03.013
    Citation: YE Xiaochen. Development and Validation of a Structural Equation Model: The Impact of Generative Artificial Intelligence on Task Completion among Music Teachers in Higher EducationJ. Journal of Neijiang Normal University, 2026, 41(3): 72-81. DOI: 10.13603/j.cnki.51-1621/z.2026.03.013

    基于SEM的生成式人工智能对高校音乐教师任务 完成度影响模型的构建与检验

    Development and Validation of a Structural Equation Model: The Impact of Generative Artificial Intelligence on Task Completion among Music Teachers in Higher Education

    • 摘要: 生成式人工智能技术凭借其内容创造与智能交互优势,正逐步渗透至教育领域。本研究基于技术接受模型与沉浸理论的整合框架,构建包含网络外部性、感知易用性、感知有用性、感知价值、沉浸体验、持续使用意愿6个潜变量的结构方程模型,对612名高校音乐教师进行问卷调查,验证生成式人工智能对高校音乐教师任务完成度的正向影响机制。研究发现,沉浸式体验与感知有用性对持续使用意愿具有显著正向作用,而感知价值存在负向影响。应从政策支持体系构建、产品研发优化路径、教学实践创新方案、教师发展支持系统四个维度进行优化,以助力音乐教育的数字化转型。

       

      Abstract: Generative artificial intelligence (GAI) is increasingly integrating into education, leveraging its strengths in content creation and intelligent interaction. This study is grounded in an integrated framework of the Technology Acceptance Model and Flow Theory. It constructs a novel structural equation model to examine the interrelationships among six latent variables. These variables include network externalities, perceived ease of use, perceived usefulness, perceived value, immersive experience, and continuous usage intention. A survey of 612 music teachers from higher education institutions examines the positive impact mechanism of GAI on their task completion. The results indicate that immersive experience and perceived usefulness significantly promote continuous usage intention, while perceived value exhibits a negative influence. Accordingly, optimization should focus on four dimensions. Specifically, efforts are needed in: building a policy support system, optimizing paths of product research and development, innovating teaching practices, and establishing a teacher development support system. These efforts, thus, will collectively facilitate the digital transformation of music education.

       

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