Continuance Intention of University Students and Online Learning during the COVID-19 Pandemic: A Modified Expectation Confirmation Model Perspective

The prevalence of COVID-19 has changed traditional teaching modes. For many teachers, online learning effectively compensated for the absence of traditional face-to-face instruction. Online learning can support students and schools and can create unique opportunities under emergency management. Educ...

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Published inSustainability Vol. 13; no. 8; p. 4586
Main Authors Wang, Ting, Lin, Chien-Liang, Su, Yu-Sheng
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 20.04.2021
Subjects
Cognitive tasks
Colleges & universities
COVID-19
Distance learning
Education
Emergency management
Emergency preparedness
Higher education institutions
Information systems
Institutions
Internet
Learning
Multivariate statistical analysis
Online instruction
Schools
Students
Surveying
Sustainability
Teaching
Technical services
China
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Summary:The prevalence of COVID-19 has changed traditional teaching modes. For many teachers, online learning effectively compensated for the absence of traditional face-to-face instruction. Online learning can support students and schools and can create unique opportunities under emergency management. Educational institutions in various countries have launched large-scale online course modes in response to the pandemic. Additionally, online learning during a pandemic differs from traditional online learning modes. Through surveying students in higher education institutions, educational reform under emergency management can be explored. Therefore, university students were surveyed to investigate their continuance intention regarding online learning during the pandemic. Expectation confirmation theory was extended using the task-technology fit model to ascertain whether the technical support of promoting online learning helped student’s complete course learning tasks during the pandemic and spawned a continuance intention to use online learning in the future. Data were collected through online questionnaires. A total of 854 valid responses were collected, and partial least squares structural equation modeling was employed to verify the research hypotheses. The results revealed that the overall research framework largely explained continuance intention. Concrete suggestions are proposed for higher education institutions to promote online learning modes and methods after the COVID-19 pandemic.
ISSN:2071-1050
2071-1050
DOI:10.3390/su13084586