Validation of an instrument for measuring the technology acceptance of a virtual learning environment

Abstract

Virtual Learning Environments (VLE) provide platforms to make online education more convenient and affordable for learners. Although VLE are currently in great demand, their acceptance needs to be assessed. In this research, an instrument that measures the technology acceptance of a VLE is validated by applying a confirmatory factor analysis on 15 items and five factors. Results show that the overall fit of the model was satisfactory and that all correlations between the latent factors were higher than 0.48. It was found that the assessment of technology acceptance is very important, because the VLE’s success depends largely on the favorable reception of professors, researchers, and educational leaders.

https://doi.org/10.15174/au.2019.1796
HTML
PDF (Español (España))
XML (Español (España))

References

Atkinson, T. M., Rosenfeld, B. D., Sit, L., Mendoza, T. R., Fruscione, M., Lavene, D., and Basch, E. (2011). Using Confirmatory Factor Analysis to Evaluate Construct Validity of the Brief Pain Inventory (BPI). Journal of Pain and Symptom Management, 41(3), 558–565. http://doi.org/10.1016/j.jpainsymman.2010.05.008

Bender, K., Donohue, S. & Heywood, J. (2005). Job satisfaction and gender segregation. Oxford Economic Papers, 57(3), 479-496. doi: 10.1093/oep/gpi015

Bennell, P., and Pearce, T. (2003). The internationalisation of higher education: exporting education to developing and transitional economies. International Journal of Educational Development, 23(2), 215–232. http://doi.org/10.1016/S0738-0593(02)00024-X

Boelen, P. A., van den Hout, M. A., and van den Bout, J. (2008). The factor structure of Posttraumatic Stress Disorder symptoms among bereaved individuals: A confirmatory factor analysis study. Journal of Anxiety Disorders, 22(8), 1377–1383. http://doi.org/10.1016/j.janxdis.2008.01.018

Bosch, T. Mathiassen, S.E., Visser, B., de Looze, M.P., and van Dieën, J.H. (2011). The effect of work pace on workload, motor variability and fatigue during simulated light assembly work. Ergonomics 54(2), 154-168. doi: 10.1080/00140139.2010.538723.

Bovaird, J.A., and Koziol, N.A. (2012). Measurement models for ordered categorical indicators in structural equation modeling. In R.H. Hoyle, D. Kaplan, Marcoulides, & S. West (Eds.), Handbook of structural equation modeling. New York, NY: The Guilford Press.

Britto, M. (2005). Frameworks for CMS Design and Evaluation. In Carmean, C. & Jafari, A. (eds.) (2005). Course Management Systems for Learning: Beyond Accidental Pedagogy. Hershey, Penn.: Idea Group.

Browne, M. W., and Cudeck, R. (1992). Alternative Ways of Assessing Model Fit. Sociological Methods & Research, 21(2), 230–258. http://doi.org/10.1177/0049124192021002005

Clark, J. M., and Paivio, A. (1991). Dual coding theory and education. Educational Psychology Review, 3(3), 149–210. http://doi.org/10.1007/BF01320076

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. http://doi.org/10.2307/249008

DeVellis, R. F. (2016). Scale development: theory and applications (Fourth edition). Los Angeles: SAGE.

Garrison, D. R. (2011). E-learning in the 21st century: A framework for research and practice. New York: Routledge.

Garrison, D. R., and Kanuka, H. (2004). Blended learning: Uncovering its transformative potential in higher education. The Internet and Higher Education, 7(2), 95–105. http://doi.org/10.1016/j.iheduc.2004.02.001

Gisbert, M. (2005). Evaluación de la calidad de la formación on-line. In TEL 2005 I Jornadas: Tendencias sobre eLearning 2005 (pp. 101–107). Madrid.

Govindasamy, T. (2001). Successful implementation of e-Learning. The Internet and Higher Education, 4(3–4), 287–299. http://doi.org/10.1016/S1096-7516(01)00071-9

Hu, L., and Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. http://doi.org/10.1080/10705519909540118

Kahai, S. S., and Cooper, R. B. (2003). Exploring the Core Concepts of Media Richness Theory: The Impact of Cue Multiplicity and Feedback Immediacy on Decision Quality. Journal of Management Information Systems, 20(1), 263–299. JOUR. Retrieved from http://www.jstor.org/stable/40398623

Kimberlin, C. L., and Winterstein, A. G. (2008). Validity and reliability of measurement instruments used in research. American Journal of Health-System Pharmacy, 65(23), 2276–2284. http://doi.org/10.2146/ajhp070364

Kismiantini, -, Montesinos Lopez, O. A., García Martínez, J. J., and Franco Pérez, E. (2014). Analyzing the Factors of Job Satisfaction in a Mexican Hospital with Binary Indicators by Confirmatory Factor Analysis, 9(8), 61–83. http://doi.org/10.5539/ijbm.v9n8p61

Kline, R.B. (2011). Principles and practice structural equation modeling. New York, NY: The Guilford Press.

MacCallum, R. C., and Browne, M. W. (1993). The use of causal indicators in covariance structure models: Some practical issues. Psychological Bulletin, 114(3), 533–541. http://doi.org/10.1037/0033-2909.114.3.533

Malhotra, N. K. (1997). Investigación de mercados. Un enfoque práctico. México: Prentice Halll.

Mayer, R. E. (2009). Multimedia learning. NY: Cambridge university press.

