Learning with Generative AI (GenAI): A Bibliometric and Synthesis of Equity Issue in English as a Foreign Language (EFL) Learning
DOI:
https://doi.org/10.46328/ijonse.5828Keywords:
GenAI, English as A Foreign Language (EFL), Equity, Bibliometrics, Topic modelling, Genre analysisAbstract
Effective implementation of Generative AI (GenAI) in education requires deeper insights into its implications for equity. This bibliometric and synthesis study investigates studies on GenAI in English as a Foreign Language (EFL) learning through quantitative bibliometric analysis, topic modelling, and mixed method genre analysis. The study maps the publication panorama, identifies research hotspots, and examines how equity issues are addressed in extant studies. Results find a rapidly increasing publication trend since 2022, with key journals, authors, and highly cited works highlighted. Seven dominant research topics are identified through topic modelling and Equity and Access ranks the fifth, suggesting a lack of sufficient attention on the issue. A further analysis of 20 closely equity-related studies revealed that equity-expressions indicating challenges to equity appear more in Literature review and Findings, whereas contributions mostly appear in Introductions. Only one study focuses on equity issue in Methodology section, suggesting that equity is not a central research concern in the literature analyzed. Overall, GenAI in EFL is framed as both opportunities and challenges to equity, but they are only mentioned rather than enquired. The study calls for more explicit attention to equity to ensure a more inclusive integration of GenAI into EFL learning and teaching.
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