Acceptance and use of computerbased assessment in university students
DOI:
https://doi.org/10.32870/Ap.v16n1.2476Keywords:
Aceptación de la tecnología, educación superior, evaluación basada en computadora, evaluación electrónicaAbstract
The rapid development of information and communication technologies (ICT) has opened new possibilities for teaching and assessment practices in higher education, including computerbased assessment (CBA). Since the effective development of this depends on student acceptance, the present study analyzed the constructs that affect the intention to use CBA through the computer-based assessment acceptance model (CBAAM) at a private university in Mexico. The methodology was quantitative and divided into two phases: 1) application of an assessment with multiple-choice questions with automatic grading, and 2) testing of the measurement and structural model of the CBAAM instrument with 84 first-semester engineering students. The results indicate that playful perception has a direct effect on the use of CBA, while facilitating conditions, computer self-efficacy, perceived ease of use, goal expectation, social influence, and content only have indirect effects. The acceptance model studied explains approximately 47% of the variation in the intention to use. It is recommended to investigate other variables that affect the purpose of use and to apply the model in other contexts for further confirmationReferences
Al-Qdah, M. & Ababneh, I. (2017). Comparing Online and Paper Exams: Performances and Perceptions of Saudi Students. International Journal of Information and Education Technology, 7(2), 106-109. https://doi.org/10.18178/ijiet.2017.7.2.850
Bagozzi, R. P. & Yi, Y. (1988). On the evaluation of structural equationmodels. Journal of the academy of marketing science, 16(1), 74-94. https://doi.org/10.1007/BF02723327
Chau, K. Y.; Law, K. M. & Tang, Y. M. (2021). Impact of Self-Directed Learning and Educational Technology Readiness on Synchronous E-Learning. Journal of Organizational and End User Computing (JOEUC), 33(6), 1-20. https://doi.org/https://doi.org/10.4018/JOEUC.20211101.oa26
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336. http://www.researchgate.net/publication/232569511
Compeau, D. R. & Higgins, C. A. (1995). Computer self-efficacy: development of a measure and Initial test. MIS Quarterly, 19(2), 189-211. https://doi.org/10.2307/249688
Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing research, 18(1), 39-50. https://doi.org/10.2307/3151312
Garson, G. D. (2016). Partial least squares: Regression and structural equation models. Statistical Associates Publishers.
Granic, A. & Marangunic, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572-2593. https://doi.org/10.1111/bjet.12864
Hair, J. J. F.; Hult, G. T. M.; Ringle, C. & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLSSEM). Sage Publications.
Hestenes, D.; Wells, M. & Swackhamer, G. (1992). Force concept inventory. The Physics Teacher, 30(3), 141-158. https://doi.org/10.1119/1.2343497
Imtiaz, A. & Maarop, N. (2014). A Review of Technology Acceptance Studies in the Field of Education. Jurnal Teknologi, 69(2), 2180-3722. https://doi.org/doi:10.11113/jt.v69.3101
Joint Information Systems Committee (JISC). (2007). Effective practice with e-assessment: An overview of technologies, policies and practice in further and higher education. https://people.cs.vt.edu/shaffer/cs6604/Papers/eAssessment.pdf
Jordan, S. (2013). E-assessment: Past, present and future. New Directions, 9(1), 87-106. https://oro.open.ac.uk/38536/3/SEJ%20New%20Directions%202013%20d3.pdf
Kundu, A. & Bej, T. (2021). Experiencing e-assessment during covid-19: an analysis of Indian students’ perception. Higher Education Evaluation and Development, 15(2), 114-134. https://doi.org/10.1108/heed-03-2021-0032
Landry, B. J.; Griffeth, R. & Hartman, S. (2006). Measuring student perceptions of blackboard using the technology acceptance model. Decision Sciences Journal of Innovative Education, 4(1), 87-99. http://dx.doi.org/10.1111/j.1540-4609.2006.00103.x
