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Predicting user acceptance of electronic learning at the University of Zululand

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dc.contributor.advisor le Roux, C.B.J.
dc.contributor.advisor Jacobs, D.
dc.contributor.author Evans, Neil Davies
dc.contributor.author
dc.date.accessioned 2014-06-23T09:17:16Z
dc.date.available 2014-06-23T09:17:16Z
dc.date.issued 2013
dc.identifier.uri http://hdl.handle.net/10530/1317
dc.description Thesis submitted in fulfillment of the requirements for the award of the Degree of Doctor of Philosophy (Library and Information Science) in the Department of Information Studies at the University of Zululand, South Africa, 2013. en_US
dc.description.abstract Since the beginning of the 21st century, the ubiquitous use of e-learning resources has changed the way information, especially multimedia information is being stored, accessed and disseminated in institutions of higher learning. These institutions constantly have to review instructional policies and technical frameworks to accommodate new pedagogies and educational technologies that are required to educate a generation of students with different learning styles and needs. This research followed a positivist epistemological belief and deductive reasoning by adopting the known and validated Unified Theory of Acceptance and Use of Technology (UTAUT) and validated its application within the contextual setting of the University of Zululand where it was used to predict the acceptance, behavioural intentions and usage behaviour of the primary users of e-learning resources. The study adopted a survey research design and a non-experimental statistical method was used to analyse the quantitative data. Partial Least Squares Structural Equation Modeling (PLS-SEM) and inferential statistics were used to predict the level of acceptance of e-learning by academic staff and students and show the strengths and significances of the postulated UTAUT relationships. From the results, the study anticipates the acceptance of e-learning resources by the majority of students and academic staff at the University of Zululand. Further UTAUT demonstrated moderate predictive accuracy and relevance in explaining behavioural intentions of students (Adjusted R2 = 0.39) and academic staff (Adjusted R2 = 0.41) to use e-learning resources, which was below the high accuracies found in Venkatesh et al. (2003) study, but comparable to the predictive strengths of the eight models used to make up the UTAUT model. The expected academic performance gains in primary users proved to be significant and the strongest direct effect on the primary users’ behavioural intentions to use e-learning resources at the University of Zululand. The students’ use behaviour of e-learning resources is most influenced by the direct effect of the facilitating conditions, then by their behavioural intentions, while the most influential indirect effects were performance and effort expectancies and lastly social influences. For academic staff, the direct effect of their behavioural intentions to use e-learning resources is the most influential on their use behaviour, followed by the indirect and direct effects of performance expectancy and facilitating conditions respectively, and then lastly the indirect effects of effort expectancy and social influences. The study concludes that these results indicate the importance of creating conducive facilitating conditions for students and positive behavioural intentions in academic staff to expedite the use of e-learning resources at the University of Zululand. en_US
dc.description.sponsorship University of Zululand en_US
dc.language.iso en en_US
dc.publisher University of Zululand en_US
dc.subject e-Learning en_US
dc.title Predicting user acceptance of electronic learning at the University of Zululand en_US
dc.type Thesis en_US

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