Conversational agents in language learning
Feiwen Xiao, Priscilla Zhao, Hanyue Sha, Yang Dandan, Mark Warschauer
Abstract
Abstract Due to advances in technology, conversational agents are emerging as intelligent spoken dialogue systems that simulate natural conversation with human beings. A growing body of literature has investigated the potential of conversational agents in enhancing language learning across multiple contexts. In this paper, a broad scoping review examining the current literature on conversational agents and language learning was conducted. This review mapped APA PsycINFO, ERIC and ProQuest Dissertations & Theses databases, which yielded 23 papers for further analysis. Our examination of these papers suggests that there are three main ways in which conversational agents are used for language learning. This review discusses these three approaches and points to directions that require further research to fully exploit the potential of conversational agents in language learning.