Vietnamese Teachers’ Acceptance to Use E-Assessment Tools in Teaching: An Empirical Study Using PLS-SEM

Thuy Thi Tang; Thuy Nga Nguyen; Huong Thi Thu Tran

doi:10.30935/cedtech/12106

Thuy Thi Tang ¹ ^* , Thuy Nga Nguyen ¹, Huong Thi Thu Tran ¹

More Detail

CONT ED TECHNOLOGY, Volume 14, Issue 3, Article No: ep375

https://doi.org/10.30935/cedtech/12106

Submitted: 16 October 2021, Published Online: 22 May 2022

OPEN ACCESS 1522 Views 1039 Downloads

Download Full Text (PDF)

Abstract

The purpose of this study is to examine factors that influence teachers’ intentions to use technology in assessments using the technology acceptance model (TAM) as a framework. An online survey was utilized to collect data, and 360 teachers participated in the survey. This study used partial least squares-structural equation modelling (PLS-SEM) to test the hypotheses to verify the effects of variables on teachers’ intention of e-assessment use. The model consists of four constructs: computer self-efficacy (CE), perceived ease of use (PEOU), perceived usefulness (PU), and frequent use of e-assessment tools (FoUAT). The findings revealed a significant influence path from CE to PEOU, FoUAT, and behavior intention. In addition, PEOU is a critical factor that positively impacts both PU and teachers’ behavior intentions. In contrast to our expectation, frequency of use was statistically insignificant and had no impact on teachers’ intention to use (IU) e-assessment tools. The total of these four variables corresponded to 71.4% of the variance of user intention. These results confirm that TAM is an effective model to explain teachers’ technology acceptance to use e-assessment tools for their teaching.

Keywords: computer self-efficacy, e-assessment tools, PLS-SEM, technology acceptance model

