E-learning Acceptance Model in a Pandemic Period with an Expansion to the Quality of Work Life and Information Technology Self-Efficacy Aspects

Authors

DOI:

https://doi.org/10.21512/commit.v16i2.8145

Keywords:

E-Learning, Acceptance Model, Quality of Work Life, Information Technology Self-Efficacy

Abstract

The research is inspired by the COVID-19 pandemic which affects face-to-face learning and leads to the e-learning system. However, educational institutions and related parties are not prepared for this sudden change. So, it is interesting to research the students’ intentions related to learning during the pandemic in the framework of the Technology Acceptance Model (TAM). Specifically, the research aims to analyze the acceptance and satisfaction model of e-learning users amid the pandemic. The proposed model that predicts student intentions and satisfaction with e-learning is an expanded TAM with factors such as quality of work life and information technology self-efficacy. The research provides empirical evidence related to the quality of work balance and the ability to use information technology related to e-learning access, in addition to other factors in the TAM. The data are collected by distributing online questionnaires with a snowball sampling model. The sample includes students who voluntarily fill out the questionnaire from various Indonesian universities. Then, the structural equation model processes the data using a Partial Least Square (PLS) approach and analyzes it through the SmartPLS3 program. The results show that the variables of quality of work life and information technology self-efficacy, such as computers, the Internet, and communication, can explain the acceptance of elearning models, especially during a pandemic. As an implication of the results, the teachers should focus on elearning designs that facilitate access to learning material and student-teacher interactions to attract intentions and increase students’ satisfaction in using e-learning.

Dimensions

Plum Analytics

Author Biographies

Weli, Universitas Katolik Indonesia Atma Jaya Jakarta

Fakultas Ekonomi dan Bisnis

Julianti Sjarief, Universitas Katolik Indonesia Atma Jaya Jakarta

Fakultas Ekonomi dan Bisnis

References

C. Coman, L. G. Tˆıru, L. Mesesan-Schmitz, C. Stanciu, and M. C. Bularca, “Online teaching and learning in higher education during the Coronavirus pandemic: Student’ perspective,” Sustainability, vol. 12, no. 24, pp. 1–24, 2020.

Q. Aini, M. Budiarto, P. O. H. Putra, and U. Rahardja, “Exploring e-learning challenges during the global COVID-19 pandemic: A review,” Jurnal Sistem Informasi, vol. 16, no. 2, pp. 57–65, 2020.

S. Abbasi, T. Ayoob, A. Malik, and S. I. Memon, “Perceptions of students regarding e-learning during COVID-19 at a private medical college,” Pakistan Journal of Medical Sciences, vol. 36, no. COVID19-S4, pp. S57–S61, 2020.

M. A. Almaiah, A. Al-Khasawneh, and A. Althunibat, “Exploring the critical challenges and factors influencing the e-learning system usage during COVID-19 pandemic,” Education and Information Technologies, vol. 25, no. 6, pp. 5261–5280, 2020.

A. Y. Alqahtani and A. A. Rajkhan, “E-learning critical success factors during the COVID-19 pandemic: A comprehensive analysis of e-learning managerial perspectives,” Education Sciences, vol. 10, no. 9, pp. 1–16, 2020.

M. Lynch, “E-learning during a global pandemic.” Asian Journal of Distance Education, vol. 15, no. 1, pp. 189–195, 2020.

M. Z. Hoq, “E-learning during the period of pandemic (COVID-19) in the kingdom of Saudi Arabia: An empirical study,” American Journal of Educational Research, vol. 8, no. 7, pp. 457–464, 2020.

Y. L. Huam´an-Roman´ı, J. Estrada-Pant´ıa, O. Olivares-Rivera, E. Rodas-Guizado, and F. Fuentes-Bernedo, “Use of technological equipment for e-learning in Peruvian university students in times of COVID-19,” International Journal of Emerging Technologies in Learning (iJET), vol. 16, no. 20, pp. 119–133, 2021.

