Integrating Generative AI in Language Education: A Systematic Review of Pedagogical, Ethical, and Technological Themes

Authors

  • Wang Cong
  • Lim Seong Pek
  • Zhang Yuchen
  • Imratul Najwa Abdul Latif
  • Zhou Bo
  • Li Ming

Keywords:

Ethical AI; Generative AI; Inclusivity; Language Education; Personalized Learning

Abstract

Artificial Intelligence (AI) has emerged as a transformative force in language education offering innovative solutions for personalized instruction, real-time feedback, and inclusive learning environments. While several systematic reviews have explored AI in language learning broadly, few have specifically targeted generative AI using a combined Systematic Literature Review (SLR) and Bibliographic Coupling Analysis (BCA). This study fills this gap by synthesizing findings from 19 peer-reviewed articles published between 2020 and 2024 in the Web of Science database, using a dual approach that combines a SLR and Bibliographic Coupling Analysis to explore the educational potential and thematic development of AI in language learning. The review examines how AI facilitates adaptive learning paths, enhances language skills development, supports assessment and teacher roles, improves accessibility for diverse learners, and raises critical ethical and cross-cultural considerations. Using the PRISMA framework to guide the selection and synthesis process, and bibliographic coupling to identify intellectual linkages, the analysis reveals six main research clusters: personalized and adaptive learning, language skill enhancement, AI-driven assessment, inclusivity and accessibility, ethical and critical engagement, and system usability. According to the literature, AI supports learner autonomy, promotes engagement, and addresses various learner needs, although challenges such as digital inequality, algorithmic bias, and over-reliance on technology persist. In alignment with Sustainable Development Goal (SDG) 4: Quality Education, this study underscores the importance of inclusive, ethical, and learner-centred AI integration. Future research should address the long-term impacts of AI in education, ensure equitable access, and balance technological advancement with pedagogical integrity. This review provides practical recommendations for integrating generative AI into language classrooms, highlights the pedagogical opportunities and challenges associated with AI adoption and outlines future research directions related to long-term learning outcomes and equitable AI implementation.

https://doi.org/10.26803/ijlter.25.2.26

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Published

2026-02-28

How to Cite

Cong, W. ., Pek, L. S., Yuchen, Z. ., Latif, I. N. A., Bo, Z. ., & Ming, L. . (2026). Integrating Generative AI in Language Education: A Systematic Review of Pedagogical, Ethical, and Technological Themes. International Journal of Learning, Teaching and Educational Research, 25(2), 577–595. Retrieved from http://www.ijlter.myres.net/index.php/ijlter/article/view/2720