Constructing a New "Teacher-AI" Collaborative Teaching Paradigm in International Chinese Language Education Enabled by Generative AI

The advent of Generative Artificial Intelligence represents a watershed moment for educational paradigms across disciplines. Within the field of International Chinese Language Education, Generative Artificial Intelligence presents both profound opportunities and significant challenges, compelling a reconceptualization of traditional pedagogical models. This paper moves beyond the discourse of AI as a mere tool or replacement for educators, and instead, proposes a comprehensive "Teacher-AI" collaborative teaching paradigm. This paradigm is conceptualized as a synergistic ecosystem wherein the human teacher and AI systems engage in a dynamic partnership to foster a more personalized, efficient, and profound learning experience for students of Chinese as a second language. This inquiry is qualitative and theoretical, employing a conceptual analysis methodology. It begins by establishing a theoretical foundation grounded in Vygotsky's Sociocultural Theory, particularly the Zone of Proximal Development, and Siemens' Connectivism, arguing that these frameworks provide the necessary scaffolding for understanding a collaborative intelligence model. The core of the paper delineates the proposed paradigm, systematiComputer-Assisted Language Learningy redefining the roles of both the human teacher and the AI. The teacher's role evolves from a primary knowledge dispenser to that of a pedagogical architect, a humanistic mentor, a facilitator of complex interactions, and an assessor of deep competency. Concurrently, the AI is positioned as an indefatigable personalized tutor, a dynamic content co-creator, an immersive practice partner, and an intelligent assessment assistant. A three-stage implementation framework—encompassing pre-class preparation, in-class facilitation, and post-class consolidation—is detailed to provide a practical roadmap for integrating this model into International Chinese Language Education curricula. The paper further explores specific application scenarios, including personalized linguistic practice, simulated communicative contexts, enhancement of intercultural competence, and scaffolded academic writing. Finally, it discusses the pedagogical implications, potential challenges such as ethical considerations and the need for new teacher literacies, and charts directions for future research. This paper contributes a structured, theoretiComputer-Assisted Language Learningy-grounded framework for harnessing Generative Artificial Intelligence not as a disruptive force, but as a collaborative partner in advancing the mission of international Chinese language education.