A systematic review of research on AI in language education: Current status and future implications

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29_01_10125-73606.pdf (2.97 MB)

Date

2025-01-27

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University of Hawaii National Foreign Language Resource Center
Center for Language & Technology

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29

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1

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1

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29

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Abstract

Given the rapid advancements in artificial intelligence (AI) technologies for language education, this article provides a review of selected empirical studies on artificial intelligence in language education, spanning from 2013 to October 2023. Data for this review were gathered from the Web of Science, Eric ProQuest, Scopus, and five top specialized language education journals. A total of 125 studies met the selection criteria and were analyzed using multiple methodologies, including selected bibliometrics, content analysis, and topic modeling. This article furnishes an up-to-date overview of the current landscape of AI in language education research, emphasizing specific AI technologies, their applications, and their educational impact. The most prevalent AI technologies encompass automated writing evaluation, bots, machine translation, automatic speech recognition, and intelligent systems. The results also reveal frequent utilization of AI to assist students in learning writing and speaking. Extensive discussions about practical implications and outlines for future research directions are provided from multiple perspectives. The evolution of AI necessitates initiatives addressing diversity, equity, and inclusion (DEI) concerns in language education. Future research demands large-scale collaborative efforts with a focus on long-term research and development endeavors.

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Keywords

artificial intelligence, language education, systematic review, topic modeling

Citation

Zhu, M. & Wang, C. (2025). A systematic review of AI in language education: Current status and future implications. Language Learning & Technology, 29(1), 1–29. https://hdl.handle.net/10125/73606

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https://hdl.handle.net/10125/73606

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29

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Volume 29 Number 1, 2025
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