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ERIC Number: EJ1369787
Record Type: Journal
Publication Date: 2022
Pages: 31
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1449-3098
EISSN: EISSN-1449-5554
Available Date: N/A
The Current Research Trend of Artificial Intelligence in Language Learning: A Systematic Empirical Literature Review from an Activity Theory Perspective
Yang, Hongzhi; Kyun, Suna
Australasian Journal of Educational Technology, v38 n5 p180-210 2022
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 AIsupported 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.
Australasian Society for Computers in Learning in Tertiary Education. Ascilite Secretariat, P.O. Box 44, Figtree, NSW, Australia. Tel: +61-8-9367-1133; e-mail: info@ascilite.org.au; Web site: https://ajet.org.au/index.php/AJET
Publication Type: Journal Articles; Information Analyses
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A