Cargando…

Procrastination predicts online self-regulated learning and online learning ineffectiveness during the coronavirus lockdown

During the lockdown due to SARS-CoV-2 (coronavirus lockdown), there has been a tremendous increase in the number of students taking online courses. Few studies, however, have examined the individual dispositions that influence self-regulated online learning during the coronavirus lockdown. To addres...

Descripción completa

Detalles Bibliográficos
Autores principales: Hong, Jon-Chao, Lee, Yi-Fang, Ye, Jian-Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7846229/
https://www.ncbi.nlm.nih.gov/pubmed/33551531
http://dx.doi.org/10.1016/j.paid.2021.110673
_version_ 1783644697824067584
author Hong, Jon-Chao
Lee, Yi-Fang
Ye, Jian-Hong
author_facet Hong, Jon-Chao
Lee, Yi-Fang
Ye, Jian-Hong
author_sort Hong, Jon-Chao
collection PubMed
description During the lockdown due to SARS-CoV-2 (coronavirus lockdown), there has been a tremendous increase in the number of students taking online courses. Few studies, however, have examined the individual dispositions that influence self-regulated online learning during the coronavirus lockdown. To address this gap, the present study explored the ineffectiveness of online learning and examined how it can be predicted by self-regulated online learning and participants' procrastination disposition. Data of 433 participants were collected and subjected to confirmatory factor analysis with structural equation modeling. The results indicated that procrastination is negatively related to 6 sub-constructs of self-regulated online learning: task strategy, mood adjustment, self-evaluation, environmental structure, time management, and help-seeking. These sub-constructs were negatively related to the learners' perceived ineffectiveness of online learning. However, the relationship between perceived learning ineffectiveness and environmental structure or help-seeking was weaker than that with task strategy or mood adjustment, indicating that the latter two subtypes of self-regulated online learning should be considered before students engage in online learning.
format Online
Article
Text
id pubmed-7846229
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Elsevier Ltd.
record_format MEDLINE/PubMed
spelling pubmed-78462292021-02-01 Procrastination predicts online self-regulated learning and online learning ineffectiveness during the coronavirus lockdown Hong, Jon-Chao Lee, Yi-Fang Ye, Jian-Hong Pers Individ Dif Article During the lockdown due to SARS-CoV-2 (coronavirus lockdown), there has been a tremendous increase in the number of students taking online courses. Few studies, however, have examined the individual dispositions that influence self-regulated online learning during the coronavirus lockdown. To address this gap, the present study explored the ineffectiveness of online learning and examined how it can be predicted by self-regulated online learning and participants' procrastination disposition. Data of 433 participants were collected and subjected to confirmatory factor analysis with structural equation modeling. The results indicated that procrastination is negatively related to 6 sub-constructs of self-regulated online learning: task strategy, mood adjustment, self-evaluation, environmental structure, time management, and help-seeking. These sub-constructs were negatively related to the learners' perceived ineffectiveness of online learning. However, the relationship between perceived learning ineffectiveness and environmental structure or help-seeking was weaker than that with task strategy or mood adjustment, indicating that the latter two subtypes of self-regulated online learning should be considered before students engage in online learning. Elsevier Ltd. 2021-05 2021-01-29 /pmc/articles/PMC7846229/ /pubmed/33551531 http://dx.doi.org/10.1016/j.paid.2021.110673 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Hong, Jon-Chao
Lee, Yi-Fang
Ye, Jian-Hong
Procrastination predicts online self-regulated learning and online learning ineffectiveness during the coronavirus lockdown
title Procrastination predicts online self-regulated learning and online learning ineffectiveness during the coronavirus lockdown
title_full Procrastination predicts online self-regulated learning and online learning ineffectiveness during the coronavirus lockdown
title_fullStr Procrastination predicts online self-regulated learning and online learning ineffectiveness during the coronavirus lockdown
title_full_unstemmed Procrastination predicts online self-regulated learning and online learning ineffectiveness during the coronavirus lockdown
title_short Procrastination predicts online self-regulated learning and online learning ineffectiveness during the coronavirus lockdown
title_sort procrastination predicts online self-regulated learning and online learning ineffectiveness during the coronavirus lockdown
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7846229/
https://www.ncbi.nlm.nih.gov/pubmed/33551531
http://dx.doi.org/10.1016/j.paid.2021.110673
work_keys_str_mv AT hongjonchao procrastinationpredictsonlineselfregulatedlearningandonlinelearningineffectivenessduringthecoronaviruslockdown
AT leeyifang procrastinationpredictsonlineselfregulatedlearningandonlinelearningineffectivenessduringthecoronaviruslockdown
AT yejianhong procrastinationpredictsonlineselfregulatedlearningandonlinelearningineffectivenessduringthecoronaviruslockdown