An Analysis of the Application of Generative Artificial Intelligence in Second Language Acquisition

Nantong Institute of Technology, School of Information Engineering, No. 1 Shanghu Avenue, Economic and Technological Development Zone, Haian City, Jiangsu Province, China

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Abstract

This analysis explores the application of Generative Artificial Intelligence (GenAI) in Second Language Acquisition (SLA), highlighting its opportunities and challenges. GenAI tools (e.g., ChatGPT for text) offer significant potential by providing personalized, comprehensible input aligned with Krashen’s Input Hypothesis (i+1 level) and enabling interactive output cycles, supporting Swain’s Output Hypothesis. They facilitate constructivist learning through authentic scenario creation and immersive practice (e.g., IVR environments), and act as “cognitive scaffolds” within Vygotsky’s Zone of Proximal Development (ZPD) under Sociocultural Theory, offering real-time feedback and reducing anxiety. However, key challenges include threats to academic integrity due to ease of misuse (e.g., generating assignments) and the potential perpetuation of cultural biases inherent in training data. The paper concludes that learners and teachers should critically leverage GenAI’s benefits for personalized input, output and scenario creation while actively mitigating its risks.