Yingjuan Wang, Minjun Cai

College of Educational Technology, Northwest Normal University

Abstract：

To address the current issues in oral English teaching, such as the lack of real teaching scenarios, delayed feedback, and insufficient effectiveness of school-based training, this study, from the perspective of human-machine collaboration, explores the model construction and practical paths of AIGC-driven school-based English teacher training. Based on Activity Theory, Reflective Practice Theory, and the Intelligent Literacy Framework, it proposes a training model of "AI Virtual Coach + Oral Bilingual Classroom", designs a dual-loop interactive structure of "inner-loop classroom practice + outer-loop training improvement" and a four-stage closed-loop process of "goal design-classroom practicereflective discussion-iterative optimization", and clarifies the complementary and balanced roles of AI virtual coaches, English teachers, and school teaching and research groups. The research shows that this model has realized the transformation of oral English teaching and training from "experience-driven" to "data-driven", from "single training" to "situational collaboration", and from "individual reflection" to "community co-research". It can provide an operable paradigm for the professional development of English teachers in the intelligent era. Finally, future research directions are proposed from three aspects: teachers' emotional and cognitive development, interdisciplinary integration, and long-term tracking, aiming to build a new human-machine symbiotic educational ecosystem.

Key Words：

human-machine collaboration; AIGC; English teachers; school-based training; AI virtual coach; oral bilingual classroom