<p>The emergence of generative artificial intelligence (GAI) has significantly transformed learning patterns and innovative approaches. Human-machine (generative artificial intelligence) co-creation will become the norm, necessitating that learners possess the requisite AI literacy (AIL) to adapt to this shift. The mechanisms by which individual AIL influences innovative behavior (IB) in human-machine collaborative environments remain unclear. Therefore, this study, grounded in the Theory of Planned Behavior (TPB), employs a snowball sampling method to survey 460 university students, utilizing structural equation modeling to analyze the relationships among their AI literacy (AIL), psychological need satisfaction (PNS), creative self-efficacy (CSE), self-regulated learning (SRL), and innovative behavior (IB). The results indicate that AIL does not directly influence learners’ IB. PNS, CSE, and SRL serve as mediators between AIL and IB. Furthermore, AIL influences learners’ PNS and CSE in innovative activities, which in turn affects their use of SRL to adjust their innovation processes, thereby promoting the application of GAI in generating IB.</p>

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How does AI literacy affect individual innovative behavior: the mediating role of psychological need satisfaction, creative self-efficacy, and self-regulated learning

  • Yu Ji,
  • Mingxuan Zhong,
  • Siyan Lyu,
  • Tingting Li,
  • Shijing Niu,
  • Zehui Zhan

摘要

The emergence of generative artificial intelligence (GAI) has significantly transformed learning patterns and innovative approaches. Human-machine (generative artificial intelligence) co-creation will become the norm, necessitating that learners possess the requisite AI literacy (AIL) to adapt to this shift. The mechanisms by which individual AIL influences innovative behavior (IB) in human-machine collaborative environments remain unclear. Therefore, this study, grounded in the Theory of Planned Behavior (TPB), employs a snowball sampling method to survey 460 university students, utilizing structural equation modeling to analyze the relationships among their AI literacy (AIL), psychological need satisfaction (PNS), creative self-efficacy (CSE), self-regulated learning (SRL), and innovative behavior (IB). The results indicate that AIL does not directly influence learners’ IB. PNS, CSE, and SRL serve as mediators between AIL and IB. Furthermore, AIL influences learners’ PNS and CSE in innovative activities, which in turn affects their use of SRL to adjust their innovation processes, thereby promoting the application of GAI in generating IB.