Trends, research issues and applications of artificial intelligence in language education

Xinyi HUANG, Di ZOU*, Gary CHENG, Xieling CHEN, Haoran XIE

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review


Artificial Intelligence (AI) plays an increasingly important role in language education; however, the trends, research issues, and applications of AI in language learning remain largely under-investigated. Accordingly, the present paper, using bibliometric analysis, investigates these issues via a review of 516 papers published between 2000 and 2019, focusing on how AI was integrated into language education. Findings revealed that the frequency of studies on AI-enhanced language education increased over the period. The USA and Arizona State University were the most active country and institution, respectively. The 10 most popular topics were: (1) automated writing evaluation; (2) intelligent tutoring systems (ITS) for reading and writing; (3) automated error detection; (4) computer-mediated communication; (5) personalized systems for language learning; (6) natural language and vocabulary learning; (7) web resources and web-based systems for language learning; (8) ITS for writing in English for specific purposes; (9) intelligent tutoring and assessment systems for pronunciation and speech training; and (10) affective states and emotions. The results also indicated that AI was frequently used to assist students in learning writing, reading, vocabulary, grammar, speaking, and listening. Natural language processing, automated speech recognition, and learner profiling were commonly applied to develop automated writing evaluation, personalized learning, and intelligent tutoring systems.
Original languageEnglish
JournalEducational Technology and Society
Issue number1
Early online dateAug 2022
Publication statusE-pub ahead of print - Aug 2022

Bibliographical note

An abstract entitled “Artificial Intelligence in Language Education” based on this paper was presented at the International Conference on Education and Artificial Intelligence 2020, The Education University of Hong Kong, 9-11 November 2020, Hong Kong. Gary Cheng’s work in this research is supported by the Research Cluster Fund (RG 78/2019-2020R) of The Education University of Hong Kong and the Dean’s Research Fund 2019/20 (IDS-2 2020) of The Education University of Hong Kong. Haoran Xie’s work in this research is supported by the Faculty Research Fund (DB21A9) and the Lam Woo Research Fund (LWI20011) of Lingnan
University, Hong Kong.


  • Artificial intelligence
  • Language education
  • Bibliometric analysis
  • Automated writing evaluation
  • Intelligent Tutoring System


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