A Bibliometric Analysis of Deep Learning-Based Reading Instruction Models for EFL Students (2015–2025)

Authors

  • Ignatius Javier Couturier Tuerah

    English Education Department, Universitas Negeri Manado, Tondano 95618, Indonesia
  • Gladly Caren Rorimpandey

    Department of Engineering, Universitas Negeri Manado, Tondano 95618, Indonesia
  • Prycilia Pingkan Mamuja

    Department of Public Health, Universitas Negeri Manado, Tondano 95618, Indonesia
  • Jeane Tuilan

    English Education Department, Universitas Negeri Manado, Tondano 95618, Indonesia
  • Ni Wayan Surya Mahayanti

    Department of Foreign Language, Universitas Pendidikan Ganesha, Singaraja 81116, Indonesia

DOI:

https://doi.org/10.30564/fls.v7i12.11412
Received: 31 July 2025 | Revised: 28 October 2025 | Accepted: 30 October 2025 | Published Online: 21 November 2025

Abstract

This study presents a bibliometric analysis of research on deep learning (DL)-based reading instruction models for English as a Foreign Language (EFL) learners published between 2015 and 2025. The rapid advancement of DL technologies has reshaped instructional strategies in language education, comprehensive insights into their application in EFL reading remain limited. The study aims to map global research trends, identify influential authors and sources, examine collaborative networks, and explore thematic development in the field. Data were retrieved from the Dimensions AI database using targeted keyword searches and analyzed with VOS viewer. Results indicate a sharp increase in publications after 2019, with emphasis on classroom applications, such as personalized learning, feedback, and student motivation. Highly cited works appeared in interdisciplinary journals, including Sustainability and Computers & Education: Artificial Intelligence. Co-authorship analysis revealed strong regional clusters in China, the United Kingdom, and Southeast Asia, while Indonesia emerged as a growing contributor with limited international collaboration. Keyword co-occurrence analysis highlighted dominant themes including assessment, self-efficacy, and integration. Despite rising research interest, significant gaps remain in localized applications and accessibility of DL tools in developing contexts. The findings underscore the need for Indonesia to strengthen its research presence by developing scalable, culturally relevant DL models and fostering international partnerships. This study contributes to the field by offering a comprehensive overview of scholarly development and by identifying future directions for AI-supported reading instruction in EFL education.

Keywords:

Deep Learning; Reading Instruction; EFL Learners; Bibliometric Analysis

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Couturier Tuerah, I. J., Rorimpandey, G. C., Mamuja, P. P., Tuilan, J., & Mahayanti, N. W. S. (2025). A Bibliometric Analysis of Deep Learning-Based Reading Instruction Models for EFL Students (2015–2025). Forum for Linguistic Studies, 7(12), 1531–1548. https://doi.org/10.30564/fls.v7i12.11412

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Copyright © 2025 Ignatius Javier Couturier Tuerah, Gladly Caren Rorimpandey, Prycilia Pingkan Mamuja, Jeane Tuilan, Ni Wayan Surya Mahayanti

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