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Personality Traits' Prediction of the Digital Skills Divide between Urban and Rural College Students: A Longitudinal and Cross-Sectional Analysis of Online Learning During the COVID-19 Pandemic.
- Source :
- Educational Technology & Society; Oct2023, Vol. 26 Issue 4, p150-162, 13p
- Publication Year :
- 2023
-
Abstract
- The digital skills divide has been raised as a serious issue during the COVID-19. However, few studies explored the predictive influence of personality traits on college students' digital skills in online learning. To address this gap, this study took the second-level digital divide as the focus to conduct a two-round survey of college students over nearly 2 years based on cross-sectional and longitudinal methods to explore whether there is a digital skill divide or personality trait differences between urban and rural college students while learning online, and whether college students' personality traits can predict their digital skills. The results confirmed the rural and urban college students' digital skills divide. There were significant differences in all dimensions of their digital skills except for mobile skills. In addition, the digital skills divide of these college students persisted for nearly 2 years. Specifically, this study further confirmed that there were significant differences in the urban and rural college students' extraversion, neuroticism, and agreeableness, but there was no significant difference in their openness and conscientiousness. Additionally, there was no change in the urban and rural college students' personality trait differences in nearly 2 years. Personality traits could positively predict college students' digital skills. This study provides evidence for bridging the second-level digital divide of the rural and urban college students from the perspective of personality traits. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 11763647
- Volume :
- 26
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Educational Technology & Society
- Publication Type :
- Academic Journal
- Accession number :
- 172897653
- Full Text :
- https://doi.org/10.30191/ETS.202310_26(4).0011