Factor of zoom cloud meetings (ZCM): Technology adoption on the pandemic covid-19

Zulherman Zulherman, Zalik Nuryana, Astadi Pangarso, Farah Mohamad Zain


The purpose of this study is to prove the factors that influence the use of online learning platforms used in the co-19 pandemic. The method used in this study is a study that uses quantitative methods to analyze the validity and reliability of items and to test hypotheses. This study uses the theory of UTAUT2 models with several other variables. The total participants in this questionnaire were 175 people: lecturers. teachers. and students at the university and were randomly drawn. Consists of ten independent variables and one dependent variable. The findings of this study on ten hypotheses were only two accepted and eight rejected but. the authenticity of this study was never investigated about the purpose of using the Zoom platform during the Covid-19 outbreak in the context of Education in Indonesia.


Technology Adoption; Zoom Cloud Meetings; Learning Platform; Pandemic Covid-19


M. Cascella, M. Rajnik, A. Cuomo, S. C. Dulebohn, and R. Di Napoli, Features, Evaluation and Treatment Coronavirus (COVID-19). 2020.

P. Gt Walker et al., “The Global Impact of COVID-19 and Strategies for Mitigation and Suppression,” Imp. Coll., 2020, doi: doi.org/10.25561/77735.

M. U. G. Kraemer et al., “The effect of human mobility and control measures on the COVID-19 epidemic in China,” Science, 2020, doi: 10.1126/science.abb4218.

J. Torales, M. O’Higgins, J. M. Castaldelli-Maia, and A. Ventriglio, “The outbreak of COVID-19 coronavirus and its impact on global mental health,” International Journal of Social Psychiatry. 2020, doi: 10.1177/0020764020915212.

K. Tolksdorf, S. Buda, E. Schuler, L. H. Wieler, and W. Haas, “Influenza-associated pneumonia as reference to assess seriousness of coronavirus disease (COVID-19),” Eurosurveillance, 2020, doi: 10.2807/1560-7917.ES.2020.25.11.2000258.

W. Cao et al., “The psychological impact of the COVID-19 epidemic on college students in China,” Psychiatry Res., 2020, doi: 10.1016/j.psychres.2020.112934.

S. Eubank, I. Eckstrand, B. Lewis, S. Venkatramanan, M. Marathe, and C. L. Barrett, “Commentary on Ferguson, et al., ‘Impact of Non-pharmaceutical Interventions (NPIs) to Reduce COVID-19 Mortality and Healthcare Demand,’” Bull. Math. Biol., 2020, doi: 10.1007/s11538-020-00726-x.

W. (PRC) Aylward, Bruce (WHO); Liang, “Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19),” vol. 2019, no. February, pp. 16–24, 2020.

J. R. Hageman, “The Coronavirus Disease 2019 (COVID-19).,” Pediatr. Ann., vol. 49, no. 3, pp. e99–e100, 2020, doi: 10.3928/19382359-20200219-01.

G. Kampf, D. Todt, S. Pfaender, and E. Steinmann, “Persistence of coronaviruses on inanimate surfaces and their inactivation with biocidal agents,” J. Hosp. Infect., vol. 104, no. 3, pp. 246–251, 2020, doi: 10.1016/j.jhin.2020.01.022.

UNESCO, “Multilateral Education Platform’s meeting (online),” en.unesco.org, Mar. 2020. .

A. Pangarso, E. S. Astuti, K. Raharjo, and T. W. Afrianty, “The impact of absorptive capacity and innovation ambidexterity on sustainable competitive advantage: the case of Indonesian higher education,” Entrep. Sustain. Issues, vol. 7, no. 3, pp. 2436–2455, Mar. 2020, doi: 10.9770/jesi.2020.7.3(65).

R. Rusli, A. Rahman, and H. Abdullah, “Student perception data on online learning using heutagogy approach in the Faculty of Mathematics and Natural Sciences of Universitas Negeri Makassar, Indonesia,” Data Br., vol. 29, p. 105152, 2020, doi: 10.1016/j.dib.2020.105152.

