TRENDS IN ARTIFICIAL INTELLIGENCE-INFUSED ENGLISH LANGUAGE LEARNING - A COMPREHENSIVE BIBLIOMETRIC AND CONTENT REVIEW

Oct 15, 2026

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This paper delivers a systematic review of artificial intelligence-infused English language learning research, combining bibliometric mapping with descriptive content analysis to identify knowledge gaps and future directions. Data from the Scopus database cover publications from 1996 to 2024; results show a peak in 2024 (107 articles), with China leading in citations and output and most work published in an emerging technologies journal. Content analysis of 2014–2024 studies indicates that targeted gap addressing can improve AI integration while supporting student involvement through mobile learning.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages17

Reading Time43 min

AccessFree to download

Abstract

Introduction

Methodology and Data Sources

Bibliometric Findings

Content Analysis Results

Implications and Research Gaps

TRENDS IN ARTIFICIAL INTELLIGENCE-INFUSED ENGLISH LANGUAGE LEARNING: A COMPREHENSIVE BIBLIOMETRIC AND CONTENT REVIEW Sri Wahyuni, 1 Doctoral Student of Language Education Science Department , Universitas Negeri Yogyakarta , Indonesia Senior Lecturer of English Language Education Department, Universitas Islam Riau, Indonesia [sriwahyuni.2023@student.uny.ac.id](sriwahyuni.2023@student.uny.ac.id) , [wahyunis@edu.uir.ac.id](wahyunis@edu.uir.ac.id)[ ](wahyunis@edu.uir.ac.id)[ORCID](ORCID: 0000000265338294)[: 0000000265338294](ORCID: 0000000265338294) Nur Hidayanto Pancoro Setyo Putro,2 Professor of Language Education Science Department , Universitas Negeri Yogyakarta , Indonesia[nur_hidayanto@uny.ac.id](nur_hidayanto@uny.ac.id) [ORCID](ORCID: 0000000230198498)[: 0000000230198498](ORCID: 0000000230198498) Anwar Efendi,3 Professor of Language Education Science Department , Universitas Negeri Yogyakarta , Indonesia [anwar@uny.ac.id](anwar@uny.ac.id) ORCID: 0000000242650496 Abstract. Notwithstanding the increase in research on artificial intelligence-infused English language learning, several issues remain inadequately addressed. Thus, this paper provides a systematic review and analyzes previous studies to pinpoint fruitful knowledge gaps and outline approaches for future research directions. Two approaches, bibliometric and descriptive content analysis, were employed in this study. Firstly, we extracted data for bibliometric analysis from the Scopus database, covering publications from 1996 to 2024. The findings show that the topic peaked in 2024, with 107 articles published. China was the most cited country, with 1.215 citations, and the most productive country, with 327 articles. The International Journal of Emerging Technologies in Learning published the majority of the articles. The research theme evolved to emphasize English learning and student involvement through mobile learning. We applied descriptive content analysis to selected papers published between 2014 and 2024. Theoretically, the findings suggest that addressing knowledge gaps can enhance the integration of artificial intelligence in English language learning. Empirically, the mixed studies used descriptive statistics collected through observation and questionnaires, with a medium sample size selected through 1 Corresponding author, responsible for conceptualization, data analysis, and writing an original draft. 2 Co-author, responsible for data analysis and review. 3 Co-author, responsible for methodology and review. random sampling, a commonly used research design. These approaches can potentially expand the scholarly literature on this subject. Keywords: AI-driven language instruction, English foreign language learning, Knowledge mapping, Literature review, Pedagogical strategies. 1. INTRODUCTION Artificial intelligence (henceforth AI) has been increasingly integrated into educational settings in recent years (Afzaal et al. , 2024; Akhmadieva et al. , 2024) , including English language learning (Hockly, 2023; X. Zhang & Umeanowai, 2024) . This growing use of AI in language education represents a shift towards more flexible and customized learning environments, which enhance language learning to better meet students' needs (Király, 2024) . As a 'rising star' in the field of technology-enhanced language learning, numerous studies have reported the positive impact of AI on improving English language competence. For instance, AI writing tools like ChatGPT can assist students in creating content and offer recommendations for improved sentence structures and word choices (Algaraady & Mahyoob, 2023; Yan, 2023) . Similarly, in terms of enhancing speaking competence, AI’s role in speaking activities has been shown to increase students' speaking skills (Fathi et al. , 2024; Mohamed & Alian, 2023; Yang, 2024) . In other words, AI-infused English language learning has the potential to significantly boost students' language skills and contribut

FAQs

What methods does the paper use to review AI-infused English language learning research?

It applies bibliometric analysis using Scopus data and descriptive content analysis on selected papers published between 2014 and 2024.

What does the bibliometric analysis reveal about research trends from 1996 to 2024?

The topic peaks in 2024 with 107 articles. China is the most cited and most productive country, and the International Journal of Emerging Technologies in Learning publishes the majority of articles.

What future research needs are identified by the review?

Despite reported benefits, the paper highlights gaps regarding long-term effectiveness, challenges in using AI tools, and holistic integration across diverse educational contexts.

Oct 15, 2026

Uploaded by Đào