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

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.

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Publication Details

Journal
SHS Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/shsconf/202522301003
Citations
1
Primary Topic
Educational Technology and Pedagogy
Type
article
Field-Weighted Citation Impact
2.48
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article

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

Weiwei Xu
1 citations
SHS Web of Conferences
Educational Technology and Pedagogy
2.48
article

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

Weiwei Xu
article en
1 citations

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.

SHS Web of ConferencesVol. 223
Institute of Economic Development (GB)
Openalex Percentile: Top 8%
Educational Technology and Pedagogy
2.48
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