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Understanding Student Acceptance of Online Learning Systems in Higher Education: Application of Social Psychology Theories with Consideration of User Innovativeness

Authors: Eun-Jung Kim; Jinkyung Jenny Kim; Sang-Ho Han;

Understanding Student Acceptance of Online Learning Systems in Higher Education: Application of Social Psychology Theories with Consideration of User Innovativeness

Abstract

The COVID-19 pandemic has created the opportunity to conduct a huge experiment with online classes in the university setting. The objectives of this study are (1) to provide obvious insight into determining factors driving greater intention of students to use online learning systems based on an integrated technology acceptance model (TAM) and theory of planned behavior (TPB), and (2) to provide the moderating role of innovativeness as a key factor. An online survey was conducted with 216 university students taking hospitality and tourism studies in Busan, Korea. The results of the study are as follows. First, perceived ease of use affects perceived usefulness, perceived usefulness affects attitude, whereas perceived ease of use does not directly affect attitude. Second, attitude and subjective norms positively influence behavioral intention, while perceived behavioral control does not. Third, user innovativeness plays a moderating role in the relationship between subjective norms and behavioral intention. As part of the lessons learned from COVID-19, it is meaningful to provide insightful implications to academia, specifically to the college of hospitality and tourism.

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Keywords

Environmental effects of industries and plants, COVID-19, TJ807-830, TD194-195, Renewable energy sources, Environmental sciences, online learning system, theory of planned behavior (TPB), higher education, technology acceptance model (TAM), user innovativeness, GE1-350

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    67
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
67
Top 1%
Top 10%
Top 1%
gold