Citation
Madu, Kabu
(2019)
Factors influencing e-learning system utilization among lecturers in universities of North-Eastern Nigeria.
Doctoral thesis, Universiti Putra Malaysia.
Abstract
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.
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