Beyond the Hype: AI Tools in ESL/EFL Classroom - A Bibliometric Analysis of Research Trends, Ethical Implications, and Evidence-Based Pedagogical Practice

Abstract

The rapid proliferation of artificial intelligence tools in ESL/EFL classrooms has generated considerable excitement alongside concerns about unsubstantiated claims and promotional hype. While ChatGPT and similar technologies promise revolutionary changes to English language instruction, the field lacks systematic frameworks for distinguishing evidence-based research from marketing-driven discourse. This study addresses the critical need for quality assessment tools to support informed pedagogical decision-making in ESL/EFL contexts. This bibliometric analysis examined 502 peer-reviewed journal articles (2015-2024) from the Scopus database, focusing on AI applications in ESL/EFL classroom settings. Using an integrated approach combining biblioMagika, Biblioshiny, VOSviewer, and AI-enhanced content analysis tools, publication trends, citation patterns, research methodologies, author affiliations, and claim substantiation patterns were analyzed. The multi-tool methodology enabled comprehensive examination of quantitative bibliometric indicators alongside qualitative content analysis, where terminology evolution, evidence-based practice indicators, and promotional language detection across the decade were examined. The findings revealed distinct patterns between evidence-based research and promotional discourse, with significant implications for technology adoption decisions. The analysis identified key bibliometric indicators that distinguish rigorous, classroom-validated studies from potentially inflated claims. Post-ChatGPT publication patterns (2022-2024) showed dramatic volume increases alongside concerning methodological trends. Geographic and institutional analysis revealed varying research quality standards and commercial influence patterns across different contexts. This study provides ESL/EFL educators and administrators with practical frameworks for evaluating AI research credibility, supporting evidence-based technology adoption decisions while offering concrete tools for moving beyond promotional hype toward genuine pedagogical innovation.

Presenters

Amreet Kaur Jageer Singh
Language Instructor & Researcher, English Language Unit, Centre for Language Competencies, Faculty of Languages and Communication, Sultan Idris Education University, Perak, Malaysia

Details

Presentation Type

Paper Presentation in a Themed Session

Theme

2025 Special Focus: Human Learning and Machine Learning—Challenges and Opportunities for Artificial Intelligence in Education.

KEYWORDS

ARTIFICIAL INTELLIGENCE, ESL, EFL, BIBLIOMETRIC ANALYSIS, EVIDENCE-BASED PRACTICE, EDUCATIONAL TECHNOLOGY, RESEARCH QUALITY, CLASSROOM TECHNOLOGY, TESOL