A mixed-methods exploration of social network diversity, collaboration, and job satisfaction among new teachers in urban China

This study explores the interrelationships between social network diversity, teacher collaboration, and job satisfaction among new teachers in urban public schools in China. Employing a mixed-methods approach, the research integrates quantitative data analyzed through Structural Equation Modeling (SEM) and qualitative insights from thematic analysis. The sample consisted of 371 new teachers from primary and secondary schools in Beijing, Shanghai, and Guangzhou, chosen for their distinct educational environments. Results indicated that social network diversity positively impacts teacher collaboration, which in turn significantly enhances job satisfaction. The SEM analysis demonstrated good model fit, with significant direct effects of social network diversity on both teacher collaboration and job satisfaction, and an indirect effect of social network diversity on job satisfaction mediated by teacher collaboration. Thematic analysis of focus group discussions corroborated these findings, highlighting the critical role of supportive social networks and collaborative practices in fostering a sense of community and professional efficacy among new teachers. These findings underscore the importance of fostering robust social network diversity and collaborative environments in schools to enhance job satisfaction and retention among new teachers in urban China.