This study investigates how Chinese pre-service teachers of English as a foreign language (EFL) develop self-regulated teaching competencies in the face of disruptions posed by generative artificial intelligence (GenAI) and structural limitations within teacher education programs. As GenAI increasingly influences EFL instruction, uncertainties surrounding teachers' professional roles intensify. Meanwhile, the limited availability of practical teaching internships in China compels pre-service teachers to independently cultivate essential skills, rendering self-regulated teaching pivotal. Drawing on the Conservation of Resources (COR) theory, we examined the interplay among academic resilience, cognitive appraisals (challenge versus hindrance), and self-regulated teaching. Employing Covariance-Based Structural Equation Modeling (CB-SEM), we analyzed data from 517 participants across six universities in three Chinese provinces. Findings revealed that academic resilience significantly predicted self-regulated teaching, with challenge appraisals mediating this relationship, suggesting that resilience facilitates a growth-oriented interpretation of stress. While resilience was linked to reduced hindrance appraisal, this pathway did not significantly influence self-regulated teaching. Age was associated with more positive cognitive framing (older participants reported higher challenge appraisals), but had no direct effect on self-regulated teaching; gender showed no significant impact. These insights underscore the value of fostering academic resilience and challenge-based cognitive strategies to better prepare pre-service EFL teachers for the dual demands of technological transformation and institutional constraint.
Liu et al. (Sun,) studied this question.