McArdle, J. J. (1996). Current Directions in Structural Factor Analysis. Current Directions in Psychological Science, 5(1), 11–18. http://doi.org/10.1111/1467-8721.ep10772681

Moore, J. L., Dickson-Deane, C., and Galyen, K. (2011). e-Learning, online learning, and distance learning environments: Are they the same? The Internet and Higher Education, 14(2), 129–135. http://doi.org/10.1016/j.iheduc.2010.10.001

Moore, M. G., and Kearsley, G. (2011). Distance education: A systems view of online learning. California: Wadsworth.

MPLUS (Version 6.11). [Computer Software]. Los Angeles, CA: Muthén & Muthén.

Mueller, D., and Strohmeier, S. (2011). Design characteristics of virtual learning environments: state of research. Computers & Education, 57(4), 2505–2516. http://doi.org/10.1016/j.compedu.2011.06.017

Newsom, J. T. (2012). Some clarifications and recommendations on fit indices. USP, 655, 123-133. Retrieved from http://web.pdx.edu/~newsomj/semclass/ho_fit.pdf

Li, Y., and Baser, R. (2012). Using R and WinBUGS to fit a generalized partial credit model for developing and evaluating patient-reported outcomes assessments. Statistics in Medicine, 31(18), 2010–2026. http://doi.org/10.1002/sim.4475

Liaw, S. S., Huang, H. M., and Chen, G. D. (2007). Surveying instructor and learner attitudes toward e-learning. Computers and Education, 49(4), 1066–1080. http://doi.org/10.1016/j.compedu.2006.01.001

Lin, S.-C., Persada, S. F., and Nadlifatin, R. (2014). A study of student behavior in accepting the Blackboard Learning System: A Technology Acceptance Model (TAM) approach. In Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design (CSCWD) (pp. 457–462). IEEE. http://doi.org/10.1109/CSCWD.2014.6846888

Padilla-Meléndez, A., Del Águila-Obra, A. R., y Garrido-Moreno, A. (2014). Empleo de moodle en los procesos de enseñanza-aprendizaje de dirección de empresas: nuevo perfil del estudiante en el EEES. Educación XX1, 18(1). http://doi.org/10.5944/educxx1.18.1.12314

Paechter, M., Maier, B., and Macher, D. (2010). Students’ expectations of, and experiences in e-learning: Their relation to learning achievements and course satisfaction. Computers & Education, 54(1), 222–229. http://doi.org/10.1016/j.compedu.2009.08.005

Pituch, K. A., and Lee, Y. (2006). The influence of system characteristics on e-learning use. Computers & Education, 47(2), 222–244. http://doi.org/10.1016/j.compedu.2004.10.007

Richardson, J. C., and Swan, K. (2003). Examining social presence in online courses in relation to students’ perceived learning and satisfaction. Journal of Asynchronous Learning Network, 7(1), 68–88. http://doi.org/10.1016/j.pec.2009.03.021

Salmerón-Pérez, H., Rodríguez-Fernández, S., and Gutiérrez-Braojos, C. (2010). Methodologies to Improve Communication in Virtual Learning Environments. Comunicar, 23(45), 163–171. http://doi.org/10.3916/C34-2010-03-16

Sánchez, R. A., and Hueros, A. D. (2010). Motivational Factors That Influence the Acceptance of Moodle Using TAM. Comput. Hum. Behav., 26(6), 1632–1640. http://doi.org/10.1016/j.chb.2010.06.011

Simonson, M., Smaldino, S., Albright, M., and Zvacek, S. (2000). Teaching and Learning at a Distance: Foundations of Distance Education. Upper Saddle River, NJ: Merrill.

Strauss, M. E., and Smith, G. T. (2009). Construct Validity: Advances in Theory and Methodology. Annual Review of Clinical Psychology, 5(1), 1–25. http://doi.org/10.1146/annurev.clinpsy.032408.153639

Šumak, B., Polancic, G., and Hericko, M. (2010). An Empirical Study of Virtual Learning Environment Adoption Using UTAUT. In 2010 Second International Conference on Mobile, Hybrid, and On-Line Learning (pp. 17–22). IEEE. http://doi.org/10.1109/eLmL.2010.11

Tavakol, M., and Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53–55. http://doi.org/10.5116/ijme.4dfb.8dfd

Tiene, D. (2000). Online Discussions: A Survey of Advantages and Disadvantages Compared to Face-to-face Discussions. J. Educ. Multimedia Hypermedia, 9(4), 371–384. Retrieved from http://dl.acm.org/citation.cfm?id=374674.374866

Tuckman, B. W. (2007). The effect of motivational scaffolding on procrastinators’ distance learning outcomes. Computers & Education, 49(2), 414–422. http://doi.org/10.1016/j.compedu.2005.10.002

van Raaij, E. M., and Schepers, J. J. L. (2008). The acceptance and use of a virtual learning environment in China. Computers & Education, 50(3), 838–852. http://doi.org/10.1016/j.compedu.2006.09.001

Venkatesh, V., and Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Manage. Sci., 46(2), 186–204. article. http://doi.org/10.1287/mnsc.46.2.186.11926

Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. JOUR. Retrieved from http://www.jstor.org/stable/30036540

Yu, C.Y. and Muthen, B. (2002). Evaluation of model fit indices for latent variable models with categorical and continuous outcomes (Technical report). Los Angeles, CA: University of California at Los Angeles, Graduate School of Education & Information Studies.

Zubieta García, J. y Rama Vilate, C. (2015). La Educación Superior a Distancia en México. Una propuesta para su análisis histórico. La Educación a Distancia en México: Una nueva realidad universitaria. UNAM. Retrieved from http://web.cuaed.unam.mx/