
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.
| 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). | 326 | |
| 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 0.1% | |
| 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 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
