Modelling the Influences of Beliefs on Preservice Teachers' Attitudes towards Computer Use

Year 2012, , 13 - 22, 15.01.2012

Timothy Teo

https://doi.org/10.12973/eu-jer.1.1.13

Abstract

The purpose of this study is to examine the pre-service teachers’ attitudes toward computers use. The impact of five variables (perceived usefulness, perceived ease of use, subjective norm, facilitating conditions, and technological complexity) on attitude towards computer was assessed. Data were collected from 230 preservice teachers through self-report and structural equation modelling was used as the technique for analysis. Results showed that 64% of the variance in attitude towards computer use was explained by the five exogenous variables. In addition, perceived usefulness, subjective norm, and technological complexity were found to be significant influences on attitude toward computer use while perceived ease of use and facilitating conditions did not.

Keywords

pre-service teachers, beliefs, attitudes towards computer use, structural equation modeling

References

• Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modelling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3): 411-423.
• Arbuckle, J. L. (2006). AMOS (Version 7.0) [Computer Program]. Chicago: SPSS.
• Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York: Guilford
• Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology a comparison of two theoretical models. Management Science, 35(8), 928-1003.
• Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley
• Fornell, C., & Larcker, D. F. (1981) Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 48, 39-50.
• Grainger, R., & Tolhurst, D. (2005). Organisational factors affecting teachers¹ use and perception of information and communications technology. In Proceedings. South East Asia Regional Computer Confederation (SEARCC) Conference 2005: ICT Building Bridges, Sydney, Australia. CRPIT, 46. Low, G., Ed. ACS. 13-22.
• Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2010). Multivariate data analysis: A global perspective. Upper Saddle River: Pearson.
• Huang, H. M., & Liaw, S. S. (2005). Exploring user’s attitudes and intentions toward the web as a survey tool. Computers in Human Behavior. 21(5), 729-743.
• Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd Ed.). New York: Guilford Press.
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd Ed.). New York: McGraw-Hill.
• Pituch, K., & Lee, Y. K. (2006). The influence of system characteristics on e-learning use. Computers and Education, 47(2), 222-44.
• Raykov, T., & Marcoulides, G. A. (2008). An Introduction to Applied Multivariate Analysis. New York: Taylor & Francis.
• Schumacker, R. E., & Lomax, R. G. (2010). A beginner's guide to structural equation modeling (3rd ed.). New York: Routledge.
• Shapka, J. D. & Ferrari, M. (2003). Computer-related attitudes and actions of teacher candidates. Computers in Human Behaviour, 19(3), 319-334.
• Sime, D. and Priestley, M. (2005). Student teachers' first reflections on ICT in classroom learning: implications for Initial Teacher Education. Journal of Computer Assisted Learning, 21(2), 130-143.
• Teo, T. (2006). Attitudes toward computers: a study of post-secondary students in Singapore. Interactive Learning Environments. 14(1), 17-24.
• Teo, T. (2008). Pre-service teachers' attitudes towards computer use: A Singapore survey. Australasian Journal of Educational Technology, 24(4), 413-424.
• Teo, T. (2009). Modelling technology acceptance in education: A study of pre- service teachers. Computers & Education, 52(1), 302-312.
• Teo, T. (2010). A path analysis of pre-service teachers' attitudes to computer use: Applying and extending the Technology Acceptance Model in an educational context. Interactive Learning Environments, 18(1), 65-79
• Teo, T., Lee, C. B., & Chai, C. S. (2008). Understanding pre-service teachers’ computer attitudes: applying and extending the Technology Acceptance Model (TAM). Journal of Computer Assisted Learning, 24(2), 128-143.
• Teo, T., Wong, S. L., Chai, C. S. (2008). A cross-cultural examination of the intention to use technology between Singaporean and Malaysian pre-service teachers: an application of the Technology Acceptance Model (TAM). Educational Technology & Society, 11(4), 265–280.
• Teo, T., & Van Schaik, P. (2009). Understanding technology acceptance among pre-service teachers: a structural equation modeling approach. The Asia-Pacific Education Researcher, 18(1), 47-66
• Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: toward a conceptual model of utilization. MIS Quarterly, 15(1), 124-143.
• Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186-204.
• Wong, S. L., Ng, S. F., Nawawi, M., & Tang, S. H. (2005). Experienced and inexperienced internet users among pre-service teachers: Their use and attitudes toward the Internet. Journal of Educational Technology and Society, 8(1), 90-103.
• Yildirim, S. (2000). Effects of an educational computing course on pre-service and inservice teachers: a discussion and analysis of attitudes and use. Journal of Research on Computing in Education. 32(4), 479-495.