logo logo European Journal of Educational Research

EU-JER is is a, peer reviewed, online academic research journal.

Subscribe to

Receive Email Alerts

for special events, calls for papers, and professional development opportunities.

Subscribe

Publisher (HQ)

Eurasian Society of Educational Research
Eurasian Society of Educational Research
7321 Parkway Drive South, Hanover, MD 21076, USA
Eurasian Society of Educational Research
Headquarters
7321 Parkway Drive South, Hanover, MD 21076, USA
gcr utaut model trust learning platform covid 19

Analyzing Indonesian Students’ Google Classroom Acceptance During COVID-19 Outbreak: Applying an Extended Unified Theory of Acceptance and Use of Technology Model

Zulherman , Farah Mohamad Zain , Darmawan Napitupulu , Siti Nazuar Sailin , Liszulfah Roza

The primary goal of this study is to explore what makes teachers accept Google Classroom (GCR). GCR platform is an emerging technology that could supp.

T

The primary goal of this study is to explore what makes teachers accept Google Classroom (GCR). GCR platform is an emerging technology that could support online learning activities by offering outstanding benefits such as usability, flexibility, and task adaptability. Many of the students in Indonesia have al-ready used the GCR platform since the government has tried to provide it as a free online learning tool to support learning activities during the pandemic. However, there is limited understanding of users' behavior, especially Indonesian students' acceptance of the GCR platform. The model is tested by administering the online questionnaire to 261 university students in Indonesia. The extended Unified Theory of Acceptance and Use of Technology Model (UTAUT) model has been applied to observe users’ acceptance of GCR. The result Performance expectancy (PE), Effort expectancy (EE) Social Influence (SI), Facilitating Conditions (FC), Trust of Internet (TI) and Trust of Government (TG) considerably affected users’ intention to use the GCR. Moreover, Trust of Internet (TI) and Trust of Government (TG) also knowingly impacted Performance expectancy (PE).

Keywords: GCR, UTAUT model, trust, learning platform, COVID-19.

cloud_download PDF
Cite
Article Metrics
Views
411
Download
582
Citations
Crossref
0

Scopus
12

References

Abuzant, M., Ghanem, M., Abd-Rabo, A., & Daher, W. (2021). Quality of Using Google Classroom to Support the Learning Processes in the Automation and Programming Course. International Journal of Emerging Technologies in Learning, 16(6), 72. https://doi.org/10.3991/ijet.v16i06.18847

Alalwan, A. A., Baabdullah, A. M., Rana, N. P., Tamilmani, K., & Dwivedi, Y. K. (2018). Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust. Technology in Society, 55, 100–110. https://doi.org/10.1016/j.techsoc.2018.06.007

Almaiah, M. A., Alamri, M. M., & Al-Rahmi, W. M. (2020). Analysis the Effect of Different Factors on the Development of Mobile Learning Applications at Different Stages of Usage. IEEE Access, 8, 16139–16154. https://doi.org/10.1109/ACCESS.2019.2963333

Al-Adwan, A. S., Al-adwan, A., & Berger, H. (2018). Solving the mystery of mobile learning adoption in higher education. International Journal of Mobile Communication, 16(1), 24–49. https://doi.org/10.1504/IJMC.2018.088271

Al-Maroof, R. S., Alshurideh, M. T., Salloum, S. A., AlHamad, A. Q. M., & Gaber, T. (2021). Acceptance of Google Meet during the Spread of Coronavirus by Arab University Students. Informatics, 8(2), 24. https://doi.org/10.3390/informatics8020024

Al-Maroof, R A S, & Al-Emran, M. (2018). Students acceptance of google classroom: An exploratory study using PLS-SEM approach. International Journal of Emerging Technologies in Learning, 13(6), 112–123. https://doi.org/10.3991/ijet.v13i06.8275

Al-Maroof, Rana A. Saeed, & Al-Emran, M. (2018). Students Acceptance of Google Classroom: An Exploratory Study using PLS-SEM Approach. International Journal of Emerging Technologies in Learning, 13(06), 112–123. https://doi.org/10.3991/ijet.v13i06.8275

