Improving Actual E-Learning Usage: Evidence from Indonesia

Alwan Sri Kustono


This research project aims to determine the predicting factors that influence the successful use of e-learning in Indonesia, in particular, the utilization of e-learning as a learning model during the Covid-19 pandemic. The e-learning method is a learning model that does not require face-to-face contact, so it fits the physical distancing needs imposed to limit spread of the virus. The method of data collection here employed a survey approach, while testing relied on partial least squares using SmartPLS v3.3.2 software. The research sample was 357 accounting lecturers. Data were collected using Google Forms. The results showed that the success of e-learning was influenced by the ease of use of the platform. The ease of the e-learning platform is influenced by e-learning literacy and organizational support. In the path analysis, actual use is affected by intention, ease of use affects intention, and two exogenous variables affect the ease of use. Different from what was predicted, usefulness is not a primary factor for use. In pandemic conditions, lecturers tend to call on easy-to-use devices with emergency learning methods, even though their utility is not yet optimal. Higher education institutions can take advantage of research results to increase the success and achievement of learning outcomes. Lecturers and students increase e-learning adoption if supported by organizational policies and increased literacy related to e-learning. The uniqueness of this research  relates to selecting initial antecedent variables that can be followed up with practical actions to increase the success of e-learning, thus providing scientific and practical novelty.


Keywords: e-learning outcome, e-learning literacy, organizational support, ease of use, usefulness, intention to usage, actual usage.


Full Text:



SUN P.-C., TSAI R. J., FINGER G., CHEN Y.-Y., and YEH D. What drives successful e-learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 2008, 50(4): 1183-1202.

WU J. H., TENNYSON R. D., and HSIA T. L. A study of student satisfaction in a blended e-learning system environment. Computers and Education, 2010, 55(1): 155-164. 10.1016/j.compedu.2009.12.012

ADEWOLE-ODISHA E. An attitude of students towards e-learning in South-West Nigerian Universities: An application of Technology Acceptance Model. Library Philosophy and Practice, 2014, 1.

DAVIS F. D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 1989, 13(3): 319-140.

LE O. T. T. and CAO Q. M. Examining the Technology Acceptance Model using cloud-based accounting software of Vietnamese enterprises. Management Science Letters, 2020, 10(12): 2781-2788.

DAVIS F., BAGOZZI R. P., and WARSHAW P. R. User acceptance of computer technology: a comparison of two theoretical models. Management Science, 1989, 35(8): 982-1003.

IGBARIA M. and IIVARI J. The effects of self-efficacy on computer usage. Omega, 1995, 23(6): 587-605.

KUSTONO A. S. and VALENCIA Z. G. How the effectiveness of knowledge sharing affects enterprise resource-planning system case in East Java—Indonesia. Advanced Science Letters, 2017, 23(5): 4295-4297.

KUSTONO A. S., NANGGALA A. Y. A., and MAS'UD I. Determinants of the use of e-wallet for transaction payment among college students. Journal of Economics, Business, & Accountancy Ventura, 2020, 23(1): 85–95.

SANTIKA I. W. and YADNYA I. P. Analysis of the Technology Acceptance Model of the use of e-commerce in handicraft SMEs in Gianyar. Proceeding Seminar Nasional AIMI, 2017, pp. 255–264.

LEE J.-W., & MENDLINGER S. Perceived self-efficacy and its effect on online learning acceptance and student satisfaction. Journal of Service Science and Management, 2011, 4(3): 243–252.

MANSYUR M., RAHAMMA T., and FATIMA J. M. Students' visual media literacy skills and the success of learning information and communication technology (ICT) at SMP Negeri 11 Pare-Pare. Jurnal Komunikasi KAREBA, 2013, 2(4): 379–385.

DWIUTAMI L., & WARDI T. D. Self-efficacy and information literacy ability in high school teachers. Journal of Research and Measurement in Psychology, 2015, 4(2): 65–73.

SAADÉ R. G., NEBEBE F., and TAN W. Viability of the Technology Acceptance Model in multimedia learning environments: a comparative study. Interdisciplinary Journal of e-Skills and Lifelong Learning, 2007, 3: 175–184.

