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

Author:

Yang HongzhiORCID,Kyun Suna

Abstract

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. Implications for practice or policy: Research on AI-supported language learning should view teacher and students as active agents in interacting with technology and making transformations in real life learning situations. More research should focus on productive dialogue and communication in AI-supported language learning with collaborative design. A mixed module of AI-supported language learning and formal teacher instruction should be incorporated in pedagogical design.

Publisher

Australasian Society for Computers in Learning in Tertiary Education

Subject

Education

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3