Language teacher AI literacy: insights from collaborations with ChatGPT

Abstract The transformative potential of generative artificial intelligence (GenAI) in language education highlights the importance of AI literacy among teachers to ensure its ethical and effective integration into teaching practices. Although studies have examined the application of AI in language education, there is a lack of comprehensive reviews focusing on the interaction between language teachers and ChatGPT, a GenAI tool, particularly in fostering human–AI collaboration within educational contexts. This review addresses this gap by synthesising findings from empirical studies. The Scopus database was used as the primary source for this review. A total of 19 journal articles, published between 2023 and 2024, were identified. The review first analyses the research participants and research methods of the selected studies. Key themes are organised into five dimensions: AI foundations and applications, AI ethics, a human-centred mindset, AI pedagogy and AI for professional development, which are derived from the framework proposed by Miao and Cukurova (2024. AI competency Framework for teachers . Paris, France: UNESCO). This review adopts their framework as an analytical lens for evaluating both the opportunities and challenges associated with integrating ChatGPT into language education. The findings highlight the importance of a balanced approach to AI integration to safeguard educational integrity. By offering actionable insights for teachers, curriculum designers and policymakers, this review presents a roadmap for the responsible adoption of AI in language education, ensuring that teachers remain central to the learning process.

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Publication Details

Journal
Journal of China Computer-Assisted Language Learning
Published
2025-04-24
DOI
https://doi.org/10.1515/jccall-2024-0030
Citations
8
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
13.55
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article

Language teacher AI literacy: insights from collaborations with ChatGPT

Weiming Liu
8 citations
Journal of China Computer-Assisted Language Learning
Online Learning and Analytics
13.55
article

Language teacher AI literacy: insights from collaborations with ChatGPT

Weiming Liu
article en
8 citations

Abstract

Abstract The transformative potential of generative artificial intelligence (GenAI) in language education highlights the importance of AI literacy among teachers to ensure its ethical and effective integration into teaching practices. Although studies have examined the application of AI in language education, there is a lack of comprehensive reviews focusing on the interaction between language teachers and ChatGPT, a GenAI tool, particularly in fostering human–AI collaboration within educational contexts. This review addresses this gap by synthesising findings from empirical studies. The Scopus database was used as the primary source for this review. A total of 19 journal articles, published between 2023 and 2024, were identified. The review first analyses the research participants and research methods of the selected studies. Key themes are organised into five dimensions: AI foundations and applications, AI ethics, a human-centred mindset, AI pedagogy and AI for professional development, which are derived from the framework proposed by Miao and Cukurova (2024. AI competency Framework for teachers . Paris, France: UNESCO). This review adopts their framework as an analytical lens for evaluating both the opportunities and challenges associated with integrating ChatGPT into language education. The findings highlight the importance of a balanced approach to AI integration to safeguard educational integrity. By offering actionable insights for teachers, curriculum designers and policymakers, this review presents a roadmap for the responsible adoption of AI in language education, ensuring that teachers remain central to the learning process.

Journal of China Computer-Assisted Language LearningVol. 5(2)
Dublin City University (IE)
Openalex Percentile: Top 2%
Online Learning and Analytics
13.55
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