References

Abdullah, F., & Ward, R. (2016). Developing a general extended technology acceptance model for e-learning (GETAMEL) by analyzing commonly used external factors. Computers in Human Behavior, 56, 238-256. https://doi.org/10.1016/j.chb.2015.11.036
Al-Emran, M., Mezhuyev, V., & Kamaludin, A. (2018). Technology acceptance model in m-learning context: A systematic review. Computers & Education, 125, 389-412. https://doi.org/10.1016/j.compedu.2018.06.008
Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2016). Determinants of perceived usefulness of e-learning systems. Computers in Human Behavior, 64, 843-858. https://doi.org/10.1016/j.chb.2016.07.065
Appiah, M., & Van Tonder, F. (2018). E-assessment in higher education: A review. International Journal of Business Management & Economic Research, 9(6),1454-1460.
Ariff, M. S. M., Yeow, S. M., Zakuan, N., Jusoh, A., & Bahari, A. Z. (2012). The effects of computer self-efficacy and technology acceptance model on behavioral intention in internet banking systems. Procedia-Social and Behavioral Sciences, 57, 448-452. https://doi.org/10.1016/j.sbspro.2012.09.1210
Baydas, O., & Goktas, Y. (2017). A model for preservice teachers’ intentions to use ICT in future lessons. Interactive Learning Environments, 25(7), 930-945. https://doi.org/10.1080/10494820.2016.1232277
Bhatt, S., & Shiva, A. (2020). Empirical examination of the adoption of Zoom software during COVID-19 pandemic: Zoom TAM. Journal of Content, Community & Communication, 12(6), 70-88. https://doi.org/10.31620/JCCC.06.%2020/08
Chang, C. T., Hajiyev, J., & Su, C. R. (2017). Examining the students’ behavioral intention to use e-learning in Azerbaijan? The general extended technology acceptance model for e-learning approach. Computers & Education, 111, 128-143. https://doi.org/10.1016/j.compedu.2017.04.010
Cheng, K. H., & Tsai, C. C. (2011). An investigation of Taiwan University students’ perceptions of online academic help-seeking, and their web-based learning self-efficacy. The Internet and Higher Education, 14(3), 150-157. https://doi.org/10.1016/j.iheduc.2011.04.002
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336.
Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Academic Press. https://doi.org/10.4324/9780203771587
Conole, G., & Warburton, B. (2005). A review of computer-assisted assessment. ALT-J, Research in Learning Technology, 13(1), 17-31. https://doi.org/10.1080/0968776042000339772
Davis, F. D. (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
Davis, F. D. (2011). Foreword in technology acceptance in education: Research and issues. Sense Publishers.
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. https://doi.org/10.1287/mnsc.35.8.982
Davis, M. M., Spohrer, J. C., & Maglio, P. P. (2011). Guest editorial: How technology is changing the design and delivery of services. Operations Management Research, 4(1-2), 1-5. https://doi.org/10.1007/s12063-011-0046-6
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 Publications.
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 Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). SAGE. https://doi.org/10.1007/978-3-030-80519-7
Hair Jr, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling. SAGE. https://doi.org/10.15358/9783800653614
Hong, X., Zhang, M., & Liu, Q. (2021). Preschool teachers’ technology acceptance during the COVID-19: An adapted technology acceptance model. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.691492
Huang, F., Teo, T., & Scherer, R. (2020). Investigating the antecedents of university students’ perceived ease of using the Internet for learning. Interactive Learning Environments, 1-17. https://doi.org/10.1080/10494820.2019.1710540
Ibrahim, R., Leng, N. S., Yusoff, R. C. M., Samy, G. N., Masrom, S., & Rizman, Z. I. (2017). E-learning acceptance based on technology acceptance model (TAM). Journal of Fundamental and Applied Sciences, 9(4S), 871-889. https://doi.org/10.4314/jfas.v9i4s.50
Kanwal, F., & Rehman, M. (2017). Factors affecting e-learning adoption in developing countries-empirical evidence from Pakistan’s higher education sector. IEEE Access, 5, 10968-10978. https://doi.org/10.1109/ACCESS.2021.2714379
Kundu, A., & Bej, T. (2020). 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
Lew, S. L., Lau, S. H., & Leow, M. C. (2019). Usability factors predicting continuance of intention to use cloud e-learning application. Heliyon, 5(6), e01788. https://doi.org/10.1016/j.heliyon.2019.e01788
Mailizar, M., Almanthari, A., & Maulina, S. (2021). Examining teachers’ behavioral intention to use e-learning in teaching of mathematics: An extended TAM model. Contemporary Educational Technology, 13(2), ep298. https://doi.org/10.30935/cedtech/9709
Marangunic, N., & Granic, A. (2015). Technology acceptance model: A literature review from 1986 to 2013. Universal Access in the Information Society, 14, 81-95. https://doi.org /10.1007/s10209-014-0348-1
MOET. (2021, July). Statistics. Ministry of Education and Training. https://moet.gov.vn/thong-ke/Pages/thong-ke.aspx
Mukminin, A., Habibi, A., Muhaimin, M., & Prasojo, L. D. (2020). Exploring the drivers predicting behavioral intention to use m-learning management system: Partial least square structural equation model. IEEE Access, 8, 181356-181365. https://doi.org/10.1109/ACCESS.2020.3028474
Ngabiyanto, Nurkhin, A., Mukhibad, H., & Harsono. (2021). E-learning evaluation using general extended technology acceptance model approach at schools in COVID-19 pandemic. European Journal of Educational Research, 10(3), 1171-1180. https://doi.org/10.1088/1742-6596/1783/1/012123
Purnomo, S. H., & Lee, Y. H. (2013). E-learning adoption in the banking workplace in Indonesia: An empirical study. Information Development, 29(2), 138-153. https://doi.org/10.1177/0266666912448258
Rafique, H., Almagrabi, A. O., Shamim, A., Anwar, F., & Bashir, A. K. (2020). Investigating the acceptance of mobile library applications with an extended technology acceptance model (TAM). Computers & Education, 145, 103732. https://doi.org/10.1016/j.compedu.2019.103732
Rizun, M., & Strzelecki, A. (2020). Students’ acceptance of the COVID-19 impact on shifting higher education to distance learning in Poland. International Journal of Environmental Research and Public Health, 17(18), 6468. https://doi.org/10.3390/ijerph17186468
Sanchez-Prieto, J. C., Olmos-Miguelanez, S., & Garcia-Penalvo, F. J. (2016). Informal tools in formal contexts: Development of a model to assess the acceptance of mobile technologies among teachers. Computers in Human Behavior, 55, 519-528. https://doi.org/10.1016/j.chb.2015.07.002
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
Stockless, A. (2018). Acceptance of learning management system: The case of secondary school teachers. Education and Information Technologies, 23(3), 1101-1121. https://doi.org/10.1007/s10639-017-9654-6
Teo, T., Ruangrit, N., Khlaisang, J., Thammetar, T., & Sunphakitjumnong, K. (2014). Exploring e-learning acceptance among university students in Thailand: A national survey. Journal of Educational Computing Research, 50(4). https://doi.org/10.2190/EC.50.4.c
Teo, T., Ursavas, O. F., & Bahcekapili, E. (2012). An assessment of pre-service teachers’ technology acceptance in Turkey: A structural equation modeling approach. Asia-Pacific Education Researcher, 21(1), 191-202.
Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481. https://doi.org/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, 425-478. https://doi.org/10.2307/30036540
Weerasinghe, S., & Hindagolla, M. (2017). Technology acceptance model in the domains of LIS and education: A review of selected literature. Library Philosophy & Practice, 1582, 1-26.
Wirtz, B. W., & Göttel, V. (2016). Technology acceptance in social media: Review, synthesis and directions for future empirical research. Journal of Electronic Commerce Research, 17(2), 97-115.
Yalcin, M. E., & Kutlu, B. (2019). Examination of students’ acceptance of and intention to use learning management systems using extended TAM. British Journal of Educational Technology, 50(5), 2414-2432. https://doi.org/10.1111/bjet.12798
Yuen, A. H., & Ma, W. W. (2008). Exploring teacher acceptance of e‐learning technology. Asia‐Pacific Journal of Teacher Education, 36(3), 229-243. https://doi.org/10.1080/13598660802232779
Zainab, B., Bhatti, M. A., & Alshagawi, M. (2017). Factors affecting e-training adoption: An examination of perceived cost, computer self-efficacy and the technology acceptance model. Behavior & Information Technology, 36(12), 1261-1273. https://doi.org/10.1080/0144929X.2017.1380703

