Uncovering the Mechanism of Online-Learning Stress of College Students

Online-learning stress poses a significant challenge to the sustainability of higher education. The present study employs mixed methods to propose a conceptual process model that depicts the mechanism of online-learning stress of college students. The result of the qualitative study indicates 11 inf...
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Autor*in:	Enuo Wang [verfasserIn] Xueyao Zhang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	online-learning stress online-learning digital education higher education sustainability

Übergeordnetes Werk:	In: Sustainability - MDPI AG, 2009, 15(2023), 12, p 9541
Übergeordnetes Werk:	volume:15 ; year:2023 ; number:12, p 9541

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/su15129541

Katalog-ID:	DOAJ094054452

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spellingShingle	Enuo Wang misc TD194-195 misc TJ807-830 misc GE1-350 misc online-learning stress misc online-learning misc digital education misc higher education sustainability misc Environmental effects of industries and plants misc Renewable energy sources misc Environmental sciences Uncovering the Mechanism of Online-Learning Stress of College Students
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title_sort	uncovering the mechanism of online-learning stress of college students
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title_auth	Uncovering the Mechanism of Online-Learning Stress of College Students
abstract	Online-learning stress poses a significant challenge to the sustainability of higher education. The present study employs mixed methods to propose a conceptual process model that depicts the mechanism of online-learning stress of college students. The result of the qualitative study indicates 11 influential factors of online-learning stress, 10 manifestations of online-learning stress (OS), and three learning performance outcomes of OS (LP) through in-depth interviews with 15 college students. The result of a quantitative study on 159 online surveys implies that the influential factors of online-learning stress could be further categorized into learner competence and commitment (LC), course design reasonability (CD), and social support (SS). In addition, the results of the structural equation model (SEM) confirm the negative impact of LC and CD on OS, as well as OS on LP. However, the negative effect of SS on OS is unsupported. The study contributes to both OS theory development and online-learning and teaching in higher education.
abstractGer	Online-learning stress poses a significant challenge to the sustainability of higher education. The present study employs mixed methods to propose a conceptual process model that depicts the mechanism of online-learning stress of college students. The result of the qualitative study indicates 11 influential factors of online-learning stress, 10 manifestations of online-learning stress (OS), and three learning performance outcomes of OS (LP) through in-depth interviews with 15 college students. The result of a quantitative study on 159 online surveys implies that the influential factors of online-learning stress could be further categorized into learner competence and commitment (LC), course design reasonability (CD), and social support (SS). In addition, the results of the structural equation model (SEM) confirm the negative impact of LC and CD on OS, as well as OS on LP. However, the negative effect of SS on OS is unsupported. The study contributes to both OS theory development and online-learning and teaching in higher education.
abstract_unstemmed	Online-learning stress poses a significant challenge to the sustainability of higher education. The present study employs mixed methods to propose a conceptual process model that depicts the mechanism of online-learning stress of college students. The result of the qualitative study indicates 11 influential factors of online-learning stress, 10 manifestations of online-learning stress (OS), and three learning performance outcomes of OS (LP) through in-depth interviews with 15 college students. The result of a quantitative study on 159 online surveys implies that the influential factors of online-learning stress could be further categorized into learner competence and commitment (LC), course design reasonability (CD), and social support (SS). In addition, the results of the structural equation model (SEM) confirm the negative impact of LC and CD on OS, as well as OS on LP. However, the negative effect of SS on OS is unsupported. The study contributes to both OS theory development and online-learning and teaching in higher education.
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