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.
endingpage:
29
format.extent:
29
identifier.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
identifier.issn:
1094-3501
identifier.uri:
https://hdl.handle.net/10125/73606
language:
eng
llt.topic:
Review Articles
number:
1
publicationname:
Language Learning & Technology
publisher:
University of Hawaii National Foreign Language Resource Center Center for Language & Technology
rights.license:
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License