Education Quarterly Reviews
Published: 22 November 2021
Digital Immigrant Lectures’ Acceptance of e-Learning Portal: An Application of UTAUT Model
Jefri Marzal, Reni Aryani, Rina Kusuma Dewi, Saharudin
Universitas Jambi, Indonesia
Download Full-Text Pdf
Keywords: Immigrant Digital, e-learning, User Acceptance, UTAUT Model
One of the challenges in implementing e-learning in tertiary institutions is the large number of lecturers who are categorized as digital immigrants. This group has the tendency of having difficulties with Information and Communication Technology (ICT) and showing some resistance to ICT. This study aims to determine the factors that influence digital immigrants in accepting e-learning at the University of Jambi using the Unified Theory Acceptance of User Technology (UTAUT) model. Factors to be tested include innovation, perceived usefulness, perceived ease of use, attitudes towards e-learning, risk perception, and acceptance of digital immigrant lecturers. The sample in this study was 55 digital immigrant lecturers. The results of this study indicate that there are as many as 6 out of 9 hypotheses accepted significantly. The finding reveals that the acceptance of e-learning is only influenced by the perceived usefulness.
Abramson, J., Dawson, M., & Stevens, J. (2015). An Examination of the Prior Use of E-Learning Within an Extended Technology Acceptance Model and the Factors That Influence the Behavioral Intention of Users to Use M-Learning. SAGE Open, 5(4). https://doi.org/10.1177/2158244015621114
Amer, A.-A., Ahmad, A.-A., & Jo, S. (2013). Exploring Students Acceptance of E-learning Using Technology Acceptance Model in Jordanian Universities. International Journal of Education and Development Using Information and Communication Technology, 9(2), 4–18. Retrieved from http://ijedict.dec.uwi.edu/viewarticle.php?id=1617
Arsanti, T. A., & Yuliasari, E. (2018). Personal Factors As Predictors of Intention To Use It. Jurnal Manajemen Dan Kewirausahaan, 20(2), 129–136. https://doi.org/10.9744/jmk.20.2.129-136
Cappel, J. J., Hayen, R. L., Cappel, J. J., Hayen, R. L., Case, E. E. A., Cappel, J. J., & Hayen, R. L. (2017). Evaluating E-Learning : A Case Study EVALUATING E-LEARNING : A CASE STUDY. Journal of Computer Information Systems, 4417(May). https://doi.org/10.1080/08874417.2004.11647595
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13, 319–340.
Fornell, C., & Larcker, D. F. (1981). Structural equation models withunobservablee variables and measurement. Journal of Marketing Research, 18(1), 39–50.
Ghozali, I. (2014). Structural Equation Modeling(4th ed.). Semarang: Badan Penerbit - Undip.
Golladay, R. M., Prybutok, V. R., & Huff, R. A. (2000). Critical success factors for the online learner. Journal of Computer Information Systems, 40(4), 69–71.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis(Seventh). Pearson Education Limited.
Hamid, A. A., Razak, F. Z. A., Bakar, A. A., & Abdullah, W. S. W. (2016). The Effects of Perceived Usefulness and Perceived Ease of Use on Continuance Intention to Use E-Government. Procedia Economics and Finance, 35(October 2015), 644–649. https://doi.org/10.1016/s2212-5671(16)00079-4
Hsu, M. W. (2016). An analysis of intention to use in innovative product development model through TAM model. Eurasia Journal of Mathematics, Science and Technology Education, 12(3), 487–501. https://doi.org/10.12973/eurasia.2016.1229a
Koohang, A., & Harman, K. (2005). Open source: A metaphor for E-learning. Informing Science, 8, 75–86.
Lawson-Body, A., Willoughby, L., Lawson-Body, L., & Tamandja, E. M. (2018). Students’ acceptance of E-books: An application of UTAUT. Journal of Computer Information Systems, 4417, 1–12. https://doi.org/10.1080/08874417.2018.1463577
Leung, H. K. N. (2003). Evaluating the effectiveness of e-learning. International Journal of Phytoremediation, 21(1), 123–136. https://doi.org/10.1076/csed.188.8.131.5201
Mcmahon, M., & Pospisil, R. (2005). Laptops for a digital lifestyle: Millennial students and wireless mobile technologies. ASCILITE 2005 - The Australasian Society for Computers in Learning in Tertiary Education, (2001), 421–431.
Okumus, B., Ali, F., Bilgihan, A., & Ozturk, A. B. (2018). Psychological factors influencing customers’ acceptance of smartphone diet apps when ordering food at restaurants. International Journal of Hospitality Management, 72(October 2016), 67–77. https://doi.org/10.1016/j.ijhm.2018.01.001
Pando-Garcia, J., Periañez-Cañadillas, I., & Charterina, J. (2016). Business simulation games with and without supervision: An analysis based on the TAM model. Journal of Business Research, 69(5), 1731–1736. https://doi.org/10.1016/j.jbusres.2015.10.046
Sancar, H., & Cagiltay, K. (2008). Effective Use of LMS: Pedagogy through the Technology. In EdMedia+ Innovate Learning. Association for the Advancement of Computing in Education (AACE), 3927–3933. Retrieved from https://s3.amazonaws.com/academia.edu.documents/32391967/proceeding_28931.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1556642985&Signature=7Y19vPPIfTRJLS9y6tszeky16AI%3D&response-content-disposition=inline%3B filename%3DEffective_Use_of_LMS_Pedagogy_t
Sayid, O., & Echchabi, A. (2013). Attitude of Somali Customers towards Mobile Banking Services: The Case of Zaad and Sahal Services. Economic Insights: Trends and Challenges, 65(3), 9–16.
UNICEF. (2020). Key Messages and Actions for COVID-19 Prevention and Control in Schools.
Venkatesh, V., & Smith, R. H. (2003). User Acceptance of Information Techonology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. https://doi.org/10.1016/j.inoche.2016.03.015
Vodanovich, S., Sundaram, D., & Myers, M. (2010). Digital natives and ubiquitous information systems. Information Systems Research, 21(4), 711–723. https://doi.org/10.1287/isre.1100.0324
Weeden, K. A., & Cornwell, B. (2020). The Small-World Network of College Classes: Implications for Epidemic Spread on a University Campus. Sociological Science, 7(9), 222–241. https://doi.org/10.15195/v7.a9
Weng, F., Yang, R.-J., Ho, H.-J., & Su, H.-M. (2018). A TAM-Based Study of the Attitude towards Use Intention of Multimedia among School Teachers. Applied System Innovation, 1(3), 36. https://doi.org/10.3390/asi1030036
Xhaferi, G., Farizi, A., & Bahiti, R. (2018). Teacher’ attitudes towards e-learning in higher education in Macedonia Case study: University of Tetovo. European Journal of Electrical Engineering and Computer Science, 2(5), 14–17. https://doi.org/10.24018/ejece.2018.2.5.26
Yang, Q., Pang, C., Liu, L., Yen, D. C., & Michael Tarn, J. (2015). Exploring consumer perceived risk and trust for online payments: An empirical study in China’s younger generation. Computers in Human Behavior, 50, 9–24. https://doi.org/10.1016/j.chb.2015.03.058
Yi, M. Y., Fiedler, K. D., & Park, J. S. (2006). Understanding the Role of Individual Innovativeness in the Acceptance ... Decision Sciences, 37(3), 393–426.
Zur, O., & Walker, A. (2011). Psychology of the Web & Internet Addiction. Retrieved from https://www.zurinstitute.com/internet-addiction/