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  • https://doi.org/10.54254/2753-7064/2026.ht31478Copy DOI Icon

The Impact of AI-driven Contextual Input and Output on Second Language Acquisition

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Abstract

As the AI (Artificial Intelligence, AI) technology, especially the language model and the rapid development of intelligent learning system in the field of language education, contextualized input and output have gradually become an important path to promote Second Language Acquisition (SLA). Based on the theory of input hypothesis and output hypothesis and social culture and interactive approaches, this article system combed the AI drive learning environment, language input, output, and the change of the interactive mechanism and its influence on second language acquisition. Research suggests that AI can enhance the understandability and relevance of input through adaptive recommendation, multimodal presentation, and virtual situation simulation. At the output level, AI dialogue system, real-time error correction and scaffolding support for language learners provides a high frequency, low anxiety generated opportunities, complexity and accuracy in grammar, syntax and vocabulary, expression fluency and pragmatic appropriateness, etc, to promote the language output quality improvement. More importantly, AI integrates input, output and feedback into a dynamic loop process, thereby reshaping the occurrence conditions of traditional second language acquisition to a certain extent. In the affirmation of the potential of the AI in language learning at the same time, the paper also points out its authenticity, learner differences in interactive adaptation and technology rely on is still limited, and emphasizes on the importance of teachers' professional guidance to realize man-machine coordinated. This article aims to provide references for the research and instructional design of second language teaching supported by AI from both theoretical and practical perspectives.

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