Although existing models of e-learning effectiveness in information systems (IS) have increased our understanding of how technology can support and enhance learning, most of our models do not take into account the importance of social presence. Thus, this study extends previous research by developing a model of e-learning effectiveness which adds social presence to other oft studied variables including application-specific computer self-efficacy (AS-CSE), perceived usefulness, course interaction, and e-learning effectiveness. Using data from 345 individuals, this model was validated through a field study in an introductory IS survey course. Results indicate that AS-CSE and perceived usefulness were related to course performance, course satisfaction, and course instrumentality. In addition, course interaction was related to course performance and satisfaction. Finally, social presence was related to course satisfaction and course instrumentality. Implications for research and practice are discussed.
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Fang JWang YYang CWang H(2021)NoteCoStruct: Powering Online Learners with Socially Scaffolded Note Taking and SharingExtended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411763.3451694(1-5)Online publication date: 8-May-2021
Kljun MKrulec RPucihar KSolina F(2019)Persuasive Technologies in m-Learning for Training Professionals: How to Keep Learners Engaged With Adaptive TriggeringIEEE Transactions on Learning Technologies10.1109/TLT.2018.284071612:3(370-383)Online publication date: 1-Jul-2019
Sun NRosson MCarroll JMandryk RHancock MPerry MCox A(2018)Where is Community Among Online Learners?Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3173866(1-13)Online publication date: 21-Apr-2018
In recent years, there has been an increasing interest in understanding the Massive open online courses (MOOCs) due to its gaining popularity. Even though the number of online platforms and programs has grown during the COVID-19 pandemic, there is ...
In the past, the conventional concentration of Internet banking (IB) research has been on technology development, but this is now shifting to user-focused research. It has been suggested that potential users of IB services in Malaysia may not adopt the ...
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Is social interaction within an e-learning environment important to learning outcomes__?__ Johnson et al. examine this question via a study that looks at social presence, application-specific computer self-efficacy (AS-CSE), and perceived usefulness for e-learners. This paper discusses "three learning outcomes: course satisfaction, skill demonstration ... and course instrumentality." The research model includes two dimensions: human and design. The human dimension includes only the AS-CSE component, while the design dimension includes perceived usefulness, interaction, and social presence. Each component is tied directly to a research hypothesis.
Johnson et al. borrow F.D. Davis' definition of perceived usefulness: "Perceived usefulness is the degree to which an individual believes that the technology will enhance his or her performance" [1]. The authors define interaction as the exchange of information between instructors, classmates, and other support staff (page 360). As stated by the authors, Short et al. define social presence as "the degree of salience of the other person in the interaction and the consequent salience of the interpersonal relationship" [2].
One concept that is not clearly defined in the paper is e-learning. The term e-learning has different meanings, depending on where the course is administered. For example, some colleges consider e-learning classes to be online classes that have deadlines and interaction, while other colleges consider e-learning to be distance education courses that are broadcast to multiple locations at one time. In the business world, e-learning can be computer-based training, online courses, or self-paced education. Even after reading the paper, I did not clearly understand the authors' definition of the concept. This definition is vitally important to understanding why, according to the authors, social interaction was not found to be present.
The research participants were from a single information science (IS) fundamental course at a university in the US. The course "was taught exclusively online," with a software tool called WebCT. The course ran for 12 weeks, covering six modules, with a student evaluation at the end of each module and at the end of the course. Students were separated into groups of 35, and managed by one instructor and three graduate assistants. There were 371 volunteer participants; 80 percent had prior computer experience. Likert-type scales were used to rate all components within each dimension. Analysis of the data is done with the partial least squares (PLS) modeling software PLSgraph 3.0, due to the size of the sample. The authors claim that their research expands the framework developed by Piccoli et al. in 2001 [3], showing that individuals need to know how to use technology in order to succeed in an e-learning environment.
This research brings attention to the fact that in order to fully benefit from an e-learning environment, students need more from their instructors than just emails, postings, discussion boards, and assignments. It shows researchers how they need to modify their course design within the WebCT software. Although limited by size, number of courses to which it was applied, and instructors involved, the research supports the findings of prior research that faculty must be creative and involved in online courses, in order to make sure that students are cognitively learning, not simply completing the assignments. This is a critical factor in the current economic climate, where budgets-both individual and professional-are tight and need to be used wisely to get the most gain.
An appendix provides the rating questions that were presented to the students, making this a very transferable research study. Many educational institutions would benefit from conducting their own student studies, based on Johnson et al.'s work. This would also be an excellent paper to include in a course that teaches students how to evaluate scholarly papers and the concepts of reliability, transferability, social change, and contribution to body of research knowledge.
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Fang JWang YYang CWang H(2021)NoteCoStruct: Powering Online Learners with Socially Scaffolded Note Taking and SharingExtended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411763.3451694(1-5)Online publication date: 8-May-2021
Kljun MKrulec RPucihar KSolina F(2019)Persuasive Technologies in m-Learning for Training Professionals: How to Keep Learners Engaged With Adaptive TriggeringIEEE Transactions on Learning Technologies10.1109/TLT.2018.284071612:3(370-383)Online publication date: 1-Jul-2019
Sun NRosson MCarroll JMandryk RHancock MPerry MCox A(2018)Where is Community Among Online Learners?Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3173866(1-13)Online publication date: 21-Apr-2018
Bessa JBranco FCosta AMartins JGonçalves R(2017)Information Management Through a Multidimensional Information Systems ArchitectureInternational Journal of Technology and Human Interaction10.4018/IJTHI.201710010113:4(1-18)Online publication date: 1-Oct-2017
Schouten DSmets NDriessen MFuhri KNeerincx MCremers A(2017)Requirements for a virtual environment to support the social participation education of low-literatesUniversal Access in the Information Society10.1007/s10209-016-0502-z16:3(681-698)Online publication date: 1-Aug-2017
Wu B(2016)Identifying the Influential Factors of Knowledge Sharing in E-Learning 2.0 SystemsInternational Journal of Enterprise Information Systems10.4018/IJEIS.201601010512:1(85-102)Online publication date: 1-Jan-2016
Zheng SHan KRosson MCarroll JHaywood JAleven VKay JRoll I(2016)The Role of Social Media in MOOCsProceedings of the Third (2016) ACM Conference on Learning @ Scale10.1145/2876034.2876047(419-428)Online publication date: 25-Apr-2016
Alsabawy ACater-Steel ASoar J(2016)Determinants of perceived usefulness of e-learning systemsComputers in Human Behavior10.1016/j.chb.2016.07.06564:C(843-858)Online publication date: 1-Nov-2016
Hew TSyed Abdul Kadir S(2016)Behavioural intention in cloud-based VLEComputers in Human Behavior10.1016/j.chb.2016.05.07564:C(9-20)Online publication date: 1-Nov-2016