Constructing a Teacher–Student–AI Agent Collaborative Teaching Model for Vocational ESP: A Symbiotic Theory Approach to Chaoxing AI Agent Integration

Abstract

The rapid advancement of generative artificial intelligence has created new possibilities for reconstructing teaching relationships in vocational English for Specific Purposes (ESP), yet existing research remains largely confined to theoretical frameworks without platform-based empirical validation. This conceptual and design-oriented paper proposes a “Teacher–Student–AI Agent” (TSA) collaborative teaching model for vocational ESP, grounded in symbiotic theory and implemented through the Chaoxing AI Agent platform. The paper addresses two critical gaps: the lack of operational models for TSA collaboration within specific smart teaching platforms, and the insufficient integration of AI agents into vocational ESP instruction, particularly in cruise service English. Drawing upon symbiotic theory and human–AI collaboration research, the study repositions the AI agent not as a passive tool but as a “digital collaborator” capable of diagnosis, interaction, and evaluation. It analyzes the four core functions of the Chaoxing AI Agent—AI Teaching Assistant, Customized AI Agent, AI Practice, and AI Learning Analytics—and maps them onto the teaching needs of cruise service English. On this basis, the paper constructs a three-subject, four-stage collaborative model comprising three subjects (teacher, student, AI agent) and four stages (pre-class diagnosis, in-class interaction, post-class evaluation, and continuous optimization). A key contribution is the design of an AI-empowered cruise service scenario bank covering at least eight typical workplace tasks. The paper also discusses design principles, role division, interaction logic, and transferability to other vocational ESP courses, providing a theoretical and practical blueprint for reconstructing teaching relationships in the digital intelligence era.