ChatGPT in language education: Centering learner voices

Within educational linguistics and applied language studies, the debut of ChatGPT has spurred significant scholarship analyzing its potential benefits and consequences in language teaching and learning. However, limited empirical research on factors influencing language learners’ use or non-use of ChatGPT exists. From an ecological theoretical perspective, an understanding of this (non)usage is nevertheless essential: a nuanced understanding of if, how, and why language learners use these tools is necessary to craft meaningful approaches to ChatGPT and other similar generative AI tools in the language classroom. To address this gap, the current article reports on an online survey of 173 learners of non-English languages at a large public university in the United States. Survey data were analyzed using descriptive statistics and iterative qualitative coding (e.g., thematic analysis). Analysis revealed a large majority of participants (74%) elected not to use ChatGPT in their language learning. The article subsequently explores the factors that influenced this non-use, namely policies; concerns about ethics both inside and outside the language classroom (e.g., concerns about cheating, intellectual theft, and questions of fairness); beliefs about tool limitations; considerations of the potential negative impacts on language learning; and reflections on education more broadly. We discuss the implications of these findings in relation to the role of digital literacies in language education; the production of knowledge in education; and the meaning of language study, including actionable items in the language classroom.

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Publication Details

Journal
Technology in Language Teaching & Learning
Published
2024-10-25
DOI
https://doi.org/10.29140/tltl.v6n3.1741
Citations
9
Primary Topic
Text Readability and Simplification
Type
article
Field-Weighted Citation Impact
3.13
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article

ChatGPT in language education: Centering learner voices

Emily A. Hellmich, Kimberly Vinall, S Chen, Zara M. Brandt et al.
9 citations
Technology in Language Teaching & Learning
Text Readability and Simplification
3.13
article

ChatGPT in language education: Centering learner voices

Emily A. Hellmich, Kimberly Vinall, S Chen, Zara M. Brandt, Madelyn M. Sparks
article en
9 citations

Abstract

Within educational linguistics and applied language studies, the debut of ChatGPT has spurred significant scholarship analyzing its potential benefits and consequences in language teaching and learning. However, limited empirical research on factors influencing language learners’ use or non-use of ChatGPT exists. From an ecological theoretical perspective, an understanding of this (non)usage is nevertheless essential: a nuanced understanding of if, how, and why language learners use these tools is necessary to craft meaningful approaches to ChatGPT and other similar generative AI tools in the language classroom. To address this gap, the current article reports on an online survey of 173 learners of non-English languages at a large public university in the United States. Survey data were analyzed using descriptive statistics and iterative qualitative coding (e.g., thematic analysis). Analysis revealed a large majority of participants (74%) elected not to use ChatGPT in their language learning. The article subsequently explores the factors that influenced this non-use, namely policies; concerns about ethics both inside and outside the language classroom (e.g., concerns about cheating, intellectual theft, and questions of fairness); beliefs about tool limitations; considerations of the potential negative impacts on language learning; and reflections on education more broadly. We discuss the implications of these findings in relation to the role of digital literacies in language education; the production of knowledge in education; and the meaning of language study, including actionable items in the language classroom.

Technology in Language Teaching & LearningVol. 6(3)
University of California, Berkeley (US)
Quality Education
Openalex Percentile: Top 7%
Text Readability and Simplification
3.13
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