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 Kras...

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Bibliographic Details
Published in:SHS web of conferences Vol. 223; p. 1003
Main Author: Xu, Weiwei
Format: Journal Article Conference Proceeding
Language:English
Published: Les Ulis EDP Sciences 2025
Subjects:
Anxiety
Artificial intelligence
constructivist theory
Customization
Feedback
generative artificial intelligence (genai)
input hypothesis
Language acquisition
Morality
output hypothesis
Perpetuation
second language acquisition (sla)
Second language learning
social cultural theory
Sociocultural factors
Sociocultural theory
Teachers
Vygotskian perspective
ISSN:2261-2424, 2416-5182, 2261-2424
Online Access:Get full text
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Summary: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.
Bibliography:ObjectType-Conference Proceeding-1
SourceType-Conference Papers & Proceedings-1
content type line 21
ISSN:2261-2424
2416-5182
2261-2424
DOI:10.1051/shsconf/202522301003