An Evaluation of the Model of Acceptance of E-Assessment Among Academics in Saudi Universities
Education Journal
Volume 7, Issue 2, March 2018, Pages: 23-36
Received: May 22, 2018; Accepted: Jun. 6, 2018; Published: Jun. 29, 2018
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Nuha Alruwais, Electronics and Computer Science, University of Southampton, Southampton, UK
Gary Wills, Electronics and Computer Science, University of Southampton, Southampton, UK
Mike Wald, Electronics and Computer Science, University of Southampton, Southampton, UK
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E-assessment was introduced to overcome some of the limitations in paper-test assessment methods. Educational institutions have become more interested in adopting E-assessment, especially in classes with large numbers of students. This paper investigates the factors that influence Saudi academics to accept E-assessment, in order to give a clear picture for institutions before adopting E-assessment. A Model of Acceptance of E-assessment (MAE) has been developed [1] built from the existing theories and models of acceptance and use of information and communication technology (ICT) and other related studies. In previous stage of this study interviews with experts in Saudi Universities were conducted to refine the factors in MAE [2], and a questionnaire was then distributed to confirm the interview results. In the next stage of the study, another questionnaire was distributed to all academics in Saudi universities to evaluate the factors and find the most affecting factors on academics’ intention and to examine the relationships between these factors using Structural Equation Modelling (SEM) analysis. Finally, the SEM results were explored by focus group discussions, among ten Saudi academics. The results show that Attitude was the most affecting factor that had an impact on Saudi academics’ behavioural intention to accept E-assessment, followed by Subjective Norm, while Perceived Behavioural Control had no effect on their intention to accept E-assessment. Compatibility was found to have the most impact on Attitude, followed by Perceived Ease of Use and Perceived Usefulness, while Awareness of E-assessment had no effect on Attitude. Superior Influence had a strong influence on Subjective Norm, and only Self-Efficacy had an impact on Perceived Behavioural Control. Age was also examined as a moderating factor that might affect the relationships between Attitude, Subjective Norm and Perceived Behavioural Control and Behavioural Intention. The findings revealed that age had a positive and direct effect on the relationship between Attitude and Behavioural Intention, whereas it was found to have a low influence, on the relationship of Subjective Norm and Behavioural Intention.
E-Assessment, E-Exam, Electronic Exam, Online Exam, Online Assessment
To cite this article
Nuha Alruwais, Gary Wills, Mike Wald, An Evaluation of the Model of Acceptance of E-Assessment Among Academics in Saudi Universities, Education Journal. Vol. 7, No. 2, 2018, pp. 23-36. doi: 10.11648/
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
N. Alruwais, G. Wills, and M. Wald, “Identifying Factors That Affect the Acceptance and Use of E-Assessment By Academics in Saudi Universities,” IJAEDU- Int. E-Journal Adv. Educ., vol. 2, no. 4, pp. 132–140, 2016.
N. Alruwais, G. Wills, and M. Wald, “Validating Factors That Impact the Acceptance and Use of e-Assessment among Academics in Saudi Universities,” IJAEDU- Int. E-Journal Adv. Educ., vol. 2, no. 4, pp. 132–140, 2016.
J. Ridgway, S. McCusker, and D. Pead, “Literature review of e-assessment.,” Bristol, 2004.
L. Gilbert and V. Gale, Principles of E-Learning Systems Engineering. Oxford: Chandos, 2007.
A. Way, “The Use of E-assessments in The Nigerian Higher Education System,” Turkish Online J. Distance Educ., vol. 13, no. 1, pp. 140–152, 2012.
G. Taylor, Integrating Quantitative and Qualitative Methods in Research, 2nd Revise. University Press of America, 2005.
M. Fishbein and I. Ajzen, Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Reading, Mass, Addison-Wesley Pub. Co, 1975.
F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Q., vol. 13, no. 3, pp. 319–340, 1989.
I. Ajzen, “The theory of planned behavior,” Orgnizational Behav. Hum. Decis. Process., vol. 50, no. 2, pp. 179–211, 1991.
S. Taylor and P. a. Todd, “Understanding information technology usage: A test of competing models,” Inf. Syst. Res., vol. 6, no. 2, pp. 144–176, 1995.
G. Moore and I. Benbasat, “Development of an instrument to measure the perceptions of adopting an information technology innovation,” Inf. Syst. Res., vol. 2, no. 3, pp. 192–222, 1991.
V. Venkatesh and G. M. Morris, “Why don’t men ever stop to ask for direction? Gender, social influence and their role in technology acceptance and usage behaviour,” MIS Q., vol. 24, no. 1, pp. 115–139, 2000.
E. Huang and M. H. Chuang, “Extending the theory of planned behaviour as a model to explain post-merger employee behaviour of IS use,” Comput. Human Behav., vol. 23, no. 1, pp. 240–257, 2007.
R. Likert, “A technique for the measurement of attitudes,” Arch. Psychol., vol. 22, p. 140, 1932.
J. F. Hair, R. E. Anderson, B. J. Babin, and W. C. Black, Multivariate Data Analysis, Seventh Ed. Prentice Hall Higher Education., 2010.
R. B. Kline, Principles and Practice of Structural Equation Modeling. Guilford publications, 2015.
U. Sekaran, Research methods for business: A skill building approach, 4 Edition. John Wiley & Sons, Inc, 2003.
J. Pallant, Spss Survival Manual: A step by step guide to data analysis using SPSS., Forth Edit. Allen & Unwin., 2011.
M. L. Mitchell and J. M. Jolley, Research Design Explained. Cengage Learning, 2012.
A. M. Farrell, “Insufficient discriminant validity: A comment on Bove, Pervan, Beatty, and Shiu (2009),” J. Bus. Res., vol. 63, no. 3, pp. 324–327, 2010.
S. P. Chien, H. K. Wu, and Y. S. Hsu, “An investigation of teachers’ beliefs and their use of technology-based assessments,” Comput. Human Behav., vol. 31, pp. 198–210, 2014.
P. M. Bentler, Covariance structure models for maximal reliability of unit-weighted composites. Handbook of latent variable and related models, 2007.
B. M. Byrne, Structural equation modeling with Mplus: Basic concepts, applications, and programming. Routledge, 2013.
P. Gill, K. Stewart, E. Treasure, and B. Chadwick, “Methods of data collection in qualitative research: interviews and focus groups.,” Br. Dent. J., vol. 204, no. 6, pp. 291–295, 2008.
D. L. Morgan, The focus group guide book, Vol. 1. Sage publications, 1997.
M. Bloor, J. Frankland, M. Thomas, and K. Robson, Focus groups in social research. Sage publication Ltd, 2001.
R. K. Merton and P. L. Kendall, “The Focused Interview,” Am. J. Sociol., vol. 51, no. 6, pp. 541–557, 1946.
D. W. Stewart and P. N. Shamdasani, Focus groups. Theory and practice, Vol. 20. Sage publications, 2014.
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