The current research trend of artificial intelligence in language learning: A systematic empirical literature review from an activity theory perspective
Citations

WEB OF SCIENCE

60
Citations

SCOPUS

90

초록

Although the field of artificial intelligence (AI) has rapidly developed, there has been little research to review, describe, and analyse the trends and development of empirical research on AI-supported language learning. This paper selected and analysed 25 empirical research papers on AI-supported language learning published in the last 15 years. These empirical studies were analysed using the activity theory from seven constituents: tool, subject, object, rules, community, division of labour, and outcome. A key contribution of this paper is the use of activity theory to illustrate the dynamic interactions and contradictions between the seven elements. AI-supported technology as a mediating tool demonstrated some effectiveness in language learning but needs further improvement in the use of language for communication and collaborative design. We argue that teachers’ intervention and configuration of AI-supported language learning in the pedagogical design plays an important role in the effectiveness of learning. More research is needed to explore the use of AI-supported language learning in the classroom or the real-life learning context.

키워드

Activity theoryAi-supported language learningArtificial intelligenceEmpirical literature reviewLanguage learningLanguage teachingCONVERSATIONAL AGENTTECHNOLOGYFUTURECOMPREHENSIONDIALOGUEFEEDBACKMODELAI
제목
The current research trend of artificial intelligence in language learning: A systematic empirical literature review from an activity theory perspective
저자
Yang, HongzhiKyun, Suna
DOI
10.14742/ajet.7492
발행일
2022-12
저널명
Australasian Journal of Educational Technology
38
5
페이지
180 ~ 210