Amadin, F. I., Obienu, A. C., & Osaseri, R. O. (2018). Main barriers and possible enablers of Google apps for education adoption among university staff members. Nigerian Journal of Technology, 37(2), 432. https://doi.org/10.4314/njt.v37i2.18

Ansong-Gyimah, K. (2020). Students’ Perceptions and Continuous Intention to Use E-Learning Systems: The Case of Google Classroom. International Journal of Emerging Technologies in Learning, 15(11), 236. https://doi.org/10.3991/ijet.v15i11.12683

Asino, T. I., & Pulay, A. (2019). Student Perceptions on the Role of the Classroom Environment on Computer Supported Collaborative Learning. TechTrends, 63(2), 179–187. https://doi.org/10.1007/s11528-018-0353-y

Beer, U. M., Neerincx, M. A., Morina, N., & Brinkman, W. P. (2020). Computer-based perspective broadening support for appraisal training: Acceptance and effects. International Journal of Technology and Human Interaction, 16(3), 86–108. https://doi.org/10.4018/IJTHI.2020070106

Berger, H., Al Adwan, A., & Al Adwan, A. S. (2018). Solving the mystery of mobile learning adoption in higher education. International Journal of Mobile Communications, 16(1), 24. https://doi.org/10.1504/IJMC.2018.10007779

Carta, S., Corriga, A., Mulas, R., Recupero, D., & Saia, R. (2019). A supervised multi-class multi-label word embeddings approach for toxic comment classification. In A. Fred  & J. Filipe (Eds.), Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - (Volume 1) (pp. 105–112). Institute for Systems and Technologies of Information, Control and Communication (INSTICC). https://doi.org/10.5220/0008110901050112

Chang, C.-T., Hajiyev, J., & Su, C.-R. (2017). Examining the students’ behavioral intention to use e-learning in Azerbaijan? The General Extended Technology Acceptance Model for E-learning approach. Computers & Education, 111, 128–143. https://doi.org/10.1016/j.compedu.2017.04.010

Chin, W. W. (1998). Issues and opinion on structural equation modeling. Management Information Systems,  22(1), vii-xvi.

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied multiple regression/correlation analysis for the behavioral sciences. Routledge. https://doi.org/10.4324/9780203774441

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008

Dos-Santos, M. A., Calabuig Moreno, F., Montoro Ríos, F., & Alguacil, M. (2017). Online Sport Event Consumers: Attitude, E-Quality and E-Satisfaction. Journal of Theoretical and Applied Electronic Commerce Research, 12(2), 54–70. https://doi.org/10.4067/S0718-18762017000200005

Dubey, R., Luo, Z., Gunasekaran, A., Akter, S., Hazen, B. T., & Douglas, M. A. (2018). Big data and predictive analytics in humanitarian supply chains. The International Journal of Logistics Management, 29(2), 485–512. https://doi.org/10.1108/IJLM-02-2017-0039

Dumpit, D. Z., & Fernandez, C. J. (2017). Analysis of the use of social media in Higher Education Institutions (HEIs) using the Technology Acceptance Model. International Journal of Educational Technology in Higher Education, 14(5), 1–16. https://doi.org/10.1186/s41239-017-0045-2

Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21(3), 719–734. https://doi.org/10.1007/s10796-017-9774-y

Fornell, C., & Larcker, D. F. (1981a). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39. https://doi.org/10.2307/3151312

Fornell, C., & Larcker, D. F. (1981b). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312

Francom, G. M., Schwan, A., & Nuatomue, J. N. (2021). Comparing Google Classroom and D2L Brightspace Using the Technology Acceptance Model. TechTrends, 65(1), 111–119. https://doi.org/10.1007/s11528-020-00533-0

Gallagher, J. E., Dobrosielski-Vergona, K. A., Wingard, R. G., & Williams, T. M. (2005). Web-based vs. traditional classroom instruction in gerontology: A pilot study. Journal of Dental Hygiene, 79(3), 1–10.

