ReviewA meta-analysis of e-learning technology acceptance: The role of user types and e-learning technology types
Highlights
► We synthesize existing e-learning acceptance literature. ► TAM is the most common theory in e-learning acceptance literature. ► We conduct a meta-analysis of the causal effect sizes for TAM-related paths. ► User and technology related factors have a moderating role in several paths. ► PEOU and PU influence user’s ATU similarly for different user and e-learning types.
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.
Section snippets
Backgrounds: information technology acceptance theories
In information technology (IT) acceptance literature, there are different streams of research that examine how and why individuals adopt new information technology. According to Venkatesh, Morris, Davis, and Davis (2003), IT adoption research can be distinguished between (a) research that focuses on the individual acceptance of IT, in which the behavioral intentions of users, or actual use, are used as a dependent variable, and (b) research that is more focused on implementation success at the
Research methodology
To answer the above-stated research questions, a systematic review of existing literature was conducted in order to collect empirical data about e-learning acceptance. After the literature review, a meta-analysis was conducted to combine various results, taking into account the relative sample and effect sizes (King & He, 2006).
Studies relevant to the analysis were sought based on a combination of keywords, either related to acceptance theories (TAM, TTF, UTAUT, etc.) or keywords related to
Data analysis
The statistical analysis was based on 494 records about causal relationships, evaluated in the systematic literature review process. First, a descriptive analysis of causal effects was carried out. Then, the search for possible moderator variables was performed by conducting a meta-analysis on effect sizes regarding user type and e-learning technology type.
Conclusion
The purpose of our effort was to combine several independent studies about the individual acceptance and use of e-learning technologies and extract a general conclusion from existing knowledge. The main objective of the study was to search for the mean causal effect size in TAM-related causal relationships and to explain whether there are, in fact, factors that may have a moderating role in these relationships. A review of literature showed that TAM is the most-used theory in e-learning
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