Effect of chatbot‑assisted language learning: A meta‑analysis

Shunan Zhang; Cheng Shan; John Sie Yuen Lee; ShaoPeng Che; Jang Hyun Kim

doi:10.1007/s10639-023-11805-6

Effect of chatbot‑assisted language learning: A meta‑analysis

Shunan Zhang, Cheng Shan, John Sie Yuen Lee, ShaoPeng Che, Jang Hyun Kim^*

^*Corresponding author for this work

Department of Linguistics and Translation

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

43 Citations (Scopus)

Abstract

Chatbots have shown great potential for language learning. However, previous studies have reported mixed results on the efficiency of chatbot-assisted language learning (CALL). This study integrated the results of previous experimental studies on CALL by using meta-analysis to explore its effectiveness. A total of 61 samples from 18 studies were examined. The results showed that CALL had a moderate average effect (g = .527). In addition, nine potential moderating variables (educational level, target language, language domain, learning outcome, instruction duration, chatbot interface, chatbot development, task dominance, and interaction way) were identified and discussed. The results of this study provided insights into the use and design of chatbots for language learning.

© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023

Original language	English
Pages (from-to)	15223–15243
Journal	Education and Information Technologies
Volume	28
Issue number	11
Online published	26 Apr 2023
DOIs	https://doi.org/10.1007/s10639-023-11805-6
Publication status	Published - Nov 2023

Research Keywords

Chatbots
Language Learning
Meta-analysis

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10.1007/s10639-023-11805-6

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Cite this

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title = "Effect of chatbot‑assisted language learning: A meta‑analysis",

abstract = "Chatbots have shown great potential for language learning. However, previous studies have reported mixed results on the efficiency of chatbot-assisted language learning (CALL). This study integrated the results of previous experimental studies on CALL by using meta-analysis to explore its effectiveness. A total of 61 samples from 18 studies were examined. The results showed that CALL had a moderate average effect (g = .527). In addition, nine potential moderating variables (educational level, target language, language domain, learning outcome, instruction duration, chatbot interface, chatbot development, task dominance, and interaction way) were identified and discussed. The results of this study provided insights into the use and design of chatbots for language learning.{\textcopyright} The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023",

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AU - Shan, Cheng

AU - Lee, John Sie Yuen

AU - Che, ShaoPeng

AU - Kim, Jang Hyun

PY - 2023/11

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N2 - Chatbots have shown great potential for language learning. However, previous studies have reported mixed results on the efficiency of chatbot-assisted language learning (CALL). This study integrated the results of previous experimental studies on CALL by using meta-analysis to explore its effectiveness. A total of 61 samples from 18 studies were examined. The results showed that CALL had a moderate average effect (g = .527). In addition, nine potential moderating variables (educational level, target language, language domain, learning outcome, instruction duration, chatbot interface, chatbot development, task dominance, and interaction way) were identified and discussed. The results of this study provided insights into the use and design of chatbots for language learning.© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023

AB - Chatbots have shown great potential for language learning. However, previous studies have reported mixed results on the efficiency of chatbot-assisted language learning (CALL). This study integrated the results of previous experimental studies on CALL by using meta-analysis to explore its effectiveness. A total of 61 samples from 18 studies were examined. The results showed that CALL had a moderate average effect (g = .527). In addition, nine potential moderating variables (educational level, target language, language domain, learning outcome, instruction duration, chatbot interface, chatbot development, task dominance, and interaction way) were identified and discussed. The results of this study provided insights into the use and design of chatbots for language learning.© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023

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