Associations between resilience, technostress and reflective capacity in social pedagogy students: A structural equation modeling methodology

Aigerim Baisarinova

Department of Pedagogy, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan.

https://orcid.org/0009-0006-2444-4820

Rymshash Toleubekova

Department of Pedagogy, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan.

https://orcid.org/0009-0006-4056-3192

DOI: https://doi.org/10.20448/jeelr.v10i4.5201

Keywords: Higher education, Psychological resilience, Resilient behavior, Self-reflection, Social work students, Technology.


Abstract

Understanding factors affecting student academic and life outcomes may be critical for social work programs and educational institutions. Therefore, this study aims to explore the relationships   between resilience, technostress   and reflective capacity among social work students. A cross-sectional non-experimental research design was used. One hundred and sixty-three social work students completed an online survey measuring technostress level, reflective capacity and psychological resilience. Data were analyzed using Pearson’s to estimate linear correlations, confirmatory factor analysis to ensure model fit and structural equation modeling with covariates to reveal the relationships between the measured constructs. The results indicated that resilience had a direct and negative effect on technostress, a positive and direct effect on reflective capacity and a negative indirect effect on technostress through reflective capacity. This means that social work students with higher levels of resilience had lower levels of technostress related to technology use were more likely to engage in reflective practices and had lower levels of technostress due to improved reflective capacity. These findings emphasize the significance of resilience and reflective practices in mitigating the negative effects of technology use among social work students. However, researchers should be cautious about generalizing findings due to the sample’s limitations and future investigations should consider longitudinal data from diverse populations.

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