Murdoch University Research Repository

Welcome to the Murdoch University Research Repository

The Murdoch University Research Repository is an open access digital collection of research
created by Murdoch University staff, researchers and postgraduate students.

Learn more

Measuring the effect of gender on computer attitudes among pre‐service teachers

Teo, T.ORCID: 0000-0002-7552-8497 (2010) Measuring the effect of gender on computer attitudes among pre‐service teachers. Campus-Wide Information Systems, 27 (4). pp. 227-239.

Link to Published Version:
*Subscription may be required


Purpose: The purpose of this paper is to examine the effect of gender on pre-service teachers' computer attitudes. Design/methodology/approach: A total of 157 pre-service teachers completed a survey questionnaire measuring their responses to four constructs which explain computer attitude. These were administered during the teaching term where participants were attending a technology course. Structural equation modeling, in particular, confirmatory factor analysis and multiple indicators, multiple causes (MIMIC) modeling were used for data analysis. Findings: No statistical significance is found for gender in the four constructs of computer attitude. However, the mean scores for males are higher for three of the constructs. Overall, the data in this study provides evidence to support the notion that computer attitude is a multidimensional construct. Originality/value: This study contributes to the continuing interests among researchers to study the effect of gender towards the computer. The results of this study did not support others which found significant differences in computer attitudes by gender. This may be due to heavy reliance of computers in many educational institutions for teaching and learning which consequently granted equal access to male and female users. Methodologically, this study had employed MIMIC model as the technique to assess the effect of gender on computer attitude. MIMIC modeling is superior to conventional techniques (e.g. t-test, ANOVA) because it is capable of analyzing latent and observed indicators.

Item Type: Journal Article
Publisher: Emerald Group Publishing Limited
Copyright: © 2010 Emerald Group Publishing Limited
Item Control Page Item Control Page