Study demands, study resources and the role of personality characteristics in predicting the engagement of fist-year university students

Cilliers, Jeanie Rouchelle; Mostert, Karina; Nel, Jan Alewyn

doi:10.20853/32-1-1575

Cited by 34 publications

(57 citation statements)

References 74 publications

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“…When the external environment lacks resources, students cannot reduce the potentially harmful influence of SD on MH, leading to an inability to perform ( Kember, 2004 ) adequately. However, resource availability enhances study engagement, strengthening MH ( Cilliers et al, 2018 ). Several studies have shown that specific SR (i.e., peer support, lecturer support, growth opportunities, and information availability) may enhance students’ MH ( Kember, 2004 ; Mokgele and Rothmann, 2014 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Longitudinal Trajectories of Study Characteristics and Mental Health Before and During the COVID-19 Lockdown

Zyl

Rothmann

Zondervan‐Zwijnenburg

2021

Front. Psychol.

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The COVID-19 lockdown has significantly disrupted the higher education environment within the Netherlands and led to changes in available study-related resources and study demands of students. These changes in study resources and study demands, the uncertainty and confusion about educational activities, the developing fear and anxiety about the disease, and the implementation of the COVID-19 lockdown measures may have a significant impact on the mental health of students. As such, this study aimed to investigate the trajectory patterns, rate of change, and longitudinal associations between study resources–demands and mental health of 141 university students from the Netherlands before and during the COVID-19 lockdown. The present study employed a longitudinal design and a piecewise latent growth modeling strategy to investigate the changes in study resources and mental health over a 3 month period. The results showed that moderate levels of student resources significantly decreased before, followed by a substantial rate of increase during, lockdown. In contrast, study demands and mental health were reported to be moderate and stable throughout the study. Finally, the growth trajectories of study resources–demands and mental health were only associated before the lockdown procedures were implemented. Despite growing concerns relating to the negative psychological impact of COVID-19 on students, our study shows that the mental health during the initial COVID-19 lockdown remained relatively unchanged.

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Section: Literature Reviewmentioning

confidence: 99%

Longitudinal Trajectories of Study Characteristics and Mental Health Before and During the COVID-19 Lockdown

Zyl

Rothmann

Zondervan‐Zwijnenburg

2021

Front. Psychol.

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“…Similar to employees, students, are faced with various demands. They are expected to attend lectures and seminars, and to invest time in self-studying [ 30 ]. Furthermore, they are demanded to manage high workload, in some disciplines up to 50 hours per week [ 31 ].…”

Section: Introductionmentioning

confidence: 99%

“…Perceived and actual workload is frequently associated with workplace burnout [ 2 ]. Further study-related demands arise from the pressure of behaving like a competent professional [ 30 ].…”

Section: Introductionmentioning

confidence: 99%

The Study Demands-Resources Framework: An Empirical Introduction

Lesener

Pleiss

Gusy

et al. 2020

IJERPH

128

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Based on the well-established job demands-resources (JD-R) framework, in our study we introduce the novel study demands-resources (SD-R) framework. The SD-R framework allows the study of salutogenic and pathogenic effects of university settings on students’ health and well-being. Using a large sample of university students (n = 5660), our aim was to translate and validate the JD-R’s essential assumptions within the university context, and thus establish the SD-R framework. We performed structural equation modelling to examine these essential assumptions. As assumed, we found that study demands—the “bad things” at university—predict student burnout (β = 0.50), whereas study resources—the “good things” at university—predict student engagement (β = 0.70) as well as burnout (β = −0.35). Also, in line with the SD-R’s assumptions, student burnout predicts life satisfaction negatively (β = −0.34), whereas student engagement predicts life satisfaction positively (β = 0.29). Hence, we were able to introduce the novel SD-R framework and validate its core assumptions. The SD-R framework serves as an excellent theoretical basis to examine both the salutogenic and pathogenic effects of the study context on students’ health and well-being. However, the framework needs further longitudinal and meta-analytical verification in accordance with the research on the JD-R framework.

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“…Many internal factors can influence learning engagement, including needs, motivation, and personality traits (e.g., learning normative consciousness and learning behaviors; Martin et al, 2016 ; Yamada et al, 2017 ; Cilliers et al, 2018 ). The normative consciousness of learning is an intuitive confidence that students deliberately form in the process of learning.…”

Section: Introductionmentioning

confidence: 99%

The Relationship Between Family Support and e-Learning Engagement in College Students: The Mediating Role of e-Learning Normative Consciousness and Behaviors and Self-Efficacy

Hong

Zhang

et al. 2021

Front. Psychol.

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Due to the current COVID-19 pandemic, colleges and universities have implemented network teaching. E-learning engagement is the most important concern of educators and parents because this will directly affect student academic performance. Hence, this study focuses on students’ perceived family support and their e-learning engagement and analyzes the effects of e-learning normative consciousness and behaviors and self-efficacy on the relationship between family support and e-learning engagement in college students. Prior to this study, the relationship between these variables was unknown. Four structural equation models revealed the multiple mediating roles of e-learning normative consciousness and behaviors and self-efficacy in the relationship between family support and e-learning engagement. A total of 1,317 college students (mean age=19.51; 52.2% freshman) voluntarily participated in our study. The results showed that e-learning normative consciousness and behaviors and self-efficacy played significant and mediating roles between students’ perceived family support and e-learning engagement. Specifically, these two individual variables fully mediated the relationship between students’ perceived family support and e-learning engagement. The multiple mediation model showed that family members can increase family support of their children by creating a household environment conducive to learning, displaying positive emotions, demonstrating the capability to assist their children, advocating the significance of learning normative consciousness and behaviors, and encouraging dedicated and efficient learning. The findings complement and extend the understanding of factors influencing student e-learning engagement.

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Study demands, study resources and the role of personality characteristics in predicting the engagement of fist-year university students

Cited by 34 publications

References 74 publications

Longitudinal Trajectories of Study Characteristics and Mental Health Before and During the COVID-19 Lockdown

Longitudinal Trajectories of Study Characteristics and Mental Health Before and During the COVID-19 Lockdown

The Study Demands-Resources Framework: An Empirical Introduction

The Relationship Between Family Support and e-Learning Engagement in College Students: The Mediating Role of e-Learning Normative Consciousness and Behaviors and Self-Efficacy

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