Type of Document Dissertation Author Park, Byungho URN etd-08182004-111239 Title Faculty Adoption and Utilization of Web-Assisted Instruction (WAI) in Higher Education: Structural Equation Modelling (SEM) Degree Doctor of Philosophy Department Educational Psychology and Learning Systems, Department of Advisory Committee
Advisor Name Title John Keller Committee Chair Beverly Bower Committee Member Mary Driscoll Committee Member Walter Wager Committee Member Keywords
- Higher Education
- Structural Equation Modeling
- Web Instruction
Date of Defense 2003-12-01 Availability unrestricted Abstractviii
For a number of years, we have heard that computers, or information technologies, are
going to change higher education – the way we teach and the way our students will learn. But
most of us have seen little evidence to support the claim. In fact, faculty utilization of innovative
technologies has remained low (Surry and Land, 2000). In the 1997 National Survey of
Information Technology in Higher Education in the United States, Green (1997, in Houseman,
1997) reports that only 12.2% of the institutions surveyed recognize information technology in
the career path of faculty. Thus, to accomplish the optimal use of information technology (Web-
Assisted Instruction (WAI) in this study), an analysis of the factors affecting the WAI use should
A number of studies have been performed to identify factors affecting the likelihood of
adoption of instructional technology in educational setting. Most of the studies have been based
their theoretical foundation on Roger’s adoption/ diffusion model. However, they have mostly
reported the influencing factors based on the regression-based approach, not focusing on the
interactional relationship among the factors.
Recently, there have been a few models developed and empirically studied to find out the
interactional effects of variable on innovation usage. Among those models, the three models
(Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB), and Technology
Acceptance Model (TAM)) seem to be of importance and related to the present study.
Based on the results of these models and other studies, this study developed and tested a
study model, which included seven adoption predictors in terms of three perspectives and a
criterion variable as the followings; (1) personal characteristics (Computer Experience & Selfefficacy);
(2) perceived attributes of innovation (Complexity & Relative Advantage); and (3)
perception of influence and support from the environment (Subjective Norm, Supports, & Time);
lastly, (4) the criterion variable, level of WAI use (LoWU).
With those identified variables the present study will be performed to build a model that
will predict the level of adoption and utilization with regard to instructional technology use by
university faculty members. To accomplish the purpose, the Structural Equation Modeling
(SEM) including Confirmatory Factor Analysis was employed to test the hypothesized study
model for the determination of faculty members’ WAI use.
The result showed that a study model as described produced measurement and structural
models with adequate model fits. In addition, five factors, computer experience, subjective norm,
self-efficacy, relative advantage, and complexity, were identified in the analysis as the important
predictors of LoWU. Interestingly, while relative advantage and subjective norm were significant
in direct effect on LoWU, computer experience, self-efficacy, and complexity showed only
indirect effects significant towards LoWU. Supports and Time showed no significant effect.
However, ironically qualitative data revealed that most faculty members perceived lack of
support and time as barriers for their successful participation in using WAI technology in their
The research provides a base to build on for other studies, specifically targeting
acceptance models of web-related instructional technology use. The research can also add to the
expanding base of research investigating technology adoption models outside higher education.
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