MAPPING RESEARCH TRENDS IN TECHNOLOGY-ENHANCED L2 WRITING IN EFL CONTEXTS: A BIBLIOMETRIC ANALYSIS

Abstract This study presents a comprehensive bibliometric and science mapping analysis of research on technology-enhanced second language (L2) writing in English as a Foreign Language (EFL) contexts. Although digital tools and artificial intelligence (AI) have increasingly influenced language education, a systematic understanding of research trends, intellectual structures, and thematic developments in L2 writing remains limited. To address this gap, a dataset of 221 articles published in Social Sciences Citation Index (SSCI)-indexed journals between 2010 and April 2024 was analyzed using VOSviewer and CiteSpace. The findings reveal a steady increase in research output, with major themes centering on automated writing evaluation (AWE), collaborative writing, digital writing environments, and feedback practices. Co-occurrence, co-citation, and burst analyses demonstrate the evolution of thematic clusters and the growing integration of pedagogical, linguistic, and technological perspectives. Emerging topics such as learner autonomy, data-driven learning, and AI-assisted writing tools indicate a shift toward more adaptive, personalized, and learner-centered approaches to writing instruction. Despite these developments, the findings suggest a continuing need for theoretically informed and interpretive research that can better connect innovation with pedagogical practice. Unlike previous reviews that focused on specific journals, technologies, or empirical studies, this study provides a comprehensive mapping of SSCI-indexed research over a fourteen-year period through the combined use of VOSviewer and CiteSpace. By identifying influential contributors, major research themes, and emerging directions, the study offers a valuable reference for researchers and practitioners and proposes a future research agenda for technology-enhanced L2 writing. Keywords: L2 writing, bibliometric analysis, citation patterns, theme clusters, EFL.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-01
DOI
https://doi.org/10.5281/zenodo.22210978
Primary Topic
EFL/ESL Teaching and Learning
Type
article
Field-Weighted Citation Impact
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article

MAPPING RESEARCH TRENDS IN TECHNOLOGY-ENHANCED L2 WRITING IN EFL CONTEXTS: A BIBLIOMETRIC ANALYSIS

Nida Gürbüz
Zenodo (CERN European Organization for Nuclear Research)
EFL/ESL Teaching and Learning
article

MAPPING RESEARCH TRENDS IN TECHNOLOGY-ENHANCED L2 WRITING IN EFL CONTEXTS: A BIBLIOMETRIC ANALYSIS

Nida Gürbüz
article en

Abstract

Abstract This study presents a comprehensive bibliometric and science mapping analysis of research on technology-enhanced second language (L2) writing in English as a Foreign Language (EFL) contexts. Although digital tools and artificial intelligence (AI) have increasingly influenced language education, a systematic understanding of research trends, intellectual structures, and thematic developments in L2 writing remains limited. To address this gap, a dataset of 221 articles published in Social Sciences Citation Index (SSCI)-indexed journals between 2010 and April 2024 was analyzed using VOSviewer and CiteSpace. The findings reveal a steady increase in research output, with major themes centering on automated writing evaluation (AWE), collaborative writing, digital writing environments, and feedback practices. Co-occurrence, co-citation, and burst analyses demonstrate the evolution of thematic clusters and the growing integration of pedagogical, linguistic, and technological perspectives. Emerging topics such as learner autonomy, data-driven learning, and AI-assisted writing tools indicate a shift toward more adaptive, personalized, and learner-centered approaches to writing instruction. Despite these developments, the findings suggest a continuing need for theoretically informed and interpretive research that can better connect innovation with pedagogical practice. Unlike previous reviews that focused on specific journals, technologies, or empirical studies, this study provides a comprehensive mapping of SSCI-indexed research over a fourteen-year period through the combined use of VOSviewer and CiteSpace. By identifying influential contributors, major research themes, and emerging directions, the study offers a valuable reference for researchers and practitioners and proposes a future research agenda for technology-enhanced L2 writing. Keywords: L2 writing, bibliometric analysis, citation patterns, theme clusters, EFL.

Zenodo (CERN European Organization for Nuclear Research)
Necmettin Erbakan University (TR)
Quality Education
Openalex Percentile: Top 3%
EFL/ESL Teaching and Learning
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