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Adopting Computer-Based Assessments: The Role of Perceived Value in Classroom Technology Acceptance

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Abstract (2. Language): 
Computer based assessments (CBA) have increasingly become a popular tool for educators to test students’ knowledge of course material because of the many advantages it confers. However, research on its perceived value and satisfaction among students has found mixed results, with some test takers’ attitudes ranging from enthusiasm at being able to complete exams and retrieve test results whenever they want, to others actively disliking its use. As yet, the reasons for the same remain unclear. What is clear is that unmotivated or discontented students’ negative evaluations of CBA could overtime lead to a discontinuance of its usage in classrooms. Understanding the drivers of students’ continued usage of CBA is therefore key to the future use of this technological innovation and the goal of this research. To this end, the study utilized the Unified Theory of Acceptance and Use of Technology (UTAUT)—a model specifically built to understand the adoption of software technology—to the classroom adoption of technology context. Using quantitative survey data from 111 students who were assessed using CBAs, the study examined the role of the UTAUT constructs of performance expectancy, effort expectancy, social influence, and facilitating conditions in predicting students’ continuance intention for CBA. Findings found a direct effect of UTAUT’s core constructs of performance expectancy, social influence, and facilitating conditions on continuance CBA intention. Interestingly, students’ perceived value of CBA partially mediated the effect of these constructs on continuance intention. The results of the study, therefore, point to a single, new, global construct—perceived value of CBA—that predicts whether students prefer classroom technology.
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REFERENCES

References: 

Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human
decision processes, 50, 179-211.
Akdemir, O., & Oguz, A. (2008). Computer-based testing: An alternative for the assessment
of Turkish undergraduate students. Computers & Education, 51, 1198-1204.
American Psychological Association. Committee on Professional Standards, American
Psychological Association. Board of Scientific Affairs.Committee on Psychological
Tests, & Assessment.(1986). Guidelines for computer-based tests and
interpretations. The Association.and Achievement Motivation, W.H. Freeman, San
Francisco, CA, 1983, pp. 75–146.
Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986.
Barkley, A. P. (2002). An analysis of online examinations in college courses.Journal of
Agricultural and Applied Economics, 34, 445-458.
Bouhnik, D., & Marcus, T. (2006). Interaction in distance‐learning courses.Journal of the
American Society for Information Science and Technology,57(3), 299-305.
Bransford, J. D., Brown, A. L., & Cocking, R. R. (1999). How people learn: Brain, mind,
experience, and school. National Academy Press.
Bugbee, A. C. (1996). The equivalence of paper-and-pencil and computer-based
testing. Journal of research on computing in education, 28, 282-299.
Bugbee, A.C. (1992). Examination on demand: Findings in ten years of testing by computer
1982-1991. Edina, MN: TRO Learning
Bugbee, A.C., &Bernt, F.M. (1990). Testing by computer: Findings in six years of use 1982-
1988. Journal of Research on Computing in Education, 23(1), 87-100.
Bunderson, C.V., Inouye, D.K., & Olsen, J.B. (1989). The four generations of computerized
educational measurement. In R.L. Linn (Ed.), Educational measurement (3rd ed.),
(pp. 367-407 New York: American Council on Education--Macmillan.
Castro, I., &Roldán, J. L. (2013). A mediation model between dimensions of social
capital. International Business Review, 22(6), 1034-1050.
C. Carlsson, J. Carlsson, K. Hyvo¨nen, J. Puhakainen, P. Walden, Adoption of mobile
devices/services—searching for answers with the UTAUT, in: Proceedings of the
39th Hawaii International Conference on System Sciences, 2006
Chiu, C. M., Hsu, M. H., Sun, S. Y., Lin, T. C., & Sun, P. C. (2005). Usability, quality, value
and e-learning continuance decisions. Computers & Education, 4, 399–416.
