Educational anxiety triggered by artificial intelligence technology: pathways and configuration analysis affecting teachers’ professional well-being

Abstract

Introduction: This study aims to systematically explore the key factors influencing teachers’ professional well-being and to reveal the complex underlying mechanisms, with the goal of providing both theoretical and practical guidance for enhancing teachers’ professional well-being. Methods: A mixed-methods approach was adopted, combining Structural Equation Modeling (SEM) and Artificial Neural Networks (ANN) to analyze the influencing factors and pathways affecting teachers’ professional well-being. Results: First, work resources such as autonomy in instructional design, teacher-student relationships, sense of professional competence expansion, and proactive job crafting are significantly positively correlated with teachers’ professional well-being, while educational anxiety shows a significant negative correlation. Second, educational anxiety plays a crucial mediating role between work resources and well-being, indicating that part of the positive effect of these resources lies in alleviating anxiety. Third, work engagement positively moderates the beneficial effects of professional competence expansion and proactive job crafting on well-being. Discussion: The study suggests that administrators should grant teachers greater instructional autonomy and provide high-quality professional development opportunities to enhance their sense of competence. Schools should pay attention to teachers’ mental health by establishing support systems to alleviate educational anxiety. At the same time, guiding teachers to proactively engage in job crafting is an effective internal pathway to enhance individual well-being. This study offers a multidimensional theoretical perspective and practical reference for improving teacher well-being.