Academic journal article Educational Technology & Society

A Structural Equation Model for ICT Usage in Higher Education

Academic journal article Educational Technology & Society

A Structural Equation Model for ICT Usage in Higher Education

Article excerpt

With the ongoing development of ICT and the diversification of the fields it affects, various theoretical studies have been carried out in order to ensure better understanding concerning its diffusion, adoption, acceptance, and usage (Davis, 1989; Taylor & Todd, 1995; Venkatesh & Davis, 2000; Rogers, 2003; Venkatesh, Morris, Davis, and Davis, 2003; Yi, Jakson, Park, and Probst, 2006).

In this study, the concept ICT "usage" is preferred since it is believed that usage is an indicator of adoption, acceptance as well as diffusion. In his Diffusion of Innovation (DoI) theory Rogers (2003) mentions that the rate of adoption is partially influenced by perceived attributes named as innovation characteristics which are relative advantage, compatibility, trialability, complexity, and observability. The relative advantage, compatibility, trialability, observability of an innovation, as perceived by members of a social system, are positively related to its rate of adoption; on the other hand the complexity of an innovation, as perceived by members of a social system, is negatively related to its rate of adoption.

The theory is used to explain the diffusion of innovation in numerous fields such as medicine, agriculture, and information technologies. Rogers (2003, p. 223) stated that, "The first research on attributes of innovation and their rate of adoption was conducted with farmers, but studies of teachers and school administrators suggested that similar attributes predict the rate of adoption for educational innovation." Bussey, Dormody, and VanLeeuwen (2000) stated that the strongest predictor of the level of adoption of technology education was the perception of the teacher of the attributes of technology education. The researchers also concluded that Rogers' theory of perceived attributes can be a valuable tool for instructional developers working to increase the utilization of their products.

There is a consensus on the idea that the prediction power of certain innovation characteristics is different from the prediction power of other innovation characteristics; while, there is a disagreement about innovation characteristics. For instance, A[degrees]kar, Usluel, and Mumcu (2006) stated that complexity or ease of use was found to be a common perceived innovation characteristic for teaching delivery, preparation, and managerial tasks in schools; observability is a perceived attribute in teaching delivery in some specific tasks performed during the class period whereas relative advantage and compatibility are for teaching preparation tasks. Yi et al. (2006) reported that the conclusion of subsequent studies put evidence that relative advantage, complexity, result demonstrability, and image are among the most important factors in predicting users' intentions to make use of technology. In a study on the use of the Internet as an instructional tool carried out in Brasil (Martins, Steil, and Todesco, 2004) it is found out that two most significant predictors are trialability and observability. Mumcu (2004) highlighted in her research that there is a positive relationship between relative advantage, compatibility, and visibility with the use of ICT in vocational and technical schools. Surry and Gustafson (1994) concluded that compatibility, complexity, and relative advantage can be important considerations when introducing an innovation into instructional settings.

A study focused on perceived innovation characteristics and the differences in prediction powers concludes that it may be related to the innovation itself, the usage of innovation, and culture. In an intercultural study carried out in three countries, Japan, Switzerland, and the United States, making use of Technology Acceptance Model, the results indicate that TAM holds for both the U.S. and Switzerland, but not for Japan, suggesting that the model may not predict technology use across all cultures (Straub, Keil, and Brenner, 1997). …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.