Online Journal of Communication and Media Technologies
Volume: 7 – Issue: 4 October - 2017
© Online Journal of Communication and Media Technologies 20
Chiu, C. M., Sun, S. Y., Sun, P. C., &Ju, T. L. (2007).An empirical analysis of the
antecedents of web-based learning continuance. Computers & Education, 49, 1224–
1245
Chiu, C. M., & Wang, E. T. (2008). Understanding Web-based learning continuance
intention: The role of subjective task value. Information & Management, 45, 194-
201.
Chua, S. L., Chen, D. T., & Wong, A. F. (1999). Computer anxiety and its correlates: a metaanalysis.
Computers in human behavior, 15(5), 609-623.
Clariana, R., & Wallace, P. (2002). Paper–based versus computer–based assessment: key
factors associated with the test mode effect. British Journal of Educational
Technology, 33, 593-602.
Cody-Allen, E., & Kishore, R. (2006, April). An extension of the UTAUT model with equality,
trust, and satisfaction constructs. In Proceedings of the 2006 ACM SIGMIS
CPR conference on computer personnel research: Forty four years of computer
personnel research: achievements, challenges & the future(pp. 82-89). ACM.
Croft, A. C., Danson, M., Dawson, B. R., & Ward, J. P. (2001). Experiences of using
computer assisted assessment in engineering mathematics. Computers &
Education, 37, 53-66.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of
information technology. MIS quarterly, 13, 319-340.
DeAngelis, S. (1999). Equivalency of computer-based and paper-and-pencil testing. Journal
of Allied Health, 29, 161-164.
Dickhauser, O., &Stiensmeier-Pelster, J. (2003). Gender differences in the choice of
computer courses: Applying the expectancy-value model. Social Psychology of
Education, 6, 173–189.
Eccles, J.S, Adler, T.F., Futterman, R., Goff, S.B., Kaczala, C.M., Meece, J.L., Midgley,
C.Expectancies, values, and academic behaviors, in: J.T. Spence (Ed.), Achievement
Eccles, J. S., &Wigfield, A. (1995). In the mind of the actor: The structure of adolescents'
achievement task values and expectancy-related beliefs.
Fulcher, G. (2000). The ‘communicative’legacy in language testing. System, 28, 483-497.
Harmon, O. R., &Lambrinos, J. (2008). Are online exams an invitation to cheat?. The Journal
of Economic Education, 39, 116-125.
Homer, P. M., &Kahle, L. R. (1988). A structural equation test of the value-attitude-behavior
Online Journal of Communication and Media Technologies
Volume: 7 – Issue: 4 October - 2017
© Online Journal of Communication and Media Technologies 21
hierarchy. Journal of Personality and social Psychology,54(4), 638.
Howell, S. L., Sorensen, D., & Tippets, H. R. (2009).The new (and old) news about cheating
for distance educators. Online Journal of Distance Learning Administration, 12
Jones, S., Johnson‐Yale, C., Millermaier, S., & Pérez, F. S. (2009). US college students’
Internet use: Race, gender and digital divides. Journal of Computer‐Mediated
Communication, 14, 244-264.
Kennedy, K., Nowak, S., Raghuraman, R., Thomas, J., & Davis, S. F. (2000). Academic
dishonesty and distance learning: Student and faculty views. College Student
Journal. 34, 309-314
Krsak, A. (2007). Curbing academic dishonesty in online courses. In TCC-Teaching Colleges
and Community Worldwide Online Conference , 1, 159-170.
Liaw, S. S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and
effectiveness of e-learning: A case study of the Blackboard system. Computers &
Education, 51(2), 864-873.
Limayem, M., & Cheung, C. M. K. (2011). Predicting the continued use of Internet based
learning technologies: the role of habit. Journal of Behaviour and Information
Technology, 30(1), 91–99
Mason, B. J., Patry, M., &Berstein, D. J. (2001). An examination of the equivalence between
non-adaptive computer-based and traditional testing.Journal of Educational
Computing Research, 24, 29-40.
