Conversational agents in language learning

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....

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Main Authors: Xiao Feiwen, Zhao Priscilla, Sha Hanyue, Yang Dandan, Warschauer Mark
Format: Article
Language:English
Published: De Gruyter 2023-03-01
Series:Journal of China Computer-Assisted Language Learning
Subjects:
Online Access:https://doi.org/10.1515/jccall-2022-0032
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author Xiao Feiwen
Zhao Priscilla
Sha Hanyue
Yang Dandan
Warschauer Mark
author_facet Xiao Feiwen
Zhao Priscilla
Sha Hanyue
Yang Dandan
Warschauer Mark
author_sort Xiao Feiwen
collection DOAJ
description 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.
format Article
id doaj-art-71983811efde46e4ab733c5016516775
institution Kabale University
issn 2748-3479
language English
publishDate 2023-03-01
publisher De Gruyter
record_format Article
series Journal of China Computer-Assisted Language Learning
spelling doaj-art-71983811efde46e4ab733c50165167752025-01-20T11:08:49ZengDe GruyterJournal of China Computer-Assisted Language Learning2748-34792023-03-014230032510.1515/jccall-2022-0032Conversational agents in language learningXiao Feiwen0Zhao Priscilla1Sha Hanyue2Yang Dandan3Warschauer Mark4Pennsylvania State University, State College, PA, USAStanford University, Stanford, CA, USAColumbia University, New York City, NY, USABoston College, Boston, MA, USAUniversity of California, Irvine, USADue 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.https://doi.org/10.1515/jccall-2022-0032callconversational agentslanguage learningnatural language processing (nlp)technology
spellingShingle Xiao Feiwen
Zhao Priscilla
Sha Hanyue
Yang Dandan
Warschauer Mark
Conversational agents in language learning
Journal of China Computer-Assisted Language Learning
call
conversational agents
language learning
natural language processing (nlp)
technology
title Conversational agents in language learning
title_full Conversational agents in language learning
title_fullStr Conversational agents in language learning
title_full_unstemmed Conversational agents in language learning
title_short Conversational agents in language learning
title_sort conversational agents in language learning
topic call
conversational agents
language learning
natural language processing (nlp)
technology
url https://doi.org/10.1515/jccall-2022-0032
work_keys_str_mv AT xiaofeiwen conversationalagentsinlanguagelearning
AT zhaopriscilla conversationalagentsinlanguagelearning
AT shahanyue conversationalagentsinlanguagelearning
AT yangdandan conversationalagentsinlanguagelearning
AT warschauermark conversationalagentsinlanguagelearning