Digital learning of English as a foreign language among university students: How are approaches to learning linked to digital competence and technostress?

科技压力 心理学 玩世不恭 能力(人力资源) 数学教育 社会心理学 政治学 政治 精神科 法学
作者
Liwei Niu,Xinghua Wang,Matthew P. Wallace,Hui Pang,Yanping Xu
出处
期刊:Journal of Computer Assisted Learning [Wiley]
卷期号:38 (5): 1332-1346 被引量:18
标识
DOI:10.1111/jcal.12679
摘要

Abstract Background In view of the widespread use of digital technologies in English as a foreign language (EFL) learning and the importance of students' approaches to learning (SAL) and digital competence, as well as the threats of technostress in digital settings, digital EFL learning requires a critical examination. Objectives This study sought to investigate the interrelationships among of SAL, students' digital competence, and the emerging technostress in digital learning of EFL. Methods Survey and EFL test data of 477 university students taking EFL courses were collected. Partial least square structural equation modelling and cluster analysis were employed to analyze these data. Results and Conclusions The results indicate that a surface approach to learning was significantly positively associated with technostress while negatively associated with digital competence. The deep and organized learning approaches positively predicted digital competence, which further negatively predicted technostress and burnout in digital learning of EFL. Technostress was found to be positively related to exhaustion and cynicism, with cynicism being negatively related to EFL learning outcomes. The cluster analysis identified three clusters of EFL learners and revealed that, overall, high scores in the deep and organized approaches to learning were generally aligned with strong digital competence, low technostress, low burnout, and high EFL learning outcomes. Takeaways The findings of this study carry important implications for practitioners of EFL learning and teaching in the design of strategies, pedagogies, and EFL learning technologies that improve EFL learning in digital settings while maintaining learners' wellbeing.
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
精明的书白完成签到,获得积分20
4秒前
共享精神应助DavidJin采纳,获得10
5秒前
bc应助电池哥采纳,获得20
10秒前
月夙完成签到,获得积分0
11秒前
勤劳紫青完成签到 ,获得积分10
16秒前
P2JY完成签到,获得积分10
18秒前
吃小孩的妖怪完成签到 ,获得积分10
20秒前
不想看文献完成签到 ,获得积分10
20秒前
摩卡摩卡完成签到,获得积分10
22秒前
23秒前
tahiti关注了科研通微信公众号
23秒前
HR112完成签到 ,获得积分10
23秒前
Sissi完成签到 ,获得积分10
24秒前
动听半雪完成签到,获得积分10
26秒前
周Z完成签到,获得积分10
27秒前
cbq完成签到 ,获得积分10
28秒前
动听半雪发布了新的文献求助10
29秒前
zxt完成签到,获得积分10
33秒前
机智的乌完成签到 ,获得积分10
36秒前
36秒前
neckerzhu完成签到 ,获得积分10
39秒前
bc应助忧心的寄松采纳,获得20
39秒前
tahiti发布了新的文献求助30
39秒前
Snowy周完成签到,获得积分10
39秒前
winni完成签到,获得积分10
39秒前
43秒前
Superman完成签到 ,获得积分10
43秒前
中恐发布了新的文献求助10
43秒前
拼搏的青雪完成签到 ,获得积分10
44秒前
DavidJin完成签到,获得积分20
45秒前
阳光的牛牛完成签到,获得积分10
50秒前
Bob2发布了新的文献求助10
51秒前
灰灰完成签到 ,获得积分10
52秒前
科研通AI2S应助fst采纳,获得10
52秒前
可玩性完成签到 ,获得积分10
56秒前
kyokyoro完成签到,获得积分10
56秒前
心碎的黄焖鸡完成签到 ,获得积分10
58秒前
沐颜完成签到 ,获得积分10
1分钟前
小二郎应助BUAAzmt采纳,获得10
1分钟前
残幻应助Bob2采纳,获得10
1分钟前
高分求助中
【此为提示信息,请勿应助】请按要求发布求助,避免被关 20000
ISCN 2024 – An International System for Human Cytogenomic Nomenclature (2024) 3000
Continuum Thermodynamics and Material Modelling 2000
Encyclopedia of Geology (2nd Edition) 2000
105th Edition CRC Handbook of Chemistry and Physics 1600
Maneuvering of a Damaged Navy Combatant 650
the MD Anderson Surgical Oncology Manual, Seventh Edition 300
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 3777734
求助须知:如何正确求助?哪些是违规求助? 3323199
关于积分的说明 10213148
捐赠科研通 3038520
什么是DOI,文献DOI怎么找? 1667445
邀请新用户注册赠送积分活动 798139
科研通“疑难数据库(出版商)”最低求助积分说明 758275