Skip to main content
SpringerLink
Log in
Book cover

Technology Acceptance in Education pp 43–61Cite as

Student Teachers’ Acceptance of Computer Technology

An Application of the Technology Acceptance Model (TAM)

  • Chapter

Abstract

This chapter report an empirical study focussing on the Malaysian student teachers’ acceptance of computer technology in a leading research university. The TAM will be used as the basis of the theoretical framework. This study investigated 245 Malaysian student teachers’ self-reported intentions to use (ITU) computers. Data collected from these student teachers at Universiti Putra Malaysia were tested against the Technology Acceptance Model (TAM) using the structural modelling approach. The study found perceived usefulness (PU) of computer technology, perceived ease of use (PEU), and attitude towards computer use (ATCU) to be significant determinants of ITU. Additionally, the results of the study revealed that (1) PEU significantly influenced PU; (2) both PU and PEU significantly influenced ATCU, and (3) both PU and ATCU significantly influenced ITU. The results suggest that the TAM is able to predict technology acceptance well among student teachers in Malaysia.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   49.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

REFERENCES

  • Abdalla, I. (2007). Evaluating effectiveness of e-blackboard system using TAM framework: A structural analysis approach. AACE Journal, 15(3), 279–287.

    Google Scholar 

  • Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences, 30(2), 361–391.

    Article  Google Scholar 

  • Aiken, L. R. (1994). Psychological testing and assessment. Massachusetts, MA: Allyn and Bacon.

    Google Scholar 

  • Ajzen, I., & Fishbein, M. (1977). Attitude-behaviour relations, theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888–918.

    Article  Google Scholar 

  • Ajzen, I., & Fishbein, M. (2005). The influence of attitudes on behavior. In D. Albarracín, B. T. Johnson, & M. P. Zanna (Eds.), The handbook of attitudes (pp. 173–221). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. Englewood Cliffs, NJ: Prentice-Hall.

    Google Scholar 

  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.

    Article  Google Scholar 

  • Arbuckle, J. L. (2006). AMOS (version 6.0) [Computer software]. Chicago: SmallWaters.

    Google Scholar 

  • Askar, P., & Umay, A. (2001). Pre-service elementary mathematics teachers’ computer self-efficacy, attitudes towards computers, and their perceptions of computer-enriched learning environments.

    Google Scholar 

  • In C. Crawford, et al. (Eds.), Proceedings of society for information technology and teacher education international conference 2001 (pp. 2262–2263). Chesapeake, VA: AACE.

    Google Scholar 

  • Bai, H., & Ertmer, P. (2008). Teacher educator’s beliefs and technology uses as predictors of preservice teachers’ beliefs and technology attitudes. Journal of Technology and Teacher Education, 16(1), 93–112.

    Google Scholar 

  • Barclay, D., Higgins, C., & Thompson, R. (1995). The Partial Least Squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration. Technology Studies, 2(2), 285–309.

    Google Scholar 

  • Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.

    Article  Google Scholar 

  • Baylor, A. L., & Richie, D. (2002). What factors facilitate teacher skill, teacher morale, and perceived student learning in technology-using classrooms? Computers & Education, 39(4), 395–414.

    Article  Google Scholar 

  • Becker, H. (2001, April). How are teachers using computers in instruction? Paper presented at the 2001 meetings of the American Educational Research Association. Retrieved September 19, 2007, from http://www.crito.uci.edu/tlc/findings/conferences-pdf/how_are_teachers_using.pdf

  • Bollen, K. A. (1989). Structural equations with latent variables. New York: John Wiley & Sons.

    Google Scholar 

  • Bosch, K. A. (1993). Is there a computer crisis in the classroom? Schools in the Middle, 2(4), 7–9.

    Google Scholar 

  • Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications, and programming. Mahwah, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitraitmultimethod matrix. Psychological Bulletin, 56(2), 81–105.

    Article  Google Scholar 

  • Chau, P. Y. K. (1996). An empirical assessment of a modified technology acceptance model. Journal of Management Information Systems, 13(2), 185–204.

    Google Scholar 

  • Chau, P. Y. K. (1997). Reexamining a model for evaluating information center success using a structural equation modeling approach. Decision Sciences, 28(2), 309–334.

    Article  Google Scholar 

  • Chau, P. Y. K. (2001). Influence of computer attitude and self-efficacy on IT usage behaviour. Journal of End-User Computing, 13(1), 26–33.

    Article  Google Scholar 

  • Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189–211.

