Exploring the role of conversational AI in developing communicative skills: A systematic review

Abstract

Conversational AI tools, with their capacity for interactive and dynamic language exchanges, offer promising avenues for enhancing language learning. While the potential of these tools is significant, their application in developing learners’ communicative skills remains relatively under-explored. This study investigates conversational AI tools and their applications in supporting communicative skills development among language learners. To this end, thirty-one studies published between 2010 and December 2024 were systematically reviewed across seven dimensions: (1) tools; (2) languages and skills; (3) theories and pedagogical approaches; (4) research methodologies; (5) mechanisms of employing conversational AI; (6) findings; and (7) challenges. Based on the results, conversation AI tools were categorized into five distinct types: embodied conversational agents (ECAs), speech recognition systems, chatbots, advanced AI-powered chatbots (such as ChatGPT), and general conversational agents. Advanced AI-powered chatbots emerged as the most prevalent type, likely due to their ability for personalized and real-time feedback. English was the most frequently targeted language, with a primary focus on speaking and writing skills. Most studies tended to adopt mixed methodologies, combining quantitative and qualitative techniques. Improvements were observed in learners’ communication skills, alongside increased motivation and autonomy. Methodological limitations, challenges in technological implementation, and ethical considerations emerged as key challenges. This review recognizes the transformational potential of conversational AI in developing students’ communicative skills and recommends strategies for addressing the challenges of scaling up these technologies across diverse language contexts and effectively integrating them into educational practices.

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