Research article of American Journal of Educational Research and Reviews
Measure for Assesing Religious Teacher’s Perception of Intention to Adopt Virtual Learning Environment (VLE)
Ahmad Shidki Mat Yusoff
Tatvan Vocational School, Bitlis Eren University, Bitlis, Turkey
This study was conducted to produce empirical evidence of validity and reliability of a set of questionnaire. Questionnaire drawn from the results of previous studies and the validity of the tests will determine whether all aspects of the construct domain were represented, thus ensuring the high objectivity level of the questionnaire. In addition, an alternative approach was used to assess the discriminant validity, using heterotrait-monotrait ratio of correlations. The study empirically proves that the questionnaire used is unchanged by culture. This is important because if not, its use will be restricted to a population in which the questionnaire was developed.
Keywords: Religious Teacher’s Perception, Virtual Learning Environment (VLE)
How to cite this article:
Ahmad Shidki Mat Yusoff. Measure for Assesing Religious Teacher’s Perception of Intention to Adopt Virtual Learning Environment (VLE). American Journal of Educational Research and Reviews, 2017,2:10.
1 Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.
2 Bullinger, M., Anderson, R., Cella, D., & Aaronson, N. (1993). Developing and evaluating cross-cultural instruments from minimum requirements to optimal models. Quality of Life Research, 2(6), 451-459.
3 Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Mar-coulides (Ed.), Modern methods for business research (pp. 295–336). Mahwah NJ: Lawrence Erl-baum Associates.
4 Cook, T. D., Campbell, D. T., & Day, A. (1979). Quasi-experimentation: Design & analysis issues for field settings (Vol. 351): Houghton Mifflin Boston.
5 Colton, D., & Covert, R. W. (2007). Designing and constructing instruments for social research and evaluation: John Wiley & Sons.
6 Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. psychometrika, 16(3), 297-334.
7 Davis. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340 doi:310.2307/249008
8 Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340 doi:310.2307/249008
9 Esposito Vinzi, V., Chin, W. W., Henseler, J., & Wang, H. (2010). Handbook of partial least squares: Concepts, methods and applications.
10 Fornell, C., & Bookstein, F. L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 440-452.
11 Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 39-50.
12 Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: an organizational capa-bilities perspective. Journal of Management Information Systems, 18(1), 185–214.
13 Hair, J. F. (2010). Multivariate data analysis.
14 Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414-433.
15 Hair, J. F., Tatham, R. L., Anderson, R. E., & Black, W. (2006). Multivariate data analysis (Vol. 6): Pearson Prentice Hall Upper Saddle River, NJ.
16 Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135.
17 Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Industrial Management & Data Systems, 116(1), 2-20.
18 Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic management journal, 20(2), 195-204.
19 Hung, M.-C., Chang, I.-C., & Hwang, H.-G. (2011). Exploring academic teachers’ continuance toward the web-based learning system: The role of causal attributions. Computers & Education, 57(2), 1530-1543.
20 Kline, R. B. (2011). Principles and practice of structural equation modeling. New York: Guilford Press. Teo, T. S. H.,
21 Lin, W.-S. (2012). Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives. International Journal of Human-Computer Studies, 70(7), 498-507.
22 Ministry of Education Malaysia (2012) Preliminary report of Malaysia Education Blueprint 2013-2025 Putrajaya: Ministry of Education Malaysia.
23 Ministry of Education Malaysia (2016). Malaysia Education Blueprint 2015 Putrajaya: Ministry of Ed-ucation Malaysia.
24 Ministry of Finance Malaysia. Feedback on Report of the Auditor General, 2013 (Series 3 in 2013).
25 McGill, T. J., & Klobas, J. E. (2009). A task–technology fit view of learning management system impact. Computers & Education, 52(2), 496-508.
26 Motaghian, H., Hassanzadeh, A., & Moghadam, D. K. (2013). Factors affecting university instructors’ adoption of web-based learning systems: Case study of Iran. Computers & Education, 61, 158-167.
27 Nunnally, J. (1994). Bernstein, IH (1994). Psychometric theory: New York: McGraw-Hill.
28 Nunnally, J. C., Bernstein, I. H., & Berge, J. M. t. (1967). Psychometric theory (Vol. 226): McGraw-Hill New York.
29 Raykov, T. (2007). Reliability if deleted, not ‘alpha if deleted’: Evaluation of scale reliability following component deletion. British Journal of Mathematical and Statistical Psychology, 60(2), 201-216.
30 Sechrest, L., Fay, T. L., & Zaidi, S. H. (1972). Problems of translation in cross-cultural research. Journal of cross-cultural psychology, 3(1), 41-56.
31 Shultz, K. S., & Whitney, D. J. (2005). Measurement theory in action: Case studies and exercises: Sage.
32 Taylor, S., & Todd, P. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly, 561-570.
33 Teo, T. (2013). Influences of contextual variables on the intention to use technology in education: A latent variable modeling approach. Campus-Wide Information Systems, 30(2), 95-105.
34 Urbach, N., Smolnik, S., & Riempp, G. (2010). An empirical investigation of employee portal success. The Journal of Strategic Information Systems, 19(3), 184-206.
35 Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186-204.