An NLP-enhanced large-scale review of AI trends and research gaps in English language education
TL;DR
This study examined the ERIC and Scopus databases by examining 856 journal articles and provided several trends, such as keywords, the most cited papers, subject matrices, and geolocations of the articles, as well as several implications for practitioners.
Abstract
Artificial intelligence (AI) tools such as chatbots have become an inseparable part of education with the advancements in large language models. As more studies have been conducted, researchers and practitioners may have challenges in finding the gaps in the literature and/or deciding on which tools are beneficial or not for instruction. These challenges can be addressed with bibliometric reviews that can provide a comprehensive overview of the current trends in AI use in ELT. This study addresses that need with a novel methodology by examining the ERIC and Scopus databases. Using computational data analysis tools and natural language processing, we examined 856 journal articles and provided several trends, such as keywords, the most cited papers, subject matrices, and geolocations of the articles, as well as several implications for practitioners. A key result is that the research on the use of AI tools is increasing substantially, with a clear focus on teaching methods and writing instruction. Our study offers valuable information for the researchers and practitioners who seek techniques to integrate AI tools into language instruction.