    Article  Google Scholar 

  • Cuban, L., Kirkpatrick, H., & Peck, C. (2001). High access and low use of technologies in high school classrooms: Explaining an apparent paradox. American Educational Research Journal, 38(4), 813–834.

    Article  Google Scholar 

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Diem, R. (2000). Can it make a difference? Technology and the social studies. Theory and Research in Social Education, 28(4), 493–501.

    Google Scholar 

  • DeVellis, R. F. (2003). Scale development: Theory and applications (2nd ed.). Newbury Park, CA: SAGE Publications.

    Google Scholar 

  • Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task-technology fit constructs. Information & Management, 36(1), 9–21.

    Article  Google Scholar 

  • Drennan, J., Kennedy, J., & Pisarksi, A. (2005). Factors affecting student attitudes toward flexible online learning in management education. The Journal of Educational Research, 98(6), 331–340.

    Article  Google Scholar 

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 48, 39–50.

    Article  Google Scholar 

  • Fornell, C., Tellis, G. J., & Zinkhan, G. M. (1982). Validity assessment: A structural equations approach using partial least squares. In B. J. Walker, et al. (Eds.), An assessment of marketing thought & practice (pp. 405–409). Chicago: American Marketing Association.

    Google Scholar 

  • Gaddis, S. E. (1998). How to design online surveys. Training & Development, 52(6), 67–72.

    Google Scholar 

  • Gao, Y. (2005). Applying the Technology Acceptance Model (TAM) to educational hypermedia: A field study. Journal of Educational Multimedia and Hypermedia, 14(3), 237–247.

    Google Scholar 

  • Gefen, D., & Straub, D. W. (1997). Gender differences in the perception and uses of email: An extension to the Technology Acceptance Model. MIS Quarterly, 21(4), 389–400.

    Article  Google Scholar 

  • Green, S. B., Salkind, N. J., & Akey, T. M. (2000). Using SPSS for windows (2nd ed.). New Jersey, NJ: Prentice-Hall International.

    Google Scholar 

  • Hair, J. F. Jr., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). New Jersey, NJ: Prentice-Hall International.

    Google Scholar 

  • Hu, P. J., Chau, P. Y. K., Liu, O. R., & Yan, K. (1999). Examining the Technology Acceptance Model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91–112.

    Google Scholar 

  • Hu, P. J., Clark, T. H. K., & Ma, W. W. (2003). Examining technology acceptance by school teachers: A longitudinal study. Information & Management, 41(2), 227–241.

    Article  Google Scholar 

  • Huang, H. M., & Liaw, S. S. (2005). Exploring user’s attitudes and intentions toward the web as a survey tool. Computers in Human Behaviour, 21(5), 729–743.

    Article  Google Scholar 

  • Jackson, C. M., Chow, S., & Leitch, R. A. (1997). Toward an understanding of the behavioural intention to use an information system. Decision Sciences, 28(2), 357–389.

    Article  Google Scholar 

  • Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). New York: Guilford Press.

    Google Scholar 

  • Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the Technology Acceptance Model. Information & Management, 40, 191–204.

    Article  Google Scholar 

  • Ma, W. W. K., Andersson, R., & Streith, K. O. (2005). Examining user acceptance of computer technology: An empirical study of student teachers. Journal of Computer Assisted Learning, 21, 387–395.

    Article  Google Scholar 

  • Malhotra, Y., & Galletta, D. (1999). Extending the Technology Acceptance Model to account for social influence: Theoretical bases and empirical validation. Paper presented at the Thirty-Second Annual

    Google Scholar 

  • Hawaii International Conference on System Sciences. Retrieved January 1, 2008, from http://www.brint.org/technologyacceptance.pdf

  • Mathieson, K. (1991). Predicting user intentions: Comparing the Technology Acceptance Model with the theory of planned behaviour. Information Systems Research, 2(3), 173–191.

    Article  Google Scholar 

  • McCoy, S., Galletta, D., & King, W. (2007). Applying TAM across cultures: The need for caution. European Journal of Information System, 16, 81–90.

    Article  Google Scholar 

  • Melor, M. Y. (2007). Malaysian ESL teachers’ use of ICT in their classrooms: Expectations and realities. ReCALL, 19(1), 79–95.

    Article  Google Scholar 

  • Ministry of Education. (2006). National education blueprint. Putrajaya: Government of Malaysia.

