A scoping review of voice based AI chatbots in EFL learners’ meaning focused speaking in higher education

Abstract

This scoping review examines the use of voice-based artificial intelligence (AI) chatbots in supporting meaning-focused speaking among English as a Foreign Language (EFL) learners in higher education (HE). In response to the rapid integration of AI technologies in HE, the study aims to map the extent, scope, and methodological characteristics of existing research, identify types of voice-based AI chatbots and meaning-focused speaking tasks, and synthesize key research trends. A scoping review was conducted using predefined criteria across three databases–Scopus, Web of Science, and ProQuest–resulting in the inclusion of 37 studies. The findings indicate that an explanatory mixed-methods experiment-based design was the most prevalent, and voice-enabled general-purpose systems were the most commonly used. Additionally, this study reveals that the majority of empirical reports were associated with learners’ favorable perceptions as well as positive effects both academically and affectively while longitudinal and in-depth investigation into learners’ engagement and motivation was still under-explored. The review concludes with implications and recommendations for future research and pedagogical practice.