Factors influencing e-learning system utilization among lecturers in universities of North-Eastern Nigeria

The main objective of this study is to develop a fit structural model that would predict and explain the factors that influence e-Learning utilization among university lecturers on the basis of interrelationships that exist between technology readiness, subjective norm, job relevance, perceived e...

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Bibliographic Details
Main Author: Madu, Kabu
Format: Thesis
Language:English
Published: 2019
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/90606/1/FPP%202020%207%20-%20IR.pdf
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Summary:The main objective of this study is to develop a fit structural model that would predict and explain the factors that influence e-Learning utilization among university lecturers on the basis of interrelationships that exist between technology readiness, subjective norm, job relevance, perceived enjoyment, technology self-efficacy facilitating conditions and perceived usefulness, perceived ease of use, attitude towards use, behavioural intention and e-Learning use based on Theory of Reasoned Action, Theory of Planned Behavior, Technology Acceptance Model and Technology Readiness. This study employed a correlational study and done in the Northeast zone of Nigeria, comprises of six (6) states of Adamawa, Bauchi, Borno, Gombe, Taraba, and Yobe. The instrument for data gathering used was a survey. A pilot study was done with a sample of 30 lecturers and Cronbach alpha stanch quality of the instrument from the pilot examines was .75 while it extended from .810 to .956 at the last study led on an example of 230 university lecturers. Data was examined utilizing SPPSS 22 for descriptive analysis and AMOS v22 to predict structural equation modelling. The model of this study has 21 paths for both path analysis and the test for mediation that was tried and discovered fitted according to the set fit criteria. Out of the 19 paths in the model, 11 paths have confirmed significant impacts in the interrelationships explained by the model, while nine paths did not. The paths that reflected notable impacts are: university lecturers’ technology readiness exhibit no significant influence on perceived usefulness (β = .024, p>.005); technology self-efficacy has a significant influence on perceiving the usefulness of e-Learning utilization (β=.127, p<.047); job relevance has no significant influence on perceived usefulness (β=.130, p>.005); subjective norm has no significant influence on perceived usefulness (β=.016, p>.005); perceived ease of use has a significant influence on perceived usefulness (β=.780, p<.000); technology readiness has a significant influence on perceived ease of use of e-learning (β=.280, p<.000); technology self-efficacy has no significant influence on perceived ease of use (β=.003, p>.005); job relevance has no significant influence on perceived ease of use (β=.096, p>.005); perceived enjoyment of using e-Learning has no significant influence on perceived ease of use for e-learning (β=.096, p>.005); facilitating conditions has significant influence on perceived ease of use (β=.148, p<.011); perceived usefulness has a significant influence on attitude towards to use (β=.145, p<.046); perceived ease of use has a significant influence on attitude towards to use (β=.379, p<.000).; perceived enjoyment has significant influence on behavioral intention to use (β=.306, p<.000); facilitating conditions has significant influence on behavioral intention to use (β=.198, p<.024); subjective norm has significant influence on behavioral intention to use (β=.150, p<.016); perceived usefulness has a significant influence on behavioral intention to use (β= -053, p>.005); attitude towards use e-Learning utilization has a significant influence on behavioral intention to use (β= .383, p<.000); technology readiness has a significant influence on e-learning utilization (β=.167, p<.039); behavioural intention to use utilize has no significant influence on e-Learning utilization (β=.051, p>.005). The outcomes of mediation tests demonstrated that among the four mediators, perceived usefulness, perceived ease of use attitude towards use and behavioural intention has indirect effects, partial mediation and full mediations respectively. Earlier, it has been established that there are mediation effects among the variables. The overall, the structural model of the study has explained about 18.3% of perceived usefulness, 21% of perceived ease of use, 42% of attitude towards use, 33% of behavioral intention to use, and 36.1% of the variation in the e-Learning utilization of lecturer in tertiary universities of North-eastern Nigeria. The researcher recommended that there should be more support from the universities in providing lecturers with sufficient tools and strong legal policy that will assist the mechanism of utilizing the e-Learning system in Nigerian higher education institutions.