An empirical study of instructor adoption of web-based learning systems
Introduction
In recent years, web-based learning systems have been widely employed in both educational and non-educational institutions. A report published by the Giga Information Group shows that the percentage of organizations using electronic-learning (e-learning) systems in their employee training programs rose from 21% in 2002 to 75% in 2005. Additionally, nearly 75% of the 129 universities listed in “America’s Best Colleges: 2005s Top National Universities” by US News & World Report used web-based learning systems (e.g., WebCT systems) in 2007. Thus, it is becoming more and more important to apply information technologies/systems to facilitate student learning, enhance instructor teaching performance and reduce educational costs (Pituch and Lee, 2006, Selim, 2007).
Despite the emerging trend of using web-based learning systems to facilitate teaching and learning activities, the number of users of web-based learning systems is not increasing as fast as expected (Ma, Andersson, & Streith, 2005). Russell, Bebell, O’Dwyer, and O’Connor (2003) stated that instructor use of information technologies/systems was a complex and multidirectional issue. Additionally, Pituch and Lee (2006) argued that if users lacked the sufficient motivation and intention to use web-based learning systems, the unused systems would eventually become useless. Therefore, it is critical to identify the factors that influence instructor adoption of web-based learning systems to help policymakers in higher education facilitate their use. A considerable number of studies have been conducted regarding the adoption of web-based learning systems (e.g., Barrero et al., 2008, Hayes, 2007, Ngai et al., 2007, Selim, 2007). However, very little empirical research has been conducted on instructor adoption of web-based learning systems from multiple critical perspectives such as user intention and information system success (e.g., Andersson, 2006, Condie and Livingston, 2007, Franklin, 2007, Thomas and Stratton, 2006, Zhao, 2007). As a result, the aims of this study are:
- (a)
to identify the factors affecting instructor adoption of web-based learning systems in the context of higher education in Taiwan; and
- (b)
to develop and empirically examine an integrated model of adoption of web-based learning systems, incorporating user intention/behavior, information system success and psychology.
This paper is organized as follows: section two presents a review of the literature concerning web-based learning systems, user intention theories, and information system success. Section three presents our theoretical model and research hypotheses. Section four describes the research method of this study, and section five presents the results analyzed by structural equation modeling (SEM). Section six discusses the findings and implications of this study, and section seven concludes this paper.
Section snippets
Web-based learning systems
Since web-based learning systems play an important role in learning performance (Zhao, 2007), many institutions of higher education have implemented them (Selim, 2007). Ngai et al. (2007) found that students who used web-based learning systems learned better than those who did not. Consequently, many have argued that institutions of higher education should focus on developing information technology to facilitate student learning (Sahin & Thompson, 2007).
Gunasekaran, McNeil, and Shaul (2002)
Overview of the proposed research model
Based on the results of a review of the existing technology-adoption-related education literature, in this study the variables of system quality (SQ), information quality (IQ), service quality (SEQ), subjective norm (SN), and self-efficacy (SE) are incorporated in the generic TAM model in order to examine the adoption of web-based learning systems for higher education, while avoiding the drawbacks of any single model discussed previously. The proposed research model consists of nine factors
Development of instruments
To develop an effective survey, 58 items relevant to the nine constructs of the proposed research model were adopted from existing literature and refined based on the specific topic of this study. These items were pilot-tested with 20 instructors from various institutions of higher education to examine internal consistency and reliability using Cronbach’s alpha coefficient analysis. In this method of analysis, if the overall Cronbach’s alpha coefficient of all the items of a construct is
Data analysis and results
SEM was used to test our hypotheses. In the literature, there are many suggestions regarding the minimum sample size needed for the SEM approach. Tanaka (1987) argued that the sample size should be at least five times the number of instruments (49 in this study). Gefen, Straub, and Boudreau (2000) reported that the overall sample size for IS studies using LISREL was between 41 and 451, while the average sample size was 249. Hair, Black, Babin, Anderson, and Tatham (2006) recommended a sample
Discussion
The results of this study implied a number of relationships that determined instructor adoption of web-based learning systems in higher education. First, system quality, service quality, and self-efficacy all increased perceived ease of use. Service quality contributed the more to perceived ease of use than the other two variables. This underlines the importance of effective and timely support provided to assist instructors in using web-based learning systems. System quality, which can be
Conclusion
This study has developed an integrated model for explaining and predicting instructor adoption of web-based learning systems in the context of higher education by incorporating the concepts of user intention/behavior, information system success, and psychology. The proposed model was empirically examined using structural equation modeling. The results provided considerable support for the proposed model. Nine of the 12 hypothesized relationships were found to be significant, providing
Acknowledgements
The authors thank the Editor and anonymous reviewers for their valuable feedback on this paper. This study was funded by the NCKU Project of Promoting Academic Excellence & Developing World Class Research, College of Management, National Cheng Kung University, Taiwan.
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