Measuring Gender Differences in Technology Acceptance: A Measurement Invariance Analysis

By Teo, Timothy | International Journal of Instructional Media, Summer 2011 | Go to article overview
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Measuring Gender Differences in Technology Acceptance: A Measurement Invariance Analysis

Teo, Timothy, International Journal of Instructional Media


An important the theme in technology acceptance research is the issue of gender differences. From the past research, many factors have been shown to explain gender differences in technology acceptance. For example, computers were often linked to traditionally 'masculine' subjects such as science and mathematics (Hawkins, 1985). Bernstein (1992) suggested that most introductory computer science classes ought to concentrate on applications rather than on math or programming as by doing so would remove the perception that certain subjects are targeted at the male gender. Gender differences in computer attitudes may be reflected in computer software, especially computer games. Since society in general tends to stereotype females into weak dependent roles, the stereotypical woman in most computer games is weak, and if she is a main character, she should be modeled to be attractive e.g. slim and scantily clad. One study of mathematical software reported that the number of female characters declined, and the amount of violence increased, as the grade level the software was directed at increased (Chappell, 1996). This gender bias influences children's interest in playing electronic games: boys play more than girls and prefer more realistic and violent games (Funk & Buchman, 1996).

Research has also shown that, in the primary and middle school level, it was more socially acceptable for boys to play computer games, and those boys who play computer games are perceived as more popular than girls who do so (Funk & Buchman, 1996). Computer use at home has been found to correlate positively with computer attitudes (Seyal, Rahim, & Rahman, 2000). Where computers are available at home, it was reported that boys are more likely than girls to become interested in computers. In this respect, more male than female students had reported as having a home computer (Volman, 1997) and more male than female students reported having access to home computers (Dugdale et al., 1998), having used computers at home (Colley et al., 1994), and having access to and using a home computer at least once a week (Comber et al., 1997).

Recent studies also found that females respond to technology in ways that are different than males (e.g., Broos, 2005; Liaw, 2002; Teo, 2010a). For example, Suri (2003) reported that female teachers expressed less interest in technology and placed lesser importance on computers in the teaching and learning process. Conversely, their male counterparts demonstrated greater interest in computers and a higher level of confidence in their ability to use technology. This situation was the same when applied to advanced technology skills--females perceive themselves as being less able and interested (Zarrett & Malanchuk, 2005). For this reason, it was possible that females may not choose a career related to technology despite the availability of opportunities for both genders in the computing industry (Anderson, Lankhear, Timms, & Courtney, 2008).

Technology Acceptance

User acceptance refers to a willingness to adopt information technology for the tasks it has been designed to support. For some time, procurers of technology could rely on organizational authority to ensure that technology was used, as in the case of many business entities. However, the changing working practices in recent years among many organizations have enabled greater discretion among technology users. As such there is a need to consider the dynamics of users' acceptance and how this impacts on technology adoption and usage in their work environments. For this reason, many studies on technology acceptance have emerged in the information science literature in recent years (Smarkola, 2007).

Among these studies, researchers have investigated how users' beliefs and attitudes affect their technology usage behaviors (e.g., Davis, 1989; Davis, Bagozzi & Warshaw, 1989; Venkatesh & Davis, 2000).

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Measuring Gender Differences in Technology Acceptance: A Measurement Invariance Analysis


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