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<p>The rapid integration of artificial intelligence (AI) into higher education has reshaped teachers’ work processes, yet empirical evidence regarding its implications for teaching innovation remains mixed. Moving beyond technology-deterministic and risk-oriented perspectives, this study examines how AI use fosters university teachers’ innovative teaching behavior by focusing on underlying psychological mechanisms. Drawing on Self-Determination Theory and Social Cognitive Theory, we propose a sequential mediation model in which AI use enhances teachers’ work meaningfulness, which subsequently strengthens creative self-efficacy and promotes innovative teaching behavior. Data were collected from 580 full-time Chinese university teachers using a two-wave time-lagged survey design. Structural equation modeling and bias-corrected bootstrap analyses were employed to test the hypothesized relationships. The results indicate that AI use is positively associated with innovative teaching behavior. Furthermore, both work meaningfulness and creative self-efficacy independently mediate this relationship. Importantly, a significant sequential mediation effect was identified, demonstrating that AI use enhances teachers’ perceptions of work meaningfulness, which in turn strengthens creative self-efficacy and ultimately leads to higher levels of innovative teaching behavior. These findings suggest that the innovative potential of AI in education is psychologically contingent rather than technologically automatic. By uncovering a distal-to-proximal psychological pathway from work meaningfulness to efficacy-based confidence, this study advances understanding of how AI-supported teaching innovation emerges and extends the application of Self-Determination Theory and Social Cognitive Theory to AI-integrated educational contexts. Practically, the results highlight the importance of human-centered AI implementation strategies that foster teachers’ sense of meaning and creative agency to support sustained instructional innovation.</p>

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How does AI use foster teachers’ innovative work behavior? the sequential roles of work meaningfulness and creative self-efficacy

  • 期刊论文

  • 发表日期：

    2026年5月28日

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  • Guangyan Gai,
  • Xueke Zhu,
  • Feilong Yang

摘要

The rapid integration of artificial intelligence (AI) into higher education has reshaped teachers’ work processes, yet empirical evidence regarding its implications for teaching innovation remains mixed. Moving beyond technology-deterministic and risk-oriented perspectives, this study examines how AI use fosters university teachers’ innovative teaching behavior by focusing on underlying psychological mechanisms. Drawing on Self-Determination Theory and Social Cognitive Theory, we propose a sequential mediation model in which AI use enhances teachers’ work meaningfulness, which subsequently strengthens creative self-efficacy and promotes innovative teaching behavior. Data were collected from 580 full-time Chinese university teachers using a two-wave time-lagged survey design. Structural equation modeling and bias-corrected bootstrap analyses were employed to test the hypothesized relationships. The results indicate that AI use is positively associated with innovative teaching behavior. Furthermore, both work meaningfulness and creative self-efficacy independently mediate this relationship. Importantly, a significant sequential mediation effect was identified, demonstrating that AI use enhances teachers’ perceptions of work meaningfulness, which in turn strengthens creative self-efficacy and ultimately leads to higher levels of innovative teaching behavior. These findings suggest that the innovative potential of AI in education is psychologically contingent rather than technologically automatic. By uncovering a distal-to-proximal psychological pathway from work meaningfulness to efficacy-based confidence, this study advances understanding of how AI-supported teaching innovation emerges and extends the application of Self-Determination Theory and Social Cognitive Theory to AI-integrated educational contexts. Practically, the results highlight the importance of human-centered AI implementation strategies that foster teachers’ sense of meaning and creative agency to support sustained instructional innovation.