AL-AZAWEI A., & LUNDQVIST K. Learner differences in perceived satisfaction of online learning: an extension to the Technology Acceptance Model in an Arabic sample. Electronic Journal of e-Learning, 2015, 13(5): 408–426.

HAFFAR M., AL-KARAGHOULI W., DJEBARNI R., and GBADAMOSI G. Organisational culture, and TQM implementation: investigating the mediating influences of multidimensional employee readiness for change. Total Quality Management and Business Excellence, 2019, 30(11–12): 1367–1388.

FATDINA. The role of organizational support perceived by employees as a mediator of procedural justice's effect on organizational citizenship behavior. Jurnal Psikologi, 2009, 36(1): 1–17.

HANDAYANI R. Analysis of factors affecting acceptance of the use of personal computers with the Technology Acceptance Model. Jurnal Riset Manajemen dan Akuntansi, 2010, 1: 55–66.

AL KURDI B., ALSHURIDEH M., SALLOUM S. A., OBEIDAT Z. M., and AL-DWEERI R. M. An Empirical Investigation into examining factors influencing university students' behavior towards e-learning acceptance using SEM approach. International Journal of Interactive Mobile Technologies, 2020, 14(2): 19-41.

LEGOWO N., ABDURAHMAN E., HERWIDIANA K. I., and BUDIASTUTI D. The influence of instructor readiness, its capability, support of LMS Content, and their implications on e-learning effectiveness in a corporate university of BUMN. International Journal of Recent Technology and Engineering, 2019, 8(3): 54–59.

AL-HADI S. The influences of government support in accepting the information technology in public organization culture. International Journal of Business and Social Science, 2014, 5(5): 118–124.

FIYAH N., MAYANGKY N. A., HADIANTI S., and RIANA D. Analysis of Technology Acceptance Model in Electronic Trading Platform Applications Among Students. Jurnal Teknik Informatika, 2019, 12(1): 59–68.

ANDARWATI M., & JATMIKA D. Analysis of the effect of the quality of accounting information systems on technology acceptance in the same sector using the TAM model approach. Seminar Nasional Sistem Informasi, 2017.

CHEN S. C., LI S.-H., and LI C.-Y. Recent related research in technology Acceptance Model: a literature review. Australian Journal of Business and Management Research, 2011, 1(9): 124–127.

NANGGALA A. Y. A. Use of fintech for payment: an approach to Technology Acceptance Model Modified. Journal of Contemporary Information Technology, Management, and Accounting, 2020, 1(1): 1–8.

TAJUDEEN S. A., BASHA M. K., MICHAEL F. O., and MUKTHAR A. L. Determinant of mobile devices acceptance for learning among students in developing country. Malaysia Online Journal of Educational Technology, 2013, 1(3): 17–29.

HO K. F., HO C. H., and CHUNG M. H. Theoretical Integration of user satisfaction and technology acceptance of the nursing process information system. PLoS ONE, 2019, 14(6): 1–14.

KUSTONO A. S. Use of internet banking for payment of tuition fees. International Journal of Innovation, Creativity, and Change, 2020, 14(5): 292-310.

LAI P. C. The literature review of technology adoption models and theories for the novelty technology. Journal of Information Systems and Technology Management, 2017, 14(1): 21–38.

YUNIARTI V., & EKOWATI W. H. Factors affecting interest in using financial technology peer to peer lending. Journal of Chemical Information and Modeling, 2019, 53(9): 1689–1699.

SUANA W. Students' internet access, internet self-efficacy, and internet for learning physics: gender and grade differences. Journal of Technology and Science Education, 2018, 8(4): 281–290.

NAGY J. T. Evaluation of online video usage and Learning Satisfaction: An Extension of the Technology Acceptance Model. International Review of Research in Open and Distance Learning, 2018, 19(1): 160–185.

LEE Y. H., KOZAR K. A., and LARSEN K. R. T. The technology acceptance model: past, present, future. Communications of the Association for Information Systems, 2003, 12(50): 752-780.

YUWANA A. M., & KUSTONO A. S. Why is User’s Expertise Important for Implementation of Regional Asset Information Systems: