Teachers Intention to Use E-Learning During The Covid-19 Pandemic: Age and Gender Perspective





age, gender, teachers intention, e-learning


During the Covid-19 pandemic, learning was carried out online using an e-learning system. With this system, all students and teachers can even carry out learning even though they are at home. This study aims to analyze teachers' intentions in using e-learning during the covid-19 pandemic. This study uses a modified model of TAM (Technology Acceptance Model). This study uses 7 Likert scales in measuring all indicators. The data analysis method uses Structured Equation Models (SEM). The results of the study show that perceived ease of use (USE) has a significant effect on teacher intentions in utilizing e-learning, while perceived ease of use (EASE) has no significant effect on the use of e-learning. Gender was not proven to be a moderating variable on the relationship between USE and EASE with teachers' intentions to use e-learning. Teacher age strengthens the USE relationship to e-learning use. However, teacher age weakens the relationship between EASE and e-learning use. Male and female teachers have the same understanding regarding e-learning. In addition, teachers with a more mature age see e-learning as a system that provides benefits for them to carry out their duties as teachers. They also focus more on improving performance. On the other hand, teachers with more mature ages are less concerned about the ease of using e-learning.

Author Biographies

Kardoyo, Universitas Negeri Semarang, Semarang, Indonesia

Pendidikan Ekonomi

Kusumantoro, Universitas Negeri Semarang, Semarang, Indonesia

Pendidikan Ekonomi

Ahmad Nurkhin, Universitas Negeri Semarang, Semarang, Indonesia

Pendidikan Ekonomi

Hasan Mukhibad, Universitas Negeri Semarang, Semarang, Indonesia



Al-Maroof, R. S., & Salloum, S. A. (2021). An Integrated Model of Continuous Intention to Use of Google Classroom. https://doi.org/10.1007/978-3-030-47411-9_18.

Alabdullatif, H., & Velázquez-Iturbide, J. Á. (2020). Personality Traits and Intention to Continue Using Massive Open Online Courses (ICM) in Spain: The Mediating Role of Motivations. International Journal of Human-Computer Interaction, 36(20), 1953–1967. https://doi.org/10.1080/10447318.2020.1805873.

Alqahtani, A. Y., & Rajkhan, A. A. (2020). E-learning critical success factors during the covid-19 pandemic: A comprehensive analysis of e-learning managerial perspectives. Education Sciences, 10(9), 1–16. https://doi.org/10.3390/educsci10090216.

Ansong-Gyimah, K. (2020). Students’ perceptions and continuous intention to use elearning systems: The case of google classroom. International Journal of Emerging Technologies in Learning, 15(11), 236–244. https://doi.org/10.3991/IJET.V15I11.12683.

Arpaci, I., & Basol, G. (2020). The impact of preservice teachers’ cognitive and technological perceptions on their continuous intention to use flipped classroom. Education and Information Technologies, 3503–3514. https://doi.org/10.1007/s10639-020-10104-8.

Aydın, C. H., & Tasci, D. (2005). Measuring Readiness for e-Learning : Reflections from an Emerging Country. International Forum of Educational Technology & Society, 8(4), 244–257. https://www.jstor.org/stable/pdf/jeductechsoci.8.4.244.pdf.

Barton, S. M. (2013). Social Capital Framework in the Adoption of E-Learning. International Journal on E-Learning: Corporate, Government, Healthcare, and Higher Education, 12(2), 115–137. https://www.learntechlib.org/p/39145/.

Bhuana, G. P., & Apriliyanti, D. L. (2021). Teachers’ encounter of online learning: Challenges and support system. Journal of English Education and Teaching, 5(1), 110–122. https://doi.org/10.33369/jeet.5.1.110-122.

Buabeng-Andoh, C. (2018). Predicting students’ intention to adopt mobile learning. Journal of Research in Innovative Teaching & Learning, 11(2), 178–191. https://doi.org/10.1108/jrit-03-2017-0004.

Chen, J., Lin, C. H., & Chen, G. (2021). A cross-cultural perspective on the relationships among social media use, self-regulated learning and adolescents’ digital reading literacy. Computers and Education, 175(September). https://doi.org/10.1016/j.compedu.2021.104322.

Coman, C., Țîru, L. G., Meseșan-Schmitz, L., Stanciu, C., & Bularca, M. C. (2020). Online teaching and learning in higher education during the coronavirus pandemic: Students’ perspective. Sustainability (Switzerland), 12(24), 1–22. https://doi.org/10.3390/su122410367.

Farah, M. F. (2017). Application of the theory of planned behavior to customer switching intentions in the context of bank consolidations. International Journal of Bank Marketing, 35(1), 147–172. https://doi.org/10.1108/IJBM-01-2016-0003.

Grande-De-prado, M., Cañón, R., García-Martín, S., & Cantón, I. (2020). Digital competence and gender: Teachers in training. a case study. Future Internet, 12(11), 1–15. https://doi.org/10.3390/fi12110204.

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.

He, Y., Chen, Q., & Kitkuakul, S. (2018). Regulatory focus and technology acceptance: Perceived ease of use and usefulness as efficacy. Cogent Business and Management, 5(1), 1–22. https://doi.org/10.1080/23311975.2018.1459006.

Ibrahima, N. K., Raddadia, R. Al, AlDarmasia, M., Ghamdia, A. Al, Gaddourya, M., AlBara, H. M., & Ramadana, I. K. (2021). Medical students’ acceptance and perceptions of e-learning during the Covid-19 closure time in King Abdulaziz University, Jeddah. Journal of Infection and Public Health, 14(1), 17–23. https://doi.org/10.1016/j.jiph.2020.11.007.

