Exploring AI-mediated informal digital learning of English (AI-IDLE): a mixed-method investigation of Chinese EFL learners’ AI adoption and experiences

计算机科学 数学教育 闲置 教学方法 语言学 心理学 自然语言处理 人工智能 多媒体 操作系统 哲学
作者
Guangxiang Liu,Ron Darvin,Chaojun Ma
出处
期刊:Computer Assisted Language Learning [Routledge]
卷期号:38 (7): 1632-1660 被引量:198
标识
DOI:10.1080/09588221.2024.2310288
摘要

Recent advancements in natural language processing and large language models have ushered language learning into the age of artificial intelligence (AI).Recognizing the affordances of generative AI tools, this paper aims to examine the degree to which L2 learners accepted and leveraged large language model platforms (e.g.ChatGPT, Bing Chat) for the informal digital learning of English (IDLE) purposes.Employing an explanatory sequential mixed-method design, this study draws on the technology acceptance model (TAM) and collects data via an adapted TAM questionnaire and an interview guide.A total of 867 Chinese EFL (English as a foreign language) learners answered the online survey, while 20 attended the post-survey interviews.Drawing on a validated structural model that elucidates the inter-factor relationships of perceived ease of use, perceived usefulness, intention to use, and actual use, the quantitative analysis provides statistical accounts for EFL learners' adoption of Generative Pre-trained Transformer (GPT) technologies.The qualitative findings, derived from the interview data, reveal three key themes: (1) how perceived usefulness of chatbots for IDLE emerges from hands-on experimentation with these tools; (2) how intention to use increases as learners negotiate chatbot affordances and constraints; and (3) how actual use of chatbots for IDLE involves using these tools as tutors or conversation partners.Connections between quantitative and qualitative findings enhance our understanding of how EFL learners negotiate the affordances and constraints of highly capable AI technologies to participate in creative IDLE practices.By understanding these practices, this study draws attention to the attitudes and practices that constitute AI literacies, ultimately offering implications for future classroom practices and research.
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
斯文败类的应助被谦让的口红采纳,获得10
2秒前
爆米花的应助被Arw采纳,获得10
6秒前
维西西完成签到 ,获得积分10
7秒前
mo完成签到 ,获得积分10
8秒前
森海完成签到,获得积分10
9秒前
nn发布了新的文献求助10
13秒前
hyk发布了新的文献求助10
13秒前
xxxxx完成签到,获得积分10
16秒前
曾恒敬完成签到,获得积分10
17秒前
郭志倩完成签到 ,获得积分10
17秒前
科研通AI6.4的应助被积极咖啡采纳,获得10
23秒前
秋风的应助被1351567822采纳,获得40
25秒前
cosin关注了科研通微信公众号
25秒前
25秒前
25秒前
27秒前
28秒前
30秒前
尤珩发布了新的文献求助10
32秒前
叶溪云发布了新的文献求助10
32秒前
科研通AI6.2的应助被二二春采纳,获得10
33秒前
34秒前
FF完成签到,获得积分10
35秒前
皮卡丘完成签到 ,获得积分0
37秒前
俭朴的跳跳糖完成签到 ,获得积分10
40秒前
41秒前
44秒前
852的应助被QRhahaha采纳,获得10
44秒前
47秒前
47秒前
聪慧哈密瓜完成签到 ,获得积分10
49秒前
49秒前
49秒前
50秒前
秋风的应助被xm采纳,获得40
51秒前
研友_VZG7GZ的应助被是诚心采纳,获得10
53秒前
53秒前
星星发布了新的文献求助50
55秒前
56秒前
cosin发布了新的文献求助10
57秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Rosenblum, Global Change Biology 800
Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB 600
Organizational Behavior 510
Management and the Arts 510
Production Logging: Theoretical and Interpretive Elements 400
CLSI C56QG Examples of Hemolyzed, Icteric, and Lipemic/Turbid Samples Quick Guide 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7816306
求助须知:如何正确求助?哪些是违规求助? 9345395
关于积分的说明 20529565
捐赠科研通 7408874
什么是DOI,文献DOI怎么找? 3331194
关于科研通互助平台的介绍 2477684
邀请新用户注册赠送积分活动 2350905