Mo, D. Y.; Tang, Y. M.; Wu, E. Y. & Tang, V. (2022). Theoretical model of investigating determinants for a successful Electronic Assessment System (EAS) in higher education. Education and Information Technologies, 27(9), 12543-12566. https://doi.org/10.1007/s10639-022-11098-1
Moon, J. y Kim, Y. (2001). Extending the TAM for a world-wideweb context. Information and Management, 38(4), 217-230. https://doi.org/10.1016/S0378-7206(00)00061-6
Muñiz, J.; Elosua, P. & Hambleton, R. K. (2013). Directrices para la traducción y adaptación de los tests: segunda edición. Psicothema, 25(2), 151-157. https://doi.org/10.7334/psicothema2013.24
Nikou, S. A. & Economides, A. A. (2017). Mobile-based assessment: Investigating the factors that influence behavioral intention to use. Computers and Education, 109, 56-73. https://doi.org/10.1016/j.compedu.2017.02.005
Ong, C. S.; Lai, J. Y. & Wang, Y. S. (2004). Factors affecting engineers’ acceptance of asynchronous e-learning systems in high-tech companies. Information & Management, 41(6), 795-804.http://dx.doi.org/10.1016/j.im.2003.08.012
Sarstedt, M.; Ringle, C. M.; Smith, D.; Reams, R. & Hair, J. F. (2014). Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers. Journal of Family Business Strategy, 5(1), 105-115. https://doi.org/10.1007/978-3-319-05542-8_15-2
Scherer, R.; Siddiq, F. & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13-35. https://doi.org/10.1016/j.compedu.2018.09.009
Smith, P. J.; Murphy, K. L. & Mahoney, S. E. (2003). Towards identifying factors underlying readiness for online learning: an exploratory study. Distance Education, 24(1), 57-67. https://doi.org/10.1080/01587910303043
Sousa, V. D. & Rojjanasrirat, W. (2011). Translation, adaptation and validation of instruments or scales for use in cross-cultural health care research: A clear and user-friendly guideline. Journal of Evaluation in Clinical Practice, 17(2), 268-274. https://doi.org/10.1111/j.1365-2753.2010.01434.x
Tang, Y. M.; Chen, P. C.; Law, K. M. Y.; Wu, C. H.; Lau, Y. Y.; Guan, J.; He, D. & Ho, G. T. S. (2021). Comparative analysis of Student’s live online learning readiness during the coronavirus (covid-19) pandemic in the higher education sector. Computers & Education, 168. https://doi.org/10.1016/j.compedu.2021.104211
Terzis, V. & Economides, A. A. (2011). The acceptance and use of computer based assessment. Computers & Education, 56(4), 1032-1044. https://doi.org/10.1016/j.compedu.2010.11.017
Terzis, V.; Moridis, C. N. & Economides, A. A. (2012a). How student’s personality traits affect Computer Based Assessment Acceptance: Integrating BFI with CBAAM. Computers in Human Behavior,28(5), 1985-1996. https://doi.org/10.1016/j.chb.2012.05.019
Terzis, V.; Moridis, C. N. & Economides, A. A. (2012b). The effect of emotional feedback on behavioral intention to use computer based assessment. Computers & Education, 59(2), 710-721. https://doi.org/10.1016/j.compedu.2012.03.003
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. https://doi.org/10.1016/j.compedu.2012.10.018
Timmis, S.; Broadfoot, P.; Sutherland, R. & Oldfield, A. (2016). Rethinking assessment in a digital age: opportunities, challenges and risks. British Educational Research Journal, 42(3), 454-476. https://doi.org/10.1002/berj.3215
Venkatesh, V. & Davis, F. D. (1996) A Model of the Antecedents of Perceived Ease of Use: Development and Test. Decision Science, 27, 451-481. https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1540-5915.1996.tb00860.x
Venkatesh, V.; Morris, M. G.; Davis, G. B. & Davis, F. D. (2003) User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27, 425-478. https://doi.org/10.2307/30036540
Wang, Y. (2003). Assessment of learner satisfaction with asynchronous electronic learning systems. Information & Management, 41(1), 75-86. https://doi.org/10.1016/S0378-7206(03)00028-4
Wang, Y. S.; Wu, M. C. & Wang, H. Y. (2009). Investigating the determinants and age and gender differences in the acceptance of mobile learning. British journal of educational technology, 40(1), 92-118. https://doi.org/10.1111/j.1467-8535.2007.00809.x
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