Garaika, H. M. (2020). Adoption of educational technology: Study on higher education. International Journal of Management, 11(1), 62–72. https://doi.org/10.34218/IJM.11.1.2020.007

Gialamas, V., Nikolopoulou, K., & Koutromanos, G. (2013). Computers & Education Student teachers ’ perceptions about the impact of internet usage on their learning and jobs. Computers & Education, 62, 1–7. https://doi.org/10.1016/j.compedu.2012.10.012

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial Least Squares Structural Equation Modeling: Rigorous Applications, Better Results and Higher Acceptance. Long Range Planning, 46(1–2), 1–12. https://doi.org/10.1016/j.lrp.2013.01.001

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203

Hair J. F. Jr., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM). European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128

Hamidi, H., & Chavoshi, A. (2018). Analysis of the essential factors for the adoption of mobile learning in higher education: A case study of students of the University of Technology. Telematics and Informatics, 35(4), 1053–1070. https://doi.org/10.1016/j.tele.2017.09.016

Hamidi, H., & Jahanshaheefard, M. (2019). Essential factors for the application of education information system using mobile learning: A case study of students of the university of technology. Telematics and Informatics, 38, 207–224. https://doi.org/10.1016/j.tele.2018.10.002

Herwin, H., Hastomo, A., Saptono, B., Ardiansyah, A. R., & Wibowo, S. E. (2021). How elementary school teachers organized online learning during the Covid-19 Pandemic? World Journal on Educational Technology: Current Issues, 13(3), 437–449. https://doi.org/10.18844/wjet.v13i3.5952

Ifinedo, P. (2016). Applying uses and gratifications theory and social influence processes to understand students’ pervasive adoption of social networking sites: Perspectives from the Americas. International Journal of Information Management, 36(2), 192–206. https://doi.org/10.1016/j.ijinfomgt.2015.11.007

Kaabachi, S., Ben Mrad, S., & Petrescu, M. (2017). Consumer initial trust toward internet-only banks in France. International Journal of Bank Marketing, 35(6), 903–924. https://doi.org/10.1108/IJBM-09-2016-0140

Kadek Suartama, I., Usman, M., Triwahyuni, E., Subiyantoro, S., Abbas, S., Umar, Hastuti, W. D., & Salehudin, M. (2020). Development of E-learning oriented inquiry learning based on character education in multimedia course. European Journal of Educational Research, 9(4), 1591–1603. https://doi.org/10.12973/EU-JER.9.4.1591

Kumar, J. A., & Bervell, B. (2019). Google Classroom for mobile learning in higher education: Modelling the initial perceptions of students. Education and Information Technologies, 24(2), 1793–1817. https://doi.org/10.1007/s10639-018-09858-z

Kurfalı, M., Arifoğlu, A., Tokdemir, G., & Paçin, Y. (2017). Adoption of e-government services in Turkey. Computers in Human Behavior, 66, 168–178. https://doi.org/10.1016/j.chb.2016.09.041

Liang, R., Guo, W., & Zhang, L. (2019). Exploring oppositional loyalty and satisfaction in firm-hosted communities in China. Internet Research, 30(2), 487–510. https://doi.org/10.1108/INTR-07-2018-0344

Macedo, I. M. (2017). Predicting the acceptance and use of information and communication technology by older adults: An empirical examination of the revised UTAUT2. Computers in Human Behavior, 75, 935–948. https://doi.org/10.1016/j.chb.2017.06.013

Mahendra, M. R., Supriansyah, & Zulherman. (2021). Development of Macromedia Flash-Based Mathematics Learning for Elementary School Students. Journal of Physics: Conference Series, 1783(1), 012006. https://doi.org/10.1088/1742-6596/1783/1/012006

