Factors Affecting Lecturers’ Intention to use Simulation Technology Applications in Teaching Activities at the Tertiary Level
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https://doi.org/10.52296/vje.2023.319-
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This paper aims to examine the impact of different factors on lecturers’ behavior related to the intention to use simulation technology applications in teaching activities in the context of the 4.0 industrial revolution in all fields around the world. The research employs a mixed-method approach, comprising qualitative in-depth interviews and group discussions, followed by a quantitative survey using SPSS-V.22 to assess the impact of lecturers’ intention-related factors on use of simulation applications in teaching activities. Based on the analysis results, the study identifies the factors that promote the intention to use simulation applications in teaching activities. The practical implications of this research are significant, as the findings provide valuable insights to curriculum developers, educators, administrators, policymakers, and developers of simulations in school instruction. Enhancing the intention to use simulation applications can contribute to improving the quality of teaching and training. This study adds to the current body of knowledge by offering a new perspective on the use of simulation applications in teaching activities.
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Ali, A., Almari, H., Isaac, O., & Mohammed, F. (2019). Investigating the key factors influencing the use of online social networks in public sector context in the UAE. International Journal of Innovation, 7(3), 392-411. https://doi.org/10.5585/iji.v7i3.347
Bower, M., DeWitt, D., & Lai, J. W. M. (2020). Reasons associated with preservice teachers’ intention to use immersive virtual reality in education. British Journal of Educational Technology, 51(6), 2215-2233. https://doi.org/10.1111/bjet.13009
Chigona, A., & Chigona, W. (2010). An investigation of factors affecting the use of ICT for teaching in the Western cape schools. 18th European Conference on Information Systems, ECIS. https://aisel.aisnet.org/ecis2010/61
Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral Dissertation, Massachusetts Institute of Technology.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Information Systems Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
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
Deng, X., Zhou, G., Xiao, B., Zhao, Z., He, Y., & Chen, C. (2018). Effectiveness evaluation of digital virtual simulation application in teaching of gross anatomy. Annals of Anatomy - Anatomischer Anzeiger, 218, 276-282. https://doi.org/10.1016/j.aanat.2018.02.014
Ertmer, P. A., Ottenbreit-Leftwich, A., Sadık, O., Şendurur, E., & Şendurur, P. (2012). Teacher beliefs and technology integration practices: A critical relationship. Computers & Education, 59(2), 423-435. https://doi.org/10.1016/j.compedu.2012.02.001
Gould, H., & Tobochnick, J. (1996). An introduction to computer simulation methods. Applications to physical systems (2nd Edition). New York: Addison-Wesley Publishing Company.
Granić, A., & Marangunić, 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. F. (2010). Multivariate data analysis : a global perspective. In Pearson eBooks. https://ci.nii.ac.jp/ncid/BB03463866
Hill, R. J., Fishbein, M., & Ajzen, I. (1977). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Contemporary Sociology, 6(2), 244. https://doi.org/10.2307/2065853
Hu, S., Laxman, K., & Lee, K. (2020). Exploring factors affecting academics’ adoption of emerging mobile technologies-an extended UTAUT perspective. Education and Information Technologies, 25, 4615-4635. https://doi.org/10.1007/s10639-020-10171-x
Joo, Y. J., Park, S., & Lim, E. (2018). Factors influencing preservice teachers’ intention to use technology: TPACK, teacher self-efficacy, and technology acceptance model. Educational Technology & Society, 21(3), 48-59. https://203.255.161.86/handle/2015.oak/245215
Le, T. H. L. (2022). Ứng dụng mô hình “Chấp nhận công nghệ” nghiên cứu ý định hành vi học trực tuyến của sinh viên Trường Đại học Đồng Nai trong bối cảnh đại dịch Covid-19 [Applying the “Technology Acceptance” model to study the online learning behavior intention of Dong Nai University students in the context of the Covid-19 pandemic]. Vietnam Journal of Education, 22(3), 36-41.
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
Mugo, D. G., Njagi, K., Chemwei, B., & Motanya, J. O. (2017). The Technology Acceptance Model (TAM) and its Application to the Utilization of Mobile Learning Technologies. British Journal of Mathematics & Computer Science, 20(4), 1-8. https://doi.org/10.9734/bjmcs/2017/29015
Nanayakkara, C., & Whiddett, R. J. (2005). A model of user acceptance of E-learning technologies: A case study of a polytechnic in New Zealand. ISTA, 180-190. https://cs.emis.de/LNI/Proceedings/Proceedings63/GI-Proceedings.63-13.pdf
Sarı, U., Duygu, E., Şen, Ö. F., & Kırındı, T. (2020). The effects of STEM education on scientific process skills and STEM awareness in simulation based inquiry learning environment. Journal of Turkish Science Education, 17(3), 387-405. https://doi.org/10.36681/tused.2020.34
Silva, P. (2015). Davis’ Technology Acceptance Model (TAM) (1989). In Advances in knowledge acquisition, transfer and management book series (pp. 205-219). https://doi.org/10.4018/978-1-4666-8156-9.ch013
Tang, K., Hsiao, C., Tu, Y., Hwang, G., & Wang, Y. (2021). Factors influencing university teachers’ use of a mobile technology-enhanced teaching (MTT) platform. Educational Technology Research and Development, 69(5), 2705-2728. https://doi.org/10.1007/s11423-021-10032-5
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. https://doi.org/10.1287/isre.11.4.342.11872
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., Morris, M., Davis, G. B., & Davis, F. D. (2003). User acceptance of information Technology: toward a unified view. Management Information Systems Quarterly, 27(3), 425. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer Acceptance and use of Information technology: Extending the unified theory of acceptance and use of technology. Management Information Systems Quarterly, 36(1), 157. https://doi.org/10.2307/41410412
Waheed, M., & Jam, F. A. (2010). Teacher’s intention to accept online education: Extended TAM model. Interdisciplinary Journal of Contemporary Research in Business, 2(5), 330-344.
Yildiz, Y. (2021). Teaching English as a Foreign Language to 4th Grade Students by Using Technology. Canadian Journal of Language and Literature Studies, 1(2), 38-54. https://doi.org/10.53103/cjlls.v1i2.16
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