Understanding Student Teachers’ Behavioural Intention to Use Technology: Technology Acceptance Model (TAM) Validation and Testing

Öz

This study sets out to validate and test the Technology Acceptance Model (TAM) in the context of Malaysian student teachers’ integration of their technology in teaching and learning. To establish factorial validity, data collected from 302 respondents were tested against the TAM using confirmatory factor analysis (CFA), and structural equation modelling (SEM) was used for model comparison and hypotheses testing. The goodness-of-fit test of the analysis shows partial support of the applicability of the TAM in a Malaysian context. Overall, the TAM accounted for 37.3% of the variance in intention to use technology among student teachers and of the five hypotheses formulated, four are supported. Perceived usefulness is a significant influence on attitude towards computer use and behavioural intention. Perceived ease of use significantly influences perceived usefulness, and finally, behavioural intention is found to be influenced by attitude towards computer use. The findings of this research contribute to the literature by validating the TAM in the Malaysian context and provide several prominent implications for the research and practice of technology integration development

Anahtar Kelimeler

• Technology Acceptance Model, Computer Use, Student Teachers, Behavioural Intention, Use Technology

Understanding Student Teachers’ Behavioural Intention to Use Technology: Technology Acceptance Model (TAM) Validation and Testing

Öz

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Anahtar Kelimeler

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Kaynakça

1. Ajzen, I. (1985). From intentions to actions: A theory of planned behaviour. In J. Kuhl, J. Beckmann (eds). Action Control: from Cognition to Behavior. New York: Springer Verlag, 11-39.
2. Ajzen, I. & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. New Jersey: Prentice-Hall.
3. Akbab-Altum, S. (2006). Complexity of integrating computer technologies into education in Turkey. Educational Technology and Society. 9(1),176-187.
4. Antonio, P., Aurora, G., & Ana, R.D.A. (2008). Factors affecting e-collaboration technology use among management students. Computer & Education, 51(2), 609-623.
5. Arbuckle, J.L. (2005). Amos 6.0 user’s guide. Chicago, IL: SPSS, Inc.
6. Chen, R. (2010). Investigating models for preservice teachers’ use of technology to support student-centered learning. Computer and education, 55, 32-42.
7. Compeau, D.R., & Higgins, C.A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
8. Davis, F.D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. Management Information Systems Quarterly. 13 (3), 983100

