Reconceptualizing Foreign Language Learning through Artificial Intelligence within the Framework of the Zone of Proximal Development

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摘要

The rapid integration of artificial intelligence into education is reshaping the ecology of language learning. Rather than functioning merely as auxiliary tools, intelligent systems have begun to intervene directly in the pedagogical process. Grounded in Vygotsky's sociocultural theory, this paper examines how AI systems — through scaffolding mechanisms — support learners in transitioning from actual to potential linguistic competencies. The zone of proximal development (ZPD) serves as a theoretical anchor to interpret how technologies such as intelligent evaluation systems and generative dialogue agents mediate feedback, structure adaptive input, and personalize instructional support. The study finds that AI contributes not only to dynamic scaffolding but also to the reconfiguration of human–machine instructional collaboration. This work offers a theoretical model for understanding AI's function in foreign language education and highlights its implications for task design, instructional responsiveness, and learning autonomy.

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