| Title: |
The Role of Self-Regulated Learning in Modelling the Relationships between Learning Approaches, FoMO and Smartphone Addiction among University Students |
| Language: |
English |
| Authors: |
Deniz Mertkan Gezgin (ORCID 0000-0003-4688-043X); Tugba Türk Kurtça (ORCID 0000-0002-4361-3769); Can Mihci (ORCID 0000-0001-9393-4619); Chung-Ying Lin (ORCID 0000-0002-2129-4242); Mark D. Griffiths (ORCID 0000-0001-8880-6524) |
| Source: |
British Journal of Educational Technology. 2025 56(6):2296-2320. |
| Availability: |
Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Peer Reviewed: |
Y |
| Page Count: |
25 |
| Publication Date: |
2025 |
| Document Type: |
Journal Articles; Reports - Research |
| Education Level: |
Higher Education; Postsecondary Education |
| Descriptors: |
College Students; Telecommunications; Handheld Devices; Addictive Behavior; Student Behavior; Self Management; Independent Study; Learning Strategies; Anxiety; Social Media |
| DOI: |
10.1111/bjet.13572 |
| ISSN: |
0007-1013; 1467-8535 |
| Abstract: |
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. |
| Abstractor: |
As Provided |
| Entry Date: |
2025 |
| Accession Number: |
EJ1486252 |
| Database: |
ERIC |