Application of generative artificial intelligence (GenAI) in language teaching and learning: A scoping literature review

生成语法 人工智能 计算机科学 心理学
作者
Locky Law
出处
期刊:Computers and education open [Elsevier BV]
卷期号:6: 100174-100174 被引量:21
标识
DOI:10.1016/j.caeo.2024.100174
摘要

This scoping literature review examines the application of Generative Artificial Intelligence (GenAI), a disruptive technology, in language teaching and learning. Since its launch in November 2022, GenAI has captured global attention with OpenAI's ChatGPT, powered by the generative pre-trained transformer-3 (GPT-3) large-language model. The emergence of GenAI holds immense implications across various domains, including language education. This review aims to provide an overview of the current state of research and identify research gaps and future directions in this emerging field. The review follows the PRISMA-ScR guidelines and includes eligible publications published between 2017 and July 2023. Four electronic databases were searched and 41 of the 224 initial papers were eventually selected for review. The findings reveal key terms related to GenAI in language education, the most researched language study and education levels, areas of research, attitudes towards GenAI, and the potential benefits and challenges of GenAI application. The review highlights several research gaps, including the need for more empirical studies to assess the effectiveness and impact of GenAI tools, discussion of ethical considerations, targeted interventions for specific language skills, and stakeholder engagement in responsible integration. Educators are encouraged to incorporate GenAI tools into their teaching practices while remaining vigilant about potential risks. Continuous professional development for educators is crucial to ensure informed decision-making and effective integration of GenAI tools. This scoping review contributes to the existing knowledge on the use of GenAI in language education and informs future research and practice in this disruptive and rapidly evolving field.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
persist发布了新的文献求助10
刚刚
沧海云完成签到 ,获得积分10
1秒前
无敌的裤衩完成签到 ,获得积分20
1秒前
2秒前
科研通AI5应助4645采纳,获得10
3秒前
Hosea完成签到 ,获得积分10
4秒前
畅快的饼干完成签到 ,获得积分10
5秒前
叶子兮完成签到,获得积分10
9秒前
科研通AI5应助DrDaiJune采纳,获得10
10秒前
淡然冬灵完成签到,获得积分10
10秒前
xcwy完成签到,获得积分10
11秒前
Ljc完成签到,获得积分10
11秒前
你说完成签到,获得积分10
13秒前
在郑州完成签到,获得积分10
14秒前
carly完成签到 ,获得积分10
14秒前
kaka完成签到,获得积分10
14秒前
16秒前
逍遥呱呱完成签到 ,获得积分10
19秒前
Star完成签到,获得积分10
19秒前
Hey完成签到 ,获得积分10
19秒前
科研通AI5应助含蓄采纳,获得10
20秒前
高大的战斗机完成签到,获得积分10
22秒前
混子发布了新的文献求助10
23秒前
Jasper应助着急的柔采纳,获得10
23秒前
忆韶完成签到,获得积分10
24秒前
奥特斌完成签到 ,获得积分10
24秒前
科研人员完成签到 ,获得积分10
25秒前
yiluyouni完成签到,获得积分10
25秒前
sonicgoboy完成签到,获得积分10
26秒前
小惠完成签到,获得积分10
28秒前
开心绿柳完成签到,获得积分10
29秒前
29秒前
含蓄完成签到,获得积分10
29秒前
29秒前
玩命做研究完成签到 ,获得积分20
29秒前
31秒前
半颗橙子完成签到 ,获得积分10
32秒前
mufulee完成签到,获得积分10
33秒前
着急的柔完成签到,获得积分10
33秒前
LIU完成签到,获得积分10
34秒前
高分求助中
All the Birds of the World 4000
Production Logging: Theoretical and Interpretive Elements 3000
Les Mantodea de Guyane Insecta, Polyneoptera 2000
Machine Learning Methods in Geoscience 1000
Resilience of a Nation: A History of the Military in Rwanda 888
Evaluating the Cardiometabolic Efficacy and Safety of Lipoprotein Lipase Pathway Targets in Combination With Approved Lipid-Lowering Targets: A Drug Target Mendelian Randomization Study 500
Crystal Nonlinear Optics: with SNLO examples (Second Edition) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3733511
求助须知:如何正确求助?哪些是违规求助? 3277654
关于积分的说明 10003735
捐赠科研通 2993737
什么是DOI,文献DOI怎么找? 1642806
邀请新用户注册赠送积分活动 780644
科研通“疑难数据库(出版商)”最低求助积分说明 748944