The role of self‐regulated learning in modelling the relationships between learning approaches, FoMO and smartphone addiction among university students

心理学 上瘾 教育技术 应用心理学 互联网隐私 计算机科学 多媒体 数学教育 神经科学
作者
Deniz Mertkan Gezgin,Tuğba Türk Kurtça,Can Mıhcı,Chung‐Ying Lin,Mark D. Griffiths
出处
期刊:British Journal of Educational Technology [Wiley]
卷期号:56 (6): 2296-2320 被引量:4
标识
DOI:10.1111/bjet.13572
摘要

Smartphone addiction (SA) has become a pervasive issue among university students. Therefore, it is important to better understand the conditions under which SA develops. Previous studies indicate that fear of missing out (FoMO), a psychological barrier to behavioural self‐regulation, is often associated with SA risk. In the pedagogical context, poor self‐regulation may manifest as lack of self‐regulated learning skills (SRLSs), which may, in turn, be associated with the adoption of a superficial approach to learning tasks. Therefore, the aim of the present study was to examine and model the associations between deep and surface learning approaches, SRLSs, SA and FoMO among university students. The sample comprised 687 university students, and structural equation modelling (SEM) was used to analyse the data. The results indicated that SLRSs were positively associated with deep learning, and negatively associated with surface learning. It was also shown that higher SRLSs were associated with lower risk of FoMO and SA. However, while SRLSs may help reduce the level of SA among surface learners by helping them overcome FoMO, the same may not be said for students with a deep learning approach, whose reduced risk of SA due to higher SRLSs was not explained through FoMO. Based on the findings, interventions that aim to improve SRLSs appear warranted, as these may help reduce SA. Practitioner Notes What is already known about this topic Fear of missing out (FoMO) is commonly associated with smartphone addiction (SA) risk. Smartphone notifications disrupt the learning activities of surface learners and FoMO may be the reason. FoMO is considered to be a challenge for behavioural self‐regulation. What this paper adds Higher levels of self‐regulated learning skills (SRLSs) are associated with deeper approaches to learning. Although a deeper approach to learning is associated with lower SA risk, a reduction in FoMO is irrelevant in explaining this effect. As far as surface learners are concerned, better SRLSs are associated with FoMO but are not associated with lower SA risk. Implications for practice and/or policy For deep learners, interventions that support the development of SRLSs are advised because these are important not only for fostering a deep approach to learning but also for helping reduce the risk of SA. Further research is necessary to identify the underlying mechanism by which improved SRLSs are associated with lower SA risk among deep learners. Further research is necessary to identify factors other than FoMO that may be associated with SA risk among surface learners.
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
1秒前
shiyaouao发布了新的文献求助10
2秒前
小闫同学完成签到 ,获得积分10
2秒前
3秒前
微笑向卉发布了新的文献求助10
3秒前
张冰发布了新的文献求助30
3秒前
5秒前
HThree完成签到 ,获得积分10
6秒前
7秒前
7秒前
7秒前
江城完成签到,获得积分10
7秒前
游01发布了新的文献求助10
8秒前
chengzugen发布了新的文献求助10
11秒前
11秒前
Altria完成签到,获得积分10
11秒前
赖炫芬发布了新的文献求助10
13秒前
隐形曼青应助peppa采纳,获得10
14秒前
shiyaouao发布了新的文献求助10
15秒前
HMSCC完成签到,获得积分10
15秒前
15秒前
毛驴发布了新的文献求助10
15秒前
16秒前
徐亚楠发布了新的文献求助10
16秒前
ding应助FunF采纳,获得10
19秒前
21秒前
科研通AI6.4应助暮叆采纳,获得10
21秒前
科研通AI6.3应助暮叆采纳,获得10
21秒前
科研通AI6.4应助暮叆采纳,获得10
21秒前
香蕉觅云应助暮叆采纳,获得10
21秒前
科研通AI6.3应助暮叆采纳,获得10
21秒前
英吉利25发布了新的文献求助10
21秒前
搜集达人应助暮叆采纳,获得10
22秒前
汉堡包应助暮叆采纳,获得10
22秒前
无花果应助Luo采纳,获得30
22秒前
科研通AI6.3应助暮叆采纳,获得10
22秒前
酷波er应助暮叆采纳,获得10
22秒前
23秒前
chengzugen完成签到,获得积分10
27秒前
香蕉觅云应助Lulu采纳,获得10
31秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Nondestructive Testing Handbook: Vol. 4, Thermal and Infrared Testing (IR), 4th ed 800
作者名:Kristopher P. Plain,悉尼大学的,目前只能查到其四篇论文,想找到其博士论文 590
Évora na Idade Média 555
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Radical Reactions 500
Stratospheric Ozone: A Textbook 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7353868
求助须知:如何正确求助?哪些是违规求助? 8964879
关于积分的说明 19046738
捐赠科研通 7002243
什么是DOI,文献DOI怎么找? 3221808
关于科研通互助平台的介绍 2386204
邀请新用户注册赠送积分活动 2202542