A systematic review of conversational AI tools in ELT: Publication trends, tools, research methods, learning outcomes, and antecedents
Wan Yee Winsy Lai, Ju Seong Lee
Abstract
This review analyzed the trends in conversational AI tools in ELT from January 2013 to November 2023. The study examined 32 papers, focusing on publication trends, tool types, research methods, learning outcomes, and factors influencing their use. Findings revealed a gradual increase in publications, with 4 (12%) from 2013 to 2021, 13 (41%) in 2022, and 15 (47%) in 2023. All studies (100%) were conducted in Asian EFL contexts. Among the AI chatbots, Google Assistant (25%) was the most widely used. Quasi-experimental (45%) and cross-section (41%) research designs were commonly employed. Mixed-method (50%) approaches were prevalent for data collection and analysis. Conversational AI yielded positive outcomes in affective (43%) and cognitive skills (41%). The main factors influencing user perceptions or behaviors were individual (47%) and microsystem layers (31%). Future studies should (a) include diverse contexts beyond Asia, (b) consider the use of up-to-date tools (e.g., ChatGPT ), (c) employ rigorous experimental designs, (d) explore behavioral learning outcomes, and (e) investigate broader environmental factors. The systematic review enhances current knowledge of recent research trends, identifies environmental factors influencing conversational AI tools concentrating in ELT, and provides insights for future research and practice in this rapidly evolving field.