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Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction

Authors: Demei Shen; Moon-Heum Cho; Chia-Lin Tsai; Rose M. Marra;

Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction

Abstract

Abstract Self-efficacy is believed to be a key component in successful online learning; however, most existing studies of online self-efficacy focus on the computer. Although computer self-efficacy is important in online learning, researchers have generally agreed that online learning entails self-efficacy of multifaceted dimensions; therefore, one of the purposes of the current study was to identify dimensions of online learning self-efficacy. Through exploratory factor analysis, we identified five dimensions of online learning self-efficacy: (a) self-efficacy to complete an online course, (b) self-efficacy to interact socially with classmates, (c) self-efficacy to handle tools in a Course Management System (CMS), (d) self-efficacy to interact with instructors in an online course, and (e) self-efficacy to interact with classmates for academic purposes. In addition, the role of demographic variables in online learning self-efficacy was investigated. Demographic variables, such as the number of online courses taken, gender, and academic status were found to predict online learning self-efficacy. Furthermore, we found that online learning self-efficacy predicted students' online learning satisfaction. Results are discussed, and implications for online teaching and learning are provided.

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selected citations
These citations are derived from selected sources.
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!
326
Top 0.1%
Top 1%
Top 10%
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