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The Dark Side of Mobile Learning via Social Media: How Bad Can It Get?

Xiu-Kin Loh, Voon-Hsien Lee, Xiu-Ming Loh, Garry Wei-Han Tan, Keng-Boon Ooi, Yogesh Dwivedi Orcid Logo

Information Systems Frontiers, Volume: 24, Pages: 1887 - 1904

Swansea University Author: Yogesh Dwivedi Orcid Logo

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DOI (Published version): 10.1007/s10796-021-10202-z

Abstract

As the COVID-19 pandemic continues to spread at an unprecedented rate, many universities around the world halted physical forms of teaching and learning to stop the spread of the virus. As a result, many university students were forced to utilize online learning through channels such as mobile socia...

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Published in: Information Systems Frontiers
ISSN: 1387-3326 1572-9419
Published: Springer Science and Business Media LLC 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa57827
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spelling 2023-01-04T10:54:57.7807104 v2 57827 2021-09-09 The Dark Side of Mobile Learning via Social Media: How Bad Can It Get? d154596e71b99ad1285563c8fdd373d7 0000-0002-5547-9990 Yogesh Dwivedi Yogesh Dwivedi true false 2021-09-09 BBU As the COVID-19 pandemic continues to spread at an unprecedented rate, many universities around the world halted physical forms of teaching and learning to stop the spread of the virus. As a result, many university students were forced to utilize online learning through channels such as mobile social media. Due to the novelty of this situation, there are many unknowns particularly with the negative influences of mobile learning via social media on university students. Thus, this study looks to examine this subject matter from the perspective of the stimulus–organism–response theory. The uniquely developed research model included four stimuli (i.e., social overload, information overload, life invasion, and privacy invasion), two organisms (i.e., technostress and exhaustion) as well as a response in terms of reduced intention to use mobile learning via social media. The responses were collected from 384 university students via an online survey and analyzed with the Partial-Least-Square-Structural-Equation-Modelling. It was found that the antecedents for both technostress and exhaustion were able to account for more than half of their respective variances. Furthermore, technostress and exhaustion were significant facilitators of the students’ reduced intention to use mobile learning via social media. In addition to the practical insights for stakeholders in the education industry, this study also posited several theoretical implications for researchers. Journal Article Information Systems Frontiers 24 1887 1904 Springer Science and Business Media LLC 1387-3326 1572-9419 Stimulus–organism–response; Technostress; Exhaustion; Higher education; Online learning; Mobile learning; Distance learning; Social media; COVID-19 9 10 2021 2021-10-09 10.1007/s10796-021-10202-z COLLEGE NANME Business COLLEGE CODE BBU Swansea University SU Library paid the OA fee (TA Institutional Deal) 2023-01-04T10:54:57.7807104 2021-09-09T09:32:35.3201158 Faculty of Humanities and Social Sciences School of Management - Business Management Xiu-Kin Loh 1 Voon-Hsien Lee 2 Xiu-Ming Loh 3 Garry Wei-Han Tan 4 Keng-Boon Ooi 5 Yogesh Dwivedi 0000-0002-5547-9990 6 57827__21436__4217b2ed16484a339d63e9ea485ddae0.pdf 58559.pdf 2021-11-08T09:33:08.0991061 Output 1063455 application/pdf Version of Record true © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License true eng http://creativecommons.org/licenses/by/4.0/
title The Dark Side of Mobile Learning via Social Media: How Bad Can It Get?
spellingShingle The Dark Side of Mobile Learning via Social Media: How Bad Can It Get?
Yogesh Dwivedi
title_short The Dark Side of Mobile Learning via Social Media: How Bad Can It Get?
title_full The Dark Side of Mobile Learning via Social Media: How Bad Can It Get?
title_fullStr The Dark Side of Mobile Learning via Social Media: How Bad Can It Get?
title_full_unstemmed The Dark Side of Mobile Learning via Social Media: How Bad Can It Get?
title_sort The Dark Side of Mobile Learning via Social Media: How Bad Can It Get?
author_id_str_mv d154596e71b99ad1285563c8fdd373d7
author_id_fullname_str_mv d154596e71b99ad1285563c8fdd373d7_***_Yogesh Dwivedi
author Yogesh Dwivedi
author2 Xiu-Kin Loh
Voon-Hsien Lee
Xiu-Ming Loh
Garry Wei-Han Tan
Keng-Boon Ooi
Yogesh Dwivedi
format Journal article
container_title Information Systems Frontiers
container_volume 24
container_start_page 1887
publishDate 2021
institution Swansea University
issn 1387-3326
1572-9419
doi_str_mv 10.1007/s10796-021-10202-z
publisher Springer Science and Business Media LLC
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
document_store_str 1
active_str 0
description As the COVID-19 pandemic continues to spread at an unprecedented rate, many universities around the world halted physical forms of teaching and learning to stop the spread of the virus. As a result, many university students were forced to utilize online learning through channels such as mobile social media. Due to the novelty of this situation, there are many unknowns particularly with the negative influences of mobile learning via social media on university students. Thus, this study looks to examine this subject matter from the perspective of the stimulus–organism–response theory. The uniquely developed research model included four stimuli (i.e., social overload, information overload, life invasion, and privacy invasion), two organisms (i.e., technostress and exhaustion) as well as a response in terms of reduced intention to use mobile learning via social media. The responses were collected from 384 university students via an online survey and analyzed with the Partial-Least-Square-Structural-Equation-Modelling. It was found that the antecedents for both technostress and exhaustion were able to account for more than half of their respective variances. Furthermore, technostress and exhaustion were significant facilitators of the students’ reduced intention to use mobile learning via social media. In addition to the practical insights for stakeholders in the education industry, this study also posited several theoretical implications for researchers.
published_date 2021-10-09T04:13:51Z
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score 11.012678

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