The Impact of Training Opportunities on Job Satisfaction Among Teachers: Mediating Role of AI Self-Efficacy
Abstract
This study examines how training opportunities influence teachers' job satisfaction, emphasizing the mediating effect of AI self-efficacy among primary and secondary school teachers in Wuhan, China. Current research employed a quantitative, cross-sectional design. Data were collected using an online questionnaire from 655 primary and secondary school teachers in Wuhan. Structural equation modelling (PLS-SEM) was utilized for data analysis. Results confirmed significant positive relationships between training opportunities and both AI self-efficacy and job satisfaction. Besides, AI self-efficacy was found to significantly mediate the relationship between training opportunities and job satisfaction. This study contributes to the body of knowledge by empirically showed the relatively unexplored psychological pathway (AI self-efficacy) linking training opportunities to job satisfaction within AI-intensive educational contexts. The findings enhance understanding of how structured training in AI can positively influence teachers' attitudes and job-related outcomes. Educational policymakers and administrators can utilise these findings to develop specialised training programs, thereby improving teacher self-efficacy, job satisfaction and overall effectiveness in responding to technology changes.
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