Abstract
Learning is an intentional activity, with several factors affecting students’ intention to use new learning technology. Researchers have investigated technology acceptance in different contexts by developing various theories/models and testing them by a number of means. Although most theories/models developed have been examined through regression or structural equation modeling, Bayesian analysis offers more accurate data analysis results. To address this gap, the unified theory of acceptance and technology use in the context of e-learning via Facebook are re-examined in this study using Bayesian analysis. The data (S1 Data) were collected from 170 students enrolled in a business statistics course at University of Malaya, Malaysia, and tested with the maximum likelihood and Bayesian approaches. The difference between the two methods’ results indicates that performance expectancy and hedonic motivation are the strongest factors influencing the intention to use e-learning via Facebook. The Bayesian estimation model exhibited better data fit than the maximum likelihood estimator model. The results of the Bayesian and maximum likelihood estimator approaches are compared and the reasons for the result discrepancy are deliberated.
Highlights
The use of information systems and the Internet as teaching tools is a noteworthy aspect in today’s tech-savvy community
The first modeling part was implemented using AMOS version 18, a flexible tool that allows examining the interrelationship under the normality assumption of the variables in the UTAUT2 framework for e-learning with Facebook
B-structural equation modeling (SEM) was employed with the same framework in the first part of data analysis along with WinBUGS software
Summary
The use of information systems and the Internet as teaching tools is a noteworthy aspect in today’s tech-savvy community. It is a complementary tool to traditional learning and teaching processes, since e-learning can facilitate education and training through information communication technology (ICT) for anyone, anytime and anywhere. Several models have been developed mainly in the information science domain to predict individual technology acceptance. Researchers have applied these models in a range of contexts. E-learning has become a widely accepted learning approach [30] This method of learning (E-learning) emphasizes the use of telecommunication technology for teaching and learning [31] and involves web-based communication systems. Universities and educational organizations mostly use e-learning technologies to attain new and innovative ways of delivering education to students [4]
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