K. Yatigammana and G. Wijayarathna, “Students’ perceptions of online lecture delivery modes: Higher education during COVID-19 pandemic and beyond,” International Journal of Emerging Technologies in Learning (iJET), vol. 16, no. 21, pp. 58–73, 2021.

A. Mehta, N. P. Morris, B. Swinnerton, and M. Homer, “The influence of values on e-learning adoption,” Computers & Education, vol. 141, pp. 1–16, 2019.

A. Tarhini, K. Hone, and X. Liu, “Factors affecting students’ acceptance of e-learning environments in developing countries: A structural equation modeling approach,” vol. 3, no. 1, pp. 54–59, 2013.

Z. Ghali-Zinoubi, A. Amari, and F. Jaoua, “Elearning in era of COVID-19 pandemic: Impact of flexible working arrangements on work pressure, work–life conflict and academics’ satisfaction,” Vision, pp. 1–12, 2021.

A. Tarhini, K. Hone, and X. Liu, “A crosscultural examination of the impact of social, organisational and individual factors on educational technology acceptance between British and Lebanese university students,” British Journal of Educational Technology, vol. 46, no. 4, pp. 739–755, 2015.

Y. Siron, A. Wibowo, and B. S. Narmaditya, “Factors affecting the adoption of e-learning in Indonesia: Lesson from COVID-19,” JOTSE: Journal of Technology and Science Education, vol. 10, no. 2, pp. 282–295, 2020.

C. Wiradendi Wolor, S. Solikhah, N. F. Fidhyallah, and D. P. Lestari, “Effectiveness of etraining, e-leadership, and work life balance on employee performance during COVID-19,” Journal of Asian Finance, Economics and Business, vol. 7, no. 10, pp. 443–450, 2020.

R. Bucea-Manea-T, onis¸, R. Bucea-Manea-T, onis¸, V. E. Simion, D. Ilic, C. Braicu, and N. Manea, “Sustainability in higher education: The relationship between work-life balance and XR elearning facilities,” Sustainability, vol. 12, no. 14, pp. 1–19, 2020.

G. R. Berry and H. Hughes, “Integrating work–life balance with 24/7 information and communication technologies: The experience of adult students with online learning,” American Journal of Distance Education, vol. 34, no. 2, pp. 91–105, 2020.

A. Tarhini, K. Hone, and X. Liu, “User acceptance towards web-based learning systems: Investigating the role of social, organizational and individual factors in european higher education,” Procedia Computer Science, vol. 17, pp. 189–197, 2013.

S. Caliskan, V. Tugun, and H. Uzunboylu, “University students’ readiness for e-learning,” Ensayos: Revista de la Facultad de Educaci´on de Albacete, vol. 32, no. 2, pp. 35–45, 2017.

A. Popovici and C. Mironov, “Students’ perception on using eLearning technologies,” Procedia-Social and Behavioral Sciences, vol. 180, pp.1514–1519, 2015.

J. M. Chen and R. Y. Song, “Influencing factors of users’ willingness to use online education platform,” Journal of Management and Humanity Research, vol. 5, no. 2021, pp. 1–14, 2021.

F. S. Susilaningsih, M. Komariah, A. S. Mediawati, and V. B. M. Lumbantobing, “Quality of work-life among lecturers during online learning in COVID-19 pandemic period: A scoping review,” Malaysian Journal of Medicine and Health Sciences, vol. 17, no. SUPP4, pp. 163–166, 2021.

F. Y. Yang and C. C. Tsai, “Investigating university student preferences and beliefs about learning in the web-based context,” Computers & Education, vol. 50, no. 4, pp. 1284–1303, 2008.

J. F. Hair, J. J. Risher, M. Sarstedt, and C. M. Ringle, “When to use and how to report the results of PLS-SEM,” European Business Review, vol. 31, no. 1, pp. 2–24, 2019.

J. Sun, S. Ji, and J. Ye, “Partial least squares,” in Multi-Label dimensionality reduction. Chapman and Hall/CRC, 2013.

Downloads

Published

2022-06-08
Abstract 1083  .
PDF downloaded 867  .