J. B. Stambough et al., “The Past, Present, and Future of Orthopedic Education: Lessons Learned From the COVID-19 Pandemic,” J. Arthroplasty, Apr. 2020, doi: 10.1016/j.arth.2020.04.032.

D. F. Radcliffe, “Technological and pedagogical convergence between work-based and campus-based learning,” Educ. Technol. Soc., 2002.

S. Alharbi and S. Drew, “Using the Technology Acceptance Model in Understanding Academics’ Behavioural Intention to Use Learning Management Systems,” Int. J. Adv. Comput. Sci. Appl., vol. 5, no. 1, pp. 143–155, 2014, doi: 10.14569/IJACSA.2014.050120.

K. Mahalakshmi and R. Radha, “Covid 19: a Massive Exposure Towards Web Based Learning,” J. Xidian Univ., vol. 14, no. 4, 2020, doi: 10.37896/jxu14.4/266.

D. Kumar and Rajasekhar, “Too much but less effective: Managing the cognitive load while designing the distance learning instructional formats,” J. Adv. Med. Educ. Prof., vol. 8, no. 2, pp. 107–108, 2020, doi: 10.30476/jamp.2020.85990.1208.Received.

Gunawan., N. M. Y., and Fathoroni, “Variations of Models and Learning Platforms for Prospective Teachers During the COVID-19 Pandemic Period,” Indones. J. Teach. Educ., vol. 1, no. 2, pp. 61–70, 2020.

H. T. Zimmerman, S. M. Land, and Y. J. Jung, “Mobile, Ubiquitous, and Pervasive Learning,” Adv. Intell. Syst. Comput., vol. 406, pp. 101–119, 2016, doi: 10.1007/978-3-319-26518-6.

M. M. Shahabadi and M. Uplane, “Synchronous and Asynchronous e-learning Styles and Academic Performance of e-learners,” Procedia - Soc. Behav. Sci., 2015, doi: 10.1016/j.sbspro.2015.01.453.

B. K. Hyder, A. Kwinn, R. Miazga, M. Murray, and B. Brandon, The elearning Guild’s Handbook on Synchronous e-Learning. 2007.

F. Mayadas, “Asynchronous Learning Networks: A Sloan Foundation Perspective,” Online Learn., vol. 1, no. 1, Mar. 2019, doi: 10.24059/olj.v1i1.1941.

B. H. Khan, Flexible Learning in an Information Society. IGI Global, 2007.

B. Khan, Managing E-Learning Strategies. IGI Global, 2005.

V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “Venkatesh et al (2003) User acceptance of information technology (1),” MIS Q., 2003.

V. Venkatesh, J. Y. L. Thong, and X. Xu, “Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology,” MIS Q. Manag. Inf. Syst., 2012, doi: 10.2307/41410412.

F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Q. Manag. Inf. Syst., 1989, doi: 10.2307/249008.

A. A. Alalwan, Y. K. Dwivedi, N. P. Rana, B. Lal, and M. D. Williams, “Consumer adoption of Internet banking in Jordan: Examining the role of hedonic motivation, habit, self-efficacy and trust,” J. Financ. Serv. Mark., vol. 20, no. 2, pp. 145–157, 2015, doi: 10.1057/fsm.2015.5.

R. Cheung and D. Vogel, “Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning,” Comput. Educ., vol. 63, pp. 160–175, 2013, doi: 10.1016/j.compedu.2012.12.003.

G. Falloon and E. Khoo, “Exploring young students’ talk in iPad-supported collaborative learning environments,” Comput. Educ., vol. 77, pp. 13–28, 2014, doi: 10.1016/j.compedu.2014.04.008.

P. K. Nair, F. Ali, and L. C. Leong, “Factors affecting acceptance & use of ReWIND: Validating the extended unified theory of acceptance and use of technology,” Interact. Technol. Smart Educ., vol. 12, no. 3, pp. 183–201, 2015, doi: 10.1108/ITSE-02-2015-0001.