Mazzeo, J., & Harvey, A.L. (1988).The equivalence of scores from automated and
conventional educational and psychological tests (College Board Report No. 88-8).
New York: College Entrance Examination Board.
McDonald, A. S. (2002). The impact of individual differences on the equivalence of
computer-based and paper-and-pencil educational assessments. Computers &
Education, 39(3), 299-312.
Mills, J. D. (2002). Using computer simulation methods to teach statistics: A review of the
literature. Journal of Statistics Education, 10, 1-20.
Moran, M., Hawkes, M., & El Gayar, O. (2010). 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, 79-101.
Online Journal of Communication and Media Technologies
Volume: 7 – Issue: 4 October - 2017
© Online Journal of Communication and Media Technologies 22
Ogilvie, R. W., Trusk, T. C., & Blue, A. V. (1999).Students’ attitudes towards computer
testing in a basic science course. Medical education, 33(11), 828-831.
Olsen, B., &Krendl, K.A. (1990). At-risk students and microcomputers: What do we know
and how do we know it? Journal of Educational Technology Systems, 19(2), 165-
175.
Ramos, M. (2003).Auditors’ responsibility for fraud detection. Journal of Accountancy,
195(1), 28-35.
Real, J. C., Roldán, J. L., & Leal, A. (2014). From entrepreneurial orientation and learning
orientation to business performance: analysing the mediating role of organizational
learning and the moderating effects of organizational size. British Journal of
Management, 25(2), 186-208.
Roca, J. C., Chiu, C. M., & Martinez, F. J. (2006). Understanding e-learning continuance
intention: an extension of the technology acceptance model. International Journal of
Human-Computer Studies, 64(8), 683–696.
Sambell, K., Sambell, A., & Sexton, G. (1999). Student perceptions of the learning benefits
of computer-assisted assessment: A case study in electronic engineering. S. Brown,
P. Race, & J. Bull, Computer-assisted assessment in higher education, 179-191.
Schaeffer, G. A., Reese, C. M., Steffen, M., McKinley, R. L., & Mills, C. N. (1993).Field test
of a computer‐based gre general test. ETS Research Report Series, 1993, 1-47.
Singleton, C., Horne, J., & Thomas, K. (1999).Computerised baseline assessment of
literacy. Journal of Research in Reading, 22(1), 67-80.
Stuber-McEwen, D., Wiseley, P., and Hoggatt, S. (2009). "Point, click, and cheat: Frequency
and type of academic dishonesty in the virtual classroom." Online Journal of
Distance Learning Administration 12, 1-10.
Terzis, V., & Economides, A. A. (2011). The acceptance and use of computer based
assessment. Computers & Education, 56, 1032-1044.
Terzis, V., Moridis, C. N., & Economides, A. A. (2013). Continuance acceptance of
computer based assessment through the integration of user's expectations and
perceptions. Computers & Education, 62, 50-61.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of
information technology: Toward a unified view. MIS quarterly, 425-478.
Vishwanath, A;Goldhaber, G. M. (2003). An examination of the factors contributing to
Online Journal of Communication and Media Technologies
Volume: 7 – Issue: 4 October - 2017
© Online Journal of Communication and Media Technologies 23
adoption decisions among late-diffused technology products.New media &
society, 5, 547-572.
Wang, H. I., & Yang, H. L. (2005).The role of personality traits in UTAUT model under
online stocking. Contemporary Management Research, 1(1), 69-82.
Watson, G. R., &Sottile, J. (2010). Cheating in the digital age: Do students cheat more in
online courses?.
Wellner, K. (2015). Contribution and Implications.In User Innovators in the Silver
Market (pp. 170-178).Springer Fachmedien Wiesbaden.
Wise, S. L., &Plake, B. S. (1989).Research on the effects of administering tests via
computers. Educational measurement: Issues and practice, 8, 5-10.
Yang, Y., & Cornelius, L. F. (2004). Students' Perceptions towards the Quality of Online
Education: A Qualitative Approach. Association for Educational Communications
and Technology.

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