    Google Scholar 

  • Mitra, A., Lenzmeier, S., Steffensmeier, T., Avon, R., Qu, N. & Hazen, M. (2000). Gender and computer use in an academic institution: Report from a longitudinal study. Journal of Education Computing Research, 23(1), 67–84.

    Article  Google Scholar 

  • Moon, J., & Kim, Y. (2001). Extending the TAM for a world-wide-web context. Information & Management, 38(4), 217–230.

    Article  Google Scholar 

  • Multimedia Development Corporation. (2005). Malaysian smart school roadmap 2005–2020: An educational odyssey. Putrajaya: Government of Malaysia.

    Google Scholar 

  • Multimedia Development Corporation. (2006). Impact assessment study on the smart school integrated solution and other ICT initiatives. Putrajaya: Government of Malaysia.

    Google Scholar 

  • Ndubisi, N. (2006). Factors of online learning adoption: A comparative juxtaposition of the theory of planned behaviour and the technology acceptance model. International Journal on E-Learning, 5(4), 571–591.

    Google Scholar 

  • Ngai, E. W. T., Poon, J. K. L., & Chan, Y. H. C. (2007). Empirical examination of the adoption of WebCT using TAM. Computers and Education, 48, 250–267.

    Article  Google Scholar 

  • Oblinger, D. G., & Rush, S. C. (1997). The learning revolution: The challenge of information technology in academy. Bolton, MA: Anker Publishing Company.

    Google Scholar 

  • Riemenschneider, C. K., Harrison, D. A., & Mykytn, P. P., Jr. (2003). Understanding IT adoption decisions in small business: Integrating current theories. Information & Management, 40(4), 269–285.

    Article  Google Scholar 

  • Sadiq, A. (2006). Factors influencing teachers’ attitudes toward personal use and school use: New evidence from a developing nation. Evaluation Review, 30(1), 86–113.

    Article  Google Scholar 

  • Schumacker, R. E., & Lomax, R. G. (2010). A beginner' guide to structural equation modeling (3rd ed.). New York: Routledge.

    Google Scholar 

  • Shiue, Y. M. (2007). Investigating the sources of teachers’ instructional technology use through the decomposed theory of planned behaviour. Journal of Educational Computing Research, 36(4), 425–453.

    Article  Google Scholar 

  • Sime, D., & Priestly, M. (2005). Student teachers’ first reflections on information and communications technology and classroom learning: Implications for initial teacher education. Journal of Computer Assisted Learning, 21, 130–142.

    Article  Google Scholar 

  • Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Thompson, B., & Daniel, L. G. (1996). Factor analytic evidence for the construct validity of scores: A historical overview and some guidelines. Educational and Psychological Measurement, 56, 197–208.

    Article  Google Scholar 

  • Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124–143.

    Article  Google Scholar 

  • Trochim, W. M. K. (1999). Convergent and discriminant validity. Retrieved November 30, 1999, from http://www.trochim.human.cornell.edu/kb/convdisc.htm

  • Woodrow, J. E. J. (1991). A comparison of four computer attitude scales. Journal of Educational Computing Research, 7(2), 165–187.

    Article  Google Scholar 

  • Wong, S. L., Kamariah, A. B., & Tang, S. H. (2006). Using a Student Centred Learning (SCL) approach to teach a discrete Information Technology (IT) course: The effects on Malaysian pre-service teachers’ attitudes toward IT? Technology, Pedagogy and Education, 15(2), 223–238.

    Article  Google Scholar 

  • Wozney, L., Venkatesh, V., & Abrami, P. C. (2006). Implementing computer technologies: Teachers’ perceptions and practices. Journal of Technology and Teacher Education, 14(1), 173–207.

    Google Scholar 

  • 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.

    Google Scholar 

  • Yuen, A., & Ma, W. (2002). Gender differences in teacher computer acceptance. Journal of Technology and Teacher Education, 10(3), 365–382.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Universiti Putra Malaysia, Malaysia

    Wong Su Luan

  2. Nanyang Technological University, Singapore

    Timothy Teo

Authors
  1. Wong Su Luan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Timothy Teo
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Nanyang Technological University, Singapore

    Timothy Teo

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Sense Publishers

About this chapter

Cite this chapter

Luan, W.S., Teo, T. (2011). Student Teachers’ Acceptance of Computer Technology. In: Teo, T. (eds) Technology Acceptance in Education. SensePublishers. https://doi.org/10.1007/978-94-6091-487-4_3

Download citation

Publish with us

Policies and ethics

Societies and partnerships

Search

Navigation