Digital learning of English as a foreign language among university students: How are approaches to learning linked to digital competence and technostress?. (27th April 2022)
- Record Type:
- Journal Article
- Title:
- Digital learning of English as a foreign language among university students: How are approaches to learning linked to digital competence and technostress?. (27th April 2022)
- Main Title:
- Digital learning of English as a foreign language among university students: How are approaches to learning linked to digital competence and technostress?
- Authors:
- Niu, Liwei
Wang, Xinghua
Wallace, Matthew P.
Pang, Hui
Xu, Yanping - Abstract:
- 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 findingsAbstract: 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. Lay Description: What is already known about this topic?: Computer‐assisted language learning (CALL) is often perceived as rote learning through a surface approach such as memorization and repetition. Technostress may arise if learners cannot manage their approaches to digital learning properly, but has rarely been studied in CALL. Digital competence enables learners to leverage digital technologies for maximal learning prospects. However, little is known whether and how students' approaches to learning are related to digital competence in CALL. What this paper adds?: A surface approach to CALL was significantly positively related to technostress while negatively related to digital competence. The deep and organized learning approaches positively predicted digital competence. Digital competence negatively predicted technostress and burnout in CALL. High scores in the deep and organized approaches to learning were generally aligned with strong digital competence, low technostress, low burnout, and high CALL outcomes. Implications for practitioners: Authentic and safe CALL environments should be created for students to flourish. Deep and organized approaches to CALL are conducive to digital competence and help reduce technostress. … (more)
- Is Part Of:
- Journal of computer assisted learning. Volume 38:Number 5(2022)
- Journal:
- Journal of computer assisted learning
- Issue:
- Volume 38:Number 5(2022)
- Issue Display:
- Volume 38, Issue 5 (2022)
- Year:
- 2022
- Volume:
- 38
- Issue:
- 5
- Issue Sort Value:
- 2022-0038-0005-0000
- Page Start:
- 1332
- Page End:
- 1346
- Publication Date:
- 2022-04-27
- Subjects:
- burnout -- digital competence -- English as a foreign language -- Students' approaches to learning -- technostress
Computer-assisted instruction -- Periodicals
371.334 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-2729 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/jcal.12679 ↗
- Languages:
- English
- ISSNs:
- 0266-4909
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4963.640000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23418.xml