Şahin, Merve2026-02-032026-02-0320252071-1050https://doi.org/10.3390/su17198613https://hdl.handle.net/20.500.12428/34432The integration of artificial intelligence (AI) into education is a defining challenge for achieving a sustainable digital future. This study addresses this challenge by exploring the psychological foundations necessary for teacher readiness, framing this preparation as a matter of social sustainability for the teaching profession. Employing a correlational research design, this study investigates the relationships among key psychological constructs as perceived by pre-service educators. Specifically, it examines how pre-service preschool teachers' self-reported levels of self-regulation and social-emotional expertise relate to their self-assessed AI-Technological Pedagogical Content Knowledge (AI-TPACK). The findings were revealing: multiple linear regression analyses confirmed perceived self-regulation as a robust predictor of the self-assessed core and composite knowledge elements of AI-TPACK. Counterintuitively, social-emotional expertise did not show a significant correlation with any aspect of AI-TPACK. This suggests that the metacognitive skills inherent in self-regulation are fundamental for empowering educators to engage in the lifelong learning required for a sustainable career. Therefore, teacher education programs must strategically cultivate these skills to foster a resilient teaching workforce, capable of ethically shaping the future of AI in inclusive and sustainable learning environments.eninfo:eu-repo/semantics/openAccessAI-TPACKpreschool teacher educationself-regulationsocial-emotional expertisesocial sustainabilitysustainable pedagogyArticle171910.3390/su17198613Q2WOS:0015938646000012-s2.0-105018961992Q1