• Umi Chotijah Universitas Muhammadiyah Gresik
  • Harunur Rosyid Universitas Muhammadiyah Gresik Indonesia
  • Fitri Retrialisca Universitas Airlangga
  • Mochammad Ichsan Universitas Muhammadiyah Gresik
Keywords: COVID-19; UTAUT; Smart Pls; LMS; Higher education; Senior High School; Vocational School;


The COVID-19 pandemic that emerged in 2019, in wuhan, Hubei province, China has spread almost throughout the world, including Indonesia. The impact of the virus is that the government has issued public policies, which include social distancing, social isolation, and self-quarantine. Various sectors must implement the policy. Several companies in Indonesia have to enforce working from home for all their employees, including educational institutions in Indonesia, from the level of Playgroups, Early Childhood Education, Kindergartens, Elementary Schools, Junior High Schools, Public High Schools or Senior High Schools. Vocational High Schools and Universities also apply an online learning process from home. Information Technology provides solutions for the education system in Indonesia in these difficult times, so that the learning process can continue. In previous studies, an exploration of the Unified Theory of Acceptance and Use of Technology (UTAUT) model with social isolation variables, and corona fear moderating variables was carried out on the Behavioral Intentions of the Learning Management System and the Behavior of the Use of Learning Management Systems among General or Vocational High School students. Data analysis using Smart Partial Least Square (PLS) and Structural Equation Modeling (SEM). The findings show a positive relationship of Performance Expectations (PE), Effort Expectations (EE), Social Influence (SI), and Social Isolation on LMS Behavioral Intentions and, also between LMS Behavioral Intentions and Use Behavior. In addition, the results of the moderation analysis show that the fear of Corona only moderates the relationship between Performance Expectations and Social Influences with LMS Behavioral Intentions. The findings imply the need to increase the behavioral intentions of LMS users among college students or students.


Download data is not yet available.

Author Biography

Umi Chotijah, Universitas Muhammadiyah Gresik

Teknik Informatika


Ahorsu, D. K. et al., 2020. The Fear of COVID-19 Scale: Development and Initial Validation. International Journal of Mental Health and Addiction, 27 March.pp. 1-9.
Ain, N., Kaur, K. & Waheed, M., 2015. The influence of learning value on learning management system use: An extension of UTAUT2. Information Development, 30 June.pp. 1-16.
Al-Busaidi, K. A. & Al-Shihi, H., 2010. Instructors' Acceptance of Learning Management Systems: A Theoretical Framework. pp. 1-10.
Alias, N. & Zainuddin, M., 2005. Innovation for better teaching and learning: Adopting the earning management system. Malaysian Online Journal of Instructional Technology, 2(2), pp. 27-40.
Al-Imarah, A., Zwain, A. & Al-Hakim, L., 2013. The adoption of e-government services in the Iraqi Higher Education Context: An application of the UTAUT model in the University of Kufa. Journal of Information Engineering and Applications, 3(10), p. 77–84.
Anderson, R. M., Heesterbeek, H., Klinkenberg, D. & Hollingsworth, T. D., 2020. How will country-based mitigation measures influence the course of the COVID-19 epidemic?. THE LANCET, 21 March, 395(10228), pp. 931-934.
De Jong Gierveld, . J., Van Tilburg, T. & Dykstra, P., 2016. The Cambridge handbook of personal relationship . In: Loneliness and social isolation In V. Anita & P. Daniel (Eds.). s.l.:Cambridge University Press, pp. 1-30.
Decman, M., 2015. Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender. Computers in Human Behavior, Volume 49, p. 272–281.
Iqbal, S., 2011. Learning management systems (LMS): Inside matters. Information Management and Business Review, 3(4), pp. 206-216.
Lin, C., 2020. Social reaction toward the 2019 novel coronavirus (COVID-19). Social Health and Behavior, 3(1), pp. 1-2.
Lonn, S., Teasley, S. & Krumm, A. E., 2011. Who needs to do what where?: Using learning management systems on residential vs. commuter campuses. Computers &, 5(3), p. 642–649.
Ma, , W. & Yuen, , A., 2011. E-learning system acceptance and usage pattern. In: In T. Teo (Eds.) Technology Acceptance in Education. s.l.:Brill Sense, p. 201–216.
Matar, N., Hunaiti, Z., Halling , S. & Matar, S., 2011. E-Learning acceptance and challenges in the Arab region. In: In S. Abdallah, & A. Fayez Ahmad (Eds.) ICT acceptance, investment and organization: Cultural practices and values in the Arab world. s.l.:IGI Global., pp. 184-200.
Mertens, G. et al., 2020. Fear of the coronavirus (COVID-19): Predictors in an online study conducted in March 2020. Journal of Anxiety Disorders, August 2020.74(102258).
Ngai, E. W., Poon, J. K. L. & Chan, Y. H., 2007. Empirical examination of the adoption of WebCT using TAM. Computers & Education, 48(2), p. 250–267.
Pakpour, A. H. & Griffiths, . M. D., 2020. The fear of CoVId-19 and its role in preventive behaviors. Journal of Concurrent Disorders.
Raza, S. A., Qazi, W., Khan, K. A. & J. S., 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, 0(0), pp. 1-26.
Rozandy, R. A., I. S. & Putri, S. A., 2013. Analisis Variabel–Variabel yang Mempengaruhi Tingkat Adopsi Teknologi dengan Metode Partial Least Square (Studi Kasus Pada Sentra Industri Tahu Desa Sendang, Kec. Banyakan, Kediri). Jurnal Industria, 1(3), pp. 147-158.
Teo, T., 2011. Factors influencing teachers’ intention to use technology: Model development and test. Computers & Education, 57(4), p. 2432–2440.
Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. D., 2003. User acceptance of information technology: Toward a unified view. MIS Quarterly, Volume 27, p. 425–478.
Waheed, M., Kaur, , K., Ain, N. & Hussain, , N., 2016. Perceived learning outcomes from Moodle: An empirical study of intrinsic and extrinsic motivating factors. Information Development, 32(4), p. 1001–1013.
Yoo, S. J., Han, , S. H. & Huang, W., 2012. The roles of intrinsic motivators and extrinsic motivators in promoting e-learning in the workplace: A case from South Korea. Computers in Human Behavior, 28(3), p. 942–950.
Zwain, A. A. A., 2019. Technological innovativeness and information quality as neoteric predictors of users’ acceptance of learning management system An expansion of UTAUT2. Interactive Technology and Smart Education, 16(3), pp. 239-254.
How to Cite