Citation

Tang, T. T., Nguyen, T. N., & Tran, H. T. T. (2022). Vietnamese Teachers’ Acceptance to Use E-Assessment Tools in Teaching: An Empirical Study Using PLS-SEM. Contemporary Educational Technology, 14(3), ep375. https://doi.org/10.30935/cedtech/12106

Tang, T. T., Nguyen, T. N., and Tran, H. T. T. (2022). Vietnamese Teachers’ Acceptance to Use E-Assessment Tools in Teaching: An Empirical Study Using PLS-SEM. Contemporary Educational Technology, 14(3), ep375. https://doi.org/10.30935/cedtech/12106

Tang TT, Nguyen TN, Tran HTT. Vietnamese Teachers’ Acceptance to Use E-Assessment Tools in Teaching: An Empirical Study Using PLS-SEM. CONT ED TECHNOLOGY. 2022;14(3), ep375. https://doi.org/10.30935/cedtech/12106

Tang, Thuy Thi, Thuy Nga Nguyen, and Huong Thi Thu Tran. "Vietnamese Teachers’ Acceptance to Use E-Assessment Tools in Teaching: An Empirical Study Using PLS-SEM". Contemporary Educational Technology 2022 14 no. 3 (2022): ep375. https://doi.org/10.30935/cedtech/12106

Tang, Thuy Thi et al. "Vietnamese Teachers’ Acceptance to Use E-Assessment Tools in Teaching: An Empirical Study Using PLS-SEM". Contemporary Educational Technology, vol. 14, no. 3, 2022, ep375. https://doi.org/10.30935/cedtech/12106

Tang TT, Nguyen TN, Tran HTT. Vietnamese Teachers’ Acceptance to Use E-Assessment Tools in Teaching: An Empirical Study Using PLS-SEM. CONT ED TECHNOLOGY. 2022;14(3):ep375. https://doi.org/10.30935/cedtech/12106