A meta-analysis of e-learning technology acceptance: The role of user types and e-learning technology types

Abstract

Existing literature in the field of e-learning technology acceptance reflects a significant number of independent studies that primarily investigate the causal relationships proposed by technology acceptance theory, such as the technology acceptance model (TAM). To synthesize the existing knowledge in the field of e-learning technology acceptance, we have conducted a systematic literature review of 42 independent papers, mostly published in major journals. Furthermore, in order to view the research context by combining and analyzing the quantitative results of the reviewed research studies, a meta-analysis of the causal effect sizes between common TAM-related relationships was conducted. The main findings of this study, which is the first of its kind, are: (1) TAM is the most-used acceptance theory in e-learning acceptance research, and (2) the size of the causal effects between individual TAM-related factors depends on the type of user and the type of e-learning technology. The results of the meta-analysis demonstrated a moderating effect for user-related factors and technology-related factors for several evaluated causal paths. We have gathered proof that the perceived ease of use and the perceived usefulness tend to be the factors that can influence the attitudes of users toward using an e-learning technology in equal measure for different user types and types of e-learning technology settings.

Introduction

E-learning is a way of learning that can provide education and training with the use of information communication technologies (ICT) to anyone, anytime and anywhere. E-learning technologies are mostly used by universities and other educational organizations for providing new and innovative ways for delivering education to their students. Studies on e-learning acceptance mostly incorporate students as subjects; researchers try to explain the factors influencing the acceptance of e-learning technology by students. From another perspective, for the successful implementation and introduction of e-learning technologies, they must be accepted and used by teachers or professors who use these technologies for providing learning materials to their students. Recently, the importance of e-learning has been rising, especially in the business sector, where companies have recognized the benefits of using e-learning technologies to provide cost-effective on-line learning for their employees (Chiu and Wang, 2008, Karaali et al., 2011). It is therefore important to search for factors that may influence the perceptions of employees when using a specific e-learning technology.

The use of e-learning technologies must have a positive impact on users. When the user is presented with a new e-learning technology, different factors may influence their decision on how and when they will use a particular technology. Furthermore, the weight of the impact of these factors may differ for different user types and e-learning technology types. Existing literature comprises several studies that deal with the identification of factors that influence the behavioral intentions of users and the actual use of an e-learning technology. E-learning acceptance studies mostly use well-known and contemporary acceptance theories and approaches that have been developed and continuously improved over the previous two decades. A quick, non-systematic review has revealed that TAM is the most common ground theory in e-learning acceptance literature. Researchers mostly explain the intentions of a user towards using an e-learning technology by using or extending the TAM research model. A study that would incorporate information from existing e-learning technology acceptance studies in order to provide an objective picture of the results of research using TAM in the previous 10 years was not found. Moreover, to date, none of the research has dealt with explaining whether individual causal effects depend on the type of the user or the e-learning technology type.

The main objectives of this study were to (1) systematically examine existing knowledge in the field of e-learning acceptance, and (2) to statistically compare the size of the effects in the most common causal relationships in order to provide evidence for a moderating role of the user type and e-learning technology type. In this study, we conducted a meta-analysis of 494 causal effect sizes between different factors that were evaluated in 42 independent studies. Hedges’ g statistic was the metric that was used to describe the differences in the arithmetic means of individual studies.

This paper is organized as follows: in the next section, most well-known technology acceptance theories are introduced. The third section describes the research methodology of our study. In the subsequent section, the results of the data analysis are given. In the last section, we present our conclusions and future work.