9. 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), 982100
10. Efe, R. (2011). Science student teachers and educational technology: Experience, intentions and value. Educational technology & society, 14(1), 228-240.
11. Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Reading MA: Addison-Wesley.
12. Hair, J.F. (2010). Multivariate data analysis: a global perspective. Upper Saddle River, NJ: Person Prentice Hall.
13. Kline, R. B. (2005). Principles and practice of structural equation modelling (2nd ed.). New York: Guilford Press.
14. Lin, K. (2011). E-learning continuance intention: Moderating effects of user e-learning experience. Computer & Education. 56(2), 515-526.
15. Liu, F., Chen, M.C., Sun, Y.S., Wible, D., & Kuo, C. (2010). Extending the TAM model to explore the factors that affect intention to use an online learning community. Computer & Technology, 54(2), 600-610.
16. McDonald, R.P., & Ho, M-H, R. (2002). Principles and practice in reporting structural equation analyses. Psychological Methods, 7, 64 – 82.
17. Ministry of Education. (1997). Smart School Flagship Application: The Malaysian Smart School – A conceptual blueprint. Putrajaya: Government of Malaysia.
18. Ministry of Education (2006). National Education Blueprint. Putrajaya :Government of Malaysia.
19. Moran, M., Hawkes, M., & Gayar, O.E. (2011). Tablet personal computer integration in higher education: Applying the unified theory of acceptance and use technology model to understand supporting factors. Journal of Educational Computing Research. 42(1), 79Park, S.Y. (2009). An analysis of the technology acceptance model in understanding university student’s behavioural intention to use e-learning. Educational Technology & Society, 12 (3), 150-162.
20. Pynoo, B., Devolder, P., Tondeur, J., Braak, J., Duyck, W. & Dyck, P. (2011) Predicting secondary school teachers’ acceptance and use of a digital learning environment: A cross-sectional study. Computers in Human Behavior, 27(2), 568-575.
21. Sekaran, U. (2003). Research Methods for Business. A Skill Building Approach. (fourth edition), Cambridge Massachusetts: Harvard University Press.
22. Šumak, B., Hericko, M., Pusnik, M., & Polancic, G. (2011). Factors affecting acceptance and use of Moodle: an empirical study based on TAM. Slovenian Society Informatika, 35(1), 91-100.
23. Taylor, S., & Todd, P. (1995). Understanding information technology usage: A test of competing models. Information Systems Research 6(2), 144 -176.
24. Terzis, V., & Economides, A.A. (2011). The acceptance and use of computer based assessment. Computer & Education, 56(4), 1032-1044.
25. Teo, T. (2011). Factors influencing teachers’ intention to use technology: Model development and test. Computers & Education, doi: 10.1016/j.compedu.2011.06.008
26. Teo, T. (2010). Efficiency of the technology acceptance model to explain pre-service teachers’ intention to use technology. A Turkish study. Campus Wide Information System, 28(2). 93-101.
27. Teo, T., & Schaik, P.V. (2009). Understanding technology acceptance in pre-service teachers: A structural equation modelling approach. The Asia Pacific Education Research, 18(1), 47-66.
28. Teo, T. (2009). The impact of subjective norm and facilitating conditions on pre-service teachers’ attitude toward computer use: a structural equation modelling of an extended technology acceptance model. Journal educational computing research, 40(1), 89-109.
29. Teo, T., & Noyes, J. (2011). An assessment of the influence of perceived enjoyment and attitude on the intention to use technology among pre-service teachers: A structural equation modelling approach. Computer & Technology, 57(2), 1645-1653.
30. Teo, T., Wong, S.L., & Chai, C.S. (2008). A cross-cultural examination of the intention to use technology between Singaporean and Malaysia pre-service teachers: An application of the TAM. Educational & Society, 11(4), 265-280.
31. Thompson, R.L., Higgins, C.A., & Howell, J.M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124 -143.
32. Venkatesh, V. (2000). Determinants of perceived ease of use Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Information Systems Research 11(4), 342-365.
33. Venkatesh, V.,& Davis, F.D. (2000). A theoretical extension of technology acceptance model: Four longitudinal field studies. Management Science, 46, 186-204.
34. Venkatesh, V., & Morris, M.G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.
35. Venkatesh, V., Morris, M.G., Davis, G.B., & Davis, F.D. (2003). User acceptance of information technology: Toward a unified view. MIS Quaterly, 27(3), 425 – 478.
36. Wang, W., & Wang, C. (2009). An empirical study of instructor adoption of web-based learning systems. Computer & Education, 53(3), 761-774.
37. Wong, K.T., Goh, S.C., Hafizul Fahri, & Rosma Osman (2010). Computer attitudes and use among novice teachers: The moderating effects of school environment. Malaysian Journal of Learning and Instruction, 7, p. 93-112.
38. Wong, S.L., & Teo, T. (2009). Investigating the technology acceptance among student teachers in Malaysia: An application of the technology acceptance model (TAM). The Asia-Pacific Education Researcher, 18(2), 261-272. Appendix 1
39. Constructs and corresponding items Item Statement Reference Perceived Usefulness (PU) PU1 I could improve my performance by using computers. Davis (1989), Venkatesh et al. (2003), and Teo (2009) PU2 I could increase my productivity by using computers. PU3 I could enhance my effectiveness by using computers. Perceived Ease of Use (PEU) PEU1 It is easy for me to do works that I want to do by using computers. Davis (1989), Venkatesh et al. (2003), and Teo (2009) PEU2 I find computers easy to use. PEU3 My interaction with computers is clear and understandable. Attitude Toward Computer Use (ATCU) ATCU1 Working with computers make learning more interesting. Compeau and Higgins (1995), Thompson et al. (1991), and Teo (2009) ATCU2 Working with computers is fun. ATCU3(dropped) I look forward to that job that requires me to use computers. Behavioural Intention (BI) BI 1 Whenever possible, I intend to use computers for teaching and learning.