This study examines the mediating role of social capital (SC) between the use of artificial intelligence (AI) tools and subjective well-being (SWB) among Chinese university students majoring in physical education. Drawing on a theoretical framework that distinguishes bonding and bridging SC, the study tested whether AI use in sports-related contexts influences SWB through different SC typologies. A questionnaire survey was conducted with 428 students from five universities representing diverse economic and regional contexts. Factor analysis (KMO = 0.90, α > 0.70) identified five dimensions of SC—trust and attachment, social participation, neighborhood exchange, trust in strangers, and community anxiety. Cluster analysis yielded three SC types: “low bonding,” “high bonding,” and “bridging.” Mediation analyses revealed that AI use affected SWB entirely through bonding SC. Specifically, AI experience increased low bonding SC (which negatively predicted SWB) and decreased high bonding SC (which positively predicted SWB), resulting in two opposite but both negative indirect effects. Bridging SC showed no significant mediating effect. These findings indicate that AI exposure does not automatically enhance happiness; rather, its benefits depend on the quality and density of interpersonal trust networks. In the context of Chinese collectivist sports education, where hierarchical and closed bonding structures are prevalent, strong interpersonal ties are essential for transforming AI-related experiences into subjective well-being. The study highlights that social capital, particularly bonding ties, functions as an invisible infrastructure that supports human resilience and adaptive happiness in the AI era. The implications suggest that AI implementation in education and sports industries must be accompanied by institutional designs that sustain mutual trust, reciprocity, and collaborative learning environments.
抄録全体を表示