Ministry Education and Culture. (2020, June 15). Panduan penyelenggaraan pembelajaran pada tahun ajaran dan tahun akademik baru di masa COVID-19 [Guidelines for the implementation of learning in the new academic year and academic year during the COVID-19 Period]. https://bit.ly/3nBF0lO

Phungsuk, R., Viriyavejakul, C., & Ratanaolarn, T. (2017). Development of a problem-based learning model via a virtual learning environment. Kasetsart Journal of Social Sciences, 38(3), 297–306. https://doi.org/10.1016/j.kjss.2017.01.001

Ravand, H., & Purya, B. (2016). Partial least squares structural equation modeling with R. Practical Assessment, Research and Evaluation, 21(1), 1–16. https://doi.org/10.7275/d2fa-qv48

Rostyawati, R., Zulherman, & Bandarsyah, D. (2021). Analytical Effectiveness using Adobe Flash in Learning Energy Source at Primary School. Journal of Physics: Conference Series, 1783(1), 012125. https://doi.org/10.1088/1742-6596/1783/1/012125

Safsouf, Y., Mansouri, K., & Poirier, F. (2020). An analysis to understand the online learners’ success in public higher education in Morocco. Journal of Information Technology Education: Research, 19, 1–26. https://doi.org/10.28945/4526

Sailin, S. N., & Mahmor, N. A. (2018). Improving student teachers’ digital pedagogy through meaningful learning activities. Malaysian Journal of Learning and Instruction, 15(2), 143–173. https://doi.org/10.32890/mjli2018.15.2.6

Salehudin, M., Zulherman, Z., Arifin, A., & Napitupulu, D. (2021). Extending indonesia government policy for e-learning and social media usage. Pegem Journal of Education and Instruction/ Pegem Egitim ve Ogretim Dergisi, 11(2), 14–26. https://doi.org/10.14527/pegegog.2021.00

Salloum, S. A., Al-Emran, M., Shaalan, K., & Tarhini, A. (2019). Factors affecting the E-learning acceptance: A case study from UAE. Education and Information Technologies, 24(1), 509–530. https://doi.org/10.1007/s10639-018-9786-3

Shaharanee, I. N. M., Jamil, J. M., & Rodzi, A. S. S. M. (2016). The application of Google Classroom as a tool for teaching and learning. Journal of Telecommunication, Electronic and Computer Engineering, 8(10), 5–8.

Skvarciany, V., & Jurevičienė, D. (2018). Factors Influencing Individual Customers Trust in Internet Banking: Case of Baltic States. Sustainability, 10(12), 4809. https://doi.org/10.3390/su10124809

Tan, P. J. B. (2013). Applying the UTAUT to understand factors affecting the use of english e-learning websites in Taiwan. SAGE Open, 3(4). https://doi.org/10.1177/2158244013503837

United Nations Educational, Scientific, and Cultural Organization. (2020). UNESCO’s “Next Normal” campaign. https://bit.ly/2YUlbvv

United Nations Educational, Scientific, and Cultural Organization. (2020). COVID-19: How the UNESCO Global Education Coalition is tackling the biggest learning disruption in history. https://bit.ly/3AdPxah

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221–232. https://doi.org/10.1016/j.chb.2016.10.028

Xiu, Y., Moore, M. E., Thompson, P., & French, D. P. (2019). Student Perceptions of Lecture-Capture Video to Facilitate Learning in a Flipped Classroom. TechTrends, 63(4), 369–375. https://doi.org/10.1007/s11528-018-0293-6

Zhao, D., & Hu, W. (2017). Determinants of public trust in government: empirical evidence from urban China. International Review of Administrative Sciences, 83(2), 358–377. https://doi.org/10.1177/0020852315582136

Zulherman, Z., Nuryana, Z., Pangarso, A., & Zain, F. M. (2021). Factor of zoom cloud meetings (ZCM): Technology adoption on the pandemic covid-19. International Journal of Evaluation and Research in Education, 10(3), 816–825. https://doi.org/10.11591/ijere.v10i3.21726

...