Validation of Non-Linear Relationships-Based UTAUT Model on Higher Distance Education Students’ Acceptance of WhatsApp for Supporting Learning
References:
[1]
Smith, R. (2015). The role of
social media in higher education marketing. Retrieved May 12, 2015 from http://www.bostoninteractive.com/blog/industries/socialmedia-higher-education-marketing.
[2]
Fattah, S. F. E. S. A. (2015). The
effectiveness of using WhatsApp messenger as one of mobile learning techniques
to develop students' writing skills. Journal of Education and Practice, 6(32),
115-127.
[3]
Vrocharidou, A., & Efthymiou, I.
(2012). Computer mediated communication for social and academic purposes: Profiles
of use and university students' gratifications. Computers & Education,
58(1), 609–616.
[4]
Ogara, S., Koh, C., & Prybutok,
V. (2014). Investigating factors affecting social presence and user
satisfaction with mobile instant messaging. Computers in Human Behavior,
36(2014), 453–459.
[5]
Cifuentes, O., & Lents, N.
(2010). Increasing student-teacher interactions at an urban commuter campus
through instant messaging and online office hours. Electronic Journal of
Science Education, 14(1), 1–13.
[6]
Venkatesh V., Morris M., Davis G.
& Davis F. (2003). User acceptance of information technology: Toward a
unified view. MIS Quarterly. 27(3), 425-478. DOI: 10.2307/30036540.
[7]
Bervell, B. & Umar, I. N.
(2017). Validation of UTAUT model: re-considering non-linear relationships of exogeneous
variables in higher education technology acceptance research. EURASIA Journal
of Mathematics Science and Technology Education, 13(10), 6472-6490. DOI:
10.12973/eurasia.2017.01078a.
[8]
Davis, F. D. (1986). Technology
acceptance models for empirically testing new end-user information systems:
theory and results. Cambridge: MIT Sloan School of Management.
[9]
Bandura, A. (1982). Self-efficacy
mechanism in human agency. American Psychologist, 37, 122-147.
[10]
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.
[11]
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), 982-1003.
[12]
Venkatesh, V. & Davis, F. D.
(2000). A Theoretical Extension of the Technology Acceptance Model: Four
Longitudinal Field Studies. Management Science, 46(2), 186-204. http://dx.doi.org/10.1287/mnsc.46.2.186.11926.
[13]
Nikou, S. A., and Economides, A. A.
(2017). Mobile-based assessment: investigating the factors that influence
behavioral intention to use. Comput. Educ.109, 56–73. DOI: 10.1016/j.compedu.2017.02.005.
[14]
Bandura, A. (1986). Social
foundations of thought and action: a social cognitive theory: Prentice Hall,
Englewood Cliffs, NJ.
[15]
Krejcie, R. V., & Morgan, D. W.
(1970). Determining sample size for research activities. Educational and
Psychological Measurement, 30, 607-610.
[16]
Evans, N. D. (2013). Predicting user
acceptance of electronic learning at the University of Zululand. Unpublished
Thesis. Department of Information Studies, University of Zululand, South
Africa.
[17]
Chao C-M (2019) Factors determining
the behavioral intention to use mobile learning: an application and extension
of the UTAUT model. Frontiers in Psychology, 10(1652), 1-14. DOI:
10.3389/fpsyg.2019.01652.
[18]
Ringle, C. M., Wende, S., and
Becker, J.-M. (2015). "SmartPLS 3." Boenningstedt: SmartPLS GmbH, http://www.smartpls.com.
[19]
Hair, J. F., Hult, G. T. M., Ringle,
C. M., & Sarstedt, M. (2014). A primer on partial least squares structural
equation modeling. 1st Edition. Thousand Oaks: Sage.
[20]
Henseler, J., Ringle, C. M., &
Sarstedt, M. (2015). A new criterion for assessing discriminant validity in
variance-based structural equation modeling. J. of the Acad. Mark. Sci. 43,
115–135. DOI: 10.1007/s11747-014-0403-8.
[21]
Hair, J. F., Hult, G. T. M., Ringle,
C. M., & Sarstedt, M. (2017). A primer on partial least squares structural
equation modeling. 2nd Edition. Thousand Oaks: Sage.
[22]
Kock, N. (2015). Common method bias
in PLS-SEM: A full collinearity assessment approach. International Journal of
e-Collaboration, 11(4), 1-10.