AI Empowerment Logic in the Digital Transformation of Chinese Language Education: From Tool Application to Ecological Reconstruction
Abstract
With the coupled development of Generative Artificial Intelligence (GAI) and big data technologies, Chinese language education — especially international Chinese language education—is experiencing a critical leap from "information-assisted teaching" to "digital transformation." This study delves into the inherent evolutionary logic of AI empowerment in Chinese language education, arguing that its transformation path follows a three-stage progression: from efficiency-driven tool application in individual links, to full-process human-AI collaborative innovation, and ultimately to the systematic reconstruction of the educational ecosystem. The research elaborates on AI’s profound impacts in reshaping learning paradigms, redefining teaching time and space, and enhancing teacher evaluation. It highlights that the essence of digital transformation lies in the reorganization of educational elements and the digital extension of educational sovereignty. Drawing on transnational cases and authoritative studies, this paper deconstructs the implementation paths of ecological reconstruction across four core dimensions: learning paradigms, resource development, evaluation systems, and governance mechanisms. Additionally, it offers forward-looking reflections on ethical challenges and technological boundaries in the current transformation, providing theoretical support and practical insights for building a high-quality, sustainable global digital ecosystem for Chinese language education.
Keywords
Chinese language education, artificial intelligence, digital transformation, ecological reconstruction, human-AI collaboration, educational governance
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