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Nicholas-Omoregbe, Olanike S and Azeta, A. A. and Chiazor, A.I. and Omoregbe, N. A. (2017) PREDICTING THE ADOPTION OF E-LEARNING MANAGEMENT SYSTEM: A CASE OF SELECTED PRIVATE UNIVERSITIES IN NIGERIA. Turkish Online Journal of Distance Education-TOJDE, 18 (2). ISSN 1302-6488

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Despite the availability of studies on e-learning management system (eLMS) using information system models, its theoretical foundations have not yet captured social constructs that are peculiar to developing countries including Nigeria. This study was undertaken with the aim of investigating factors that could influence eLMS adoption in higher education. Drawing upon the Social Learning Theory (SLT), Unified Theory of Acceptance and Use of Technology (UTAUT), and two other variables which are Technology Culturation and Power (electricity), an empirical based model was developed to identify predictors of eLMS. The study used Smart Partial LeastSquare-Structured Equation Modeling (PLS-SEM) to examine the pattern of inter-correlation among the SLT and UTAUT constructs. The survey method of research was used by administering questionnaires to undergraduate students of 3 selected private universities in Ogun state, Nigeria with a sample size of 472. The results show that Attitude, Social Influence and Technology Culturation are strong determining factors of intention to adopt eLMS, while Performance Expectancy and Power do not significantly influence the Behavioural Intention to adopt eLMS. More so, Performance Expectancy and Behavioural Intention have positive influence on student grades. The results of this study will provide theoretical information on the intention to adopt eLMS and should be of interest to both researchers and education administrators in terms of planning and decision making.

Item Type: Article
Uncontrolled Keywords: e-Learning management system, SLT, UTAUT, PLS-SEM, technology culturation and power, Nigeria.
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Mrs Hannah Akinwumi
Date Deposited: 11 Mar 2019 22:27
Last Modified: 11 Mar 2019 22:27

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