Y. T. C. Yang and W. C. I. Wu, “Digital storytelling for enhancing student academic achievement, critical thinking.; Learning motivation: A year-long experimental study,” Comput. Educ., vol. 59, no. 2, pp. 339–352, 2012, doi: 10.1016/j.compedu.2011.12.012.

B. Šumak and A. Šorgo, “The acceptance and use of interactive whiteboards among teachers: Differences in UTAUT determinants between pre- and post-adopters,” Comput. Human Behav., vol. 64, pp. 602–620, 2016, doi: 10.1016/j.chb.2016.07.037.

M. Limayem, S. G. Hirt, C. M. K. Cheung, and S. G. Hirt, “How habit limits the predictive power of intention: The case of information system continuance,” MIS Q., vol. 31, no. 4, pp. 705–737, 2007.

A. Tesser, D. Whitaker, L. Martin, and D. Ward, “Attitude Physiological Attitude Change and,” J. Pers., vol. 24, no. I, pp. 89–96, 1998.

F. M. Zain, E. Hanafi, Y. Don, M. F. M. Yaakob, and S. N. Sailin, “Investigating student’s acceptance of an EDMODO content management system,” Int. J. Instr., vol. 12, no. 4, pp. 1–16, 2019, doi: 10.29333/iji.2019.1241a.

M. A. Yeop, M. F. M. Yaakob, K. T. Wong, Y. Don, and F. M. Zain, “Implementation of ICT policy (blended learning approach): Investigating factors of behavioural intention and use behaviour,” Int. J. Instr., vol. 12, no. 1, pp. 767–782, 2019, doi: 10.29333/iji.2019.12149a.

T. Teo, C. B. Lee, and C. S. Chai, “Understanding pre-service teachers’ computer attitudes: Applying and extending the technology acceptance model,” J. Comput. Assist. Learn., vol. 24, no. 2, pp. 128–143, 2008, doi: 10.1111/j.1365-2729.2007.00247.x.

T. Teo and J. Noyes, “An assessment of the influence of perceived enjoyment and attitude on the intention to use technology among pre-service teachers: A structural equation modeling approach,” Comput. Educ., vol. 57, no. 2, pp. 1645–1653, 2011, doi: 10.1016/j.compedu.2011.03.002.

S. S. Liaw, H. M. Huang, and G. D. Chen, “Surveying instructor and learner attitudes toward e-learning,” Comput. Educ., vol. 49, no. 4, pp. 1066–1080, 2007, doi: 10.1016/j.compedu.2006.01.001.

M. K. O. Lee, C. M. K. Cheung, and Z. Chen, “Acceptance of Internet-based learning medium: The role of extrinsic and intrinsic motivation,” Inf. Manag., vol. 42, no. 8, pp. 1095–1104, 2005, doi: 10.1016/j.im.2003.10.007.

E. S. Varol, B. Toker, and E. Tarcan, “A Study on the Acceptance of Information Technologies From the Perspectives of the Academicians in Turkey,” Ege Akad. Bakis (Ege Acad. Rev., vol. 10, no. 3, pp. 791–791, 2010, doi: 10.21121/eab.2010319615.

C. M. Ringle, M. Sarstedt, R. Schlittgen, and C. R. Taylor, “PLS path modeling and evolutionary segmentation,” J. Bus. Res., vol. 66, no. 9, pp. 1318–1324, 2013, doi: 10.1016/j.jbusres.2012.02.031.

J. F. Hair Jr, G. T. M. Hult, C. Ringle, and M. Sarstedt, A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications, 2016.

J. C. Anderson and D. W. Gerbing, “Structural equation modeling in practice: A review and recommended two-step approach.,” Psychol. Bull., vol. 103, no. 3, p. 411, 1988.

J. F. Hair, J. J. Risher, M. Sarstedt, and C. M. Ringle, “When to use and how to report the results of PLS-SEM,” Eur. Bus. Rev., vol. 31, no. 1, pp. 2–24, 2019, doi: 10.1108/EBR-11-2018-0203.

DOI: http://doi.org/10.11591/ijere.v10i3.21726


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