Karasan, A., & Erdogan, M. (2021). Prioritization of Influence Factors for Selecting E – Learning Systems. Advances in Intelligent Systems and Computing, 1, 550–556. https://doi.org/10.1007/978-3-030-51156-2.

Khechine, H., Raymond, B., & Augier, M. (2020). The adoption of a social learning system: Intrinsic value in the UTAUT model. British Journal of Educational Technology, 51(6), 2306–2325. https://doi.org/10.1111/bjet.12905.

Laar, E. V, Deursen, A. J. A. M. V, Dijk, J. A. G. ., & Haan, J. D. (2020). Determinants of 21st-century skills and 21st-century digital skills for workers: A systematic literature review. SAGE Journal, 10(1), 1–14. https://doi.org/10.1177/2158244019900176.

Lin, S. H., Lee, H. C., Chang, C. Ter, & James Fu, C. (2020). Behavioral intention towards mobile learning in Taiwan, China, Indonesia, and Vietnam. Technology in Society, 63(September), 101387. https://doi.org/10.1016/j.techsoc.2020.101387.

Majid, F. A., & Shamsudin, N. M. (2019). Identifying factors affecting acceptance of virtual reality in classrooms based on Technology Acceptance Model (TAM). Asian Journal of University Education, 15(2), 52–60. https://doi.org/10.24191/ajue.v15i2.7556.

Martono, S., Mukhibad, H., Anisykurlillah, I., & Nurkhin, A. (2020). Evaluation of acceptance of information systems in state university with theory of planned behavior and theory of acceptance model approaches. Management Science Letters, 10, 3225–3234. https://doi.org/10.5267/j.msl.2020.6.016.

Mohan, M. M., Upadhyaya, P., & Pillai, K. R. (2020). Intention and barriers to use MOOCs: An investigation among the post graduate students in India. Education and Information Technologies, 25(6), 5017–5031. https://doi.org/10.1007/s10639-020-10215-2.

Mutambik, I., Lee, J., & Almuqrin, A. (2020). Role of gender and social context in readiness for e-learning in Saudi high schools. Distance Education, 41(4), 515–539. https://doi.org/10.1080/01587919.2020.1821602.

Nariman, D. (2021). Impact of the Interactive e-Learning Instructions on Effectiveness of a Programming. Advances in Intelligent Systems and Computing, 588–597. https://doi.org/10.1007/978-3-030-50454-0.

Nugroho, A., & Mutiaraningrum, I. (2020). EFL teachers’ beliefs and practices about digital learning of English. EduLite: Journal of English Education, Literature and Culture, 5(2), 304–321. https://doi.org/10.30659/e.5.2.304-321.

Nurlaily, V. A., Soegiyanto, H., & Usodo, B. (2019). Elementary school teacher’s obstacles in the implementation of problem-based learning model in mathematics learning. Journal on Mathematics Education, 10(2), 229–238. https://doi.org/10.22342/jme.10.2.5386.229-238.

Onyema, E. M., Chika, E. N., Ayobamidele, O. F., Sen, S. S., Grace, A. F., Aabha, S., & Omar, A. A. (2020). Impact of Coronavirus Pandemic on Education. Journal of Education and Practice, 11(13), 108–121. https://doi.org/10.7176/jep/11-13-12.

Prasojo, L. D., Habibi, A., Mukminin, A., Sofyan, Indrayana, B., & Anwar, K. (2020). Factors influencing intention to use web 2.0 in Indonesian vocational high schools. International Journal of Emerging Technologies in Learning, 15(5), 100–118. https://doi.org/10.3991/ijet.v15i05.10605.

Raza, S. A., & Qazi, W. (2020). Social Isolation and Acceptance of the Learning Management System ( LMS ) in the time of COVID-19 Pandemic : An Expansion of the UTAUT Model. Journal of Educational Computing Research, 58(8), 1–26. https://doi.org/10.1177/0735633120960421.

Sari, D. A., Ellizar, E., & Azhar, M. (2019). Development of problem-based learning module on electrolyte and nonelectrolyte solution to improve critical thinking ability. Journal of Physics: Conference Series, 1185(1). https://doi.org/10.1088/1742-6596/1185/1/012146.

Siron, Y., Wibowo, A., & Narmaditya, B. S. (2020). Factors Affecting The Adoption Of E-Learning In Indonesia : Lesson From Covid-19. Journal of Technology and Science Education, 10(2), 282–295. https://doi.org/10.3926/jotse.1025.

So, K. K. T., & Swatman, P. (2010). The Diminishing Influence of Age and Gender on e-Learning Readiness of Teachers in Hong Kong. International Conference on Hybrid Learning, 477–488. https://doi.org/https://doi.org/10.1007/978-3-642-14657-2_43.

Sukendro, S., Habibi, A., Khaeruddin, K., Indrayana, B., Syahruddin, S., Alfrets, F., & Hakim, H. (2020). Heliyon Using an extended Technology Acceptance Model to understand students ’ use of e-learning during Covid-19 : Indonesian sport science education context. Heliyon, 6(August), e05410. https://doi.org/10.1016/j.heliyon.2020.e05410.

Venkatesh, V. (2003). User Acceptance of Information Technology: Toward A Unified View. MIS Quarterly, 47(2), 425–478. https://doi.org/10.1006/mvre.1994.1019.

Yawson, D. E., & Yamoah, F. A. (2020). Understanding satisfaction essentials of E-learning in higher education: A multi-generational cohort perspective. Heliyon, 6(11), e05519. https://doi.org/10.1016/j.heliyon.2020.e05519.

Yildiz Durak, H. (2019). Examining the acceptance and use of online social networks by preservice teachers within the context of unified theory of acceptance and use of technology model. In Journal of Computing in Higher Education (Vol. 31, Issue 1). Springer US. https://doi.org/10.1007/s12528-018-9200-6.