The role of STEM teachers' emotional intelligence and psychological well-being in predicting their artificial intelligence literacy

This study explores the role of emotional intelligence and psychological well-being in predicting artificial intelligence literacy among STEM teachers. A total of 383 Chinese STEM teachers from Henan, Zhejiang, and Yunnan provinces participated. The participants varied in age and academic backgrounds, bringing diverse experiences to their roles. Data was collected using three instruments: the Meta AI Literacy Scale (MAILS), Psychological Well-Being at Work, and the Wong and Law Emotional Intelligence Scale (WLEIS). The study employed a back-translation method to ensure the accuracy of the English questionnaires, which were administered online. Data analysis was conducted using SPSS (version 27) and AMOS (version 24) to explore relationships between variables. The findings reveal a strong and statistically significant relationship between psychological well-being, emotional intelligence, and AI literacy, with psychological well-being uniquely predicting about 61 % and emotional intelligence predicting 71 % of the variations in AI literacy. These results highlight the critical role of psychological and emotional health in fostering teachers' mastery of AI-related skills, emphasizing the need for educational programs to support these aspects for effective integration of new technologies.