Scholarlink

<p>The rapid development of artificial intelligence technology in the field of education has led to its increasingly widespread application by teachers in teaching practice. This has not only reshaped the educational ecosystem but also had a profound impact on teachers’ self-efficacy. However, technological anxiety, as a negative emotional response, undermines teachers’ confidence and ability to apply artificial intelligence technology. Although existing research has explored the relationship between technological anxiety and teachers’ behavioral outcomes, there is still a lack of in-depth understanding of its psychological mechanisms and the moderating effects of external resources. Therefore, based on the Cognitive Evaluation Theory and the Unified Theory of Acceptance and Use of Technology, this study constructs an analytical framework that includes mediating and moderating effects, aiming to explore how technological anxiety affects teachers’ self-efficacy in AI teaching through work engagement and the moderating role of social support in this process. Based on a cross-sectional survey of 550 primary and secondary school teachers in Jiangxi and Fujian provinces, this study advances the educational technology anxiety mechanism model by integrating work engagement. In addition, the findings demonstrate that social support exerts a significant cross-level moderating effect. The results show that: (1) Technological anxiety has a significant negative impact on teachers’ self-efficacy in AI teaching; (2) Work engagement plays a partial mediating role between technological anxiety and teachers’ self-efficacy in AI teaching; (3) Social support has a positive moderating effect between technological anxiety and work engagement, as well as between work engagement and teachers’ self-efficacy in AI teaching; (4) Social support plays a significant positive moderating role between work engagement and teachers’ self-efficacy in AI competence. This study contributes to teachers’ professional development theory and offers empirical support for developing AI teacher training systems that combine technological and psychological dimensions. It further provides actionable insights for educational practice on mitigating teachers’ technology anxiety and strengthening their self-efficacy in AI-based teaching.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

How does technological anxiety affect teachers’ self-efficacy in AI competence: the mediating role of work engagement and the moderating role of social support

  • 期刊论文

  • 发表日期：

    2026年5月25日

查看全文
  • Qun Lin,
  • Qing Zhou,
  • Qian Long,
  • Min Zhu,
  • Haoran Ma

摘要

The rapid development of artificial intelligence technology in the field of education has led to its increasingly widespread application by teachers in teaching practice. This has not only reshaped the educational ecosystem but also had a profound impact on teachers’ self-efficacy. However, technological anxiety, as a negative emotional response, undermines teachers’ confidence and ability to apply artificial intelligence technology. Although existing research has explored the relationship between technological anxiety and teachers’ behavioral outcomes, there is still a lack of in-depth understanding of its psychological mechanisms and the moderating effects of external resources. Therefore, based on the Cognitive Evaluation Theory and the Unified Theory of Acceptance and Use of Technology, this study constructs an analytical framework that includes mediating and moderating effects, aiming to explore how technological anxiety affects teachers’ self-efficacy in AI teaching through work engagement and the moderating role of social support in this process. Based on a cross-sectional survey of 550 primary and secondary school teachers in Jiangxi and Fujian provinces, this study advances the educational technology anxiety mechanism model by integrating work engagement. In addition, the findings demonstrate that social support exerts a significant cross-level moderating effect. The results show that: (1) Technological anxiety has a significant negative impact on teachers’ self-efficacy in AI teaching; (2) Work engagement plays a partial mediating role between technological anxiety and teachers’ self-efficacy in AI teaching; (3) Social support has a positive moderating effect between technological anxiety and work engagement, as well as between work engagement and teachers’ self-efficacy in AI teaching; (4) Social support plays a significant positive moderating role between work engagement and teachers’ self-efficacy in AI competence. This study contributes to teachers’ professional development theory and offers empirical support for developing AI teacher training systems that combine technological and psychological dimensions. It further provides actionable insights for educational practice on mitigating teachers’ technology anxiety and strengthening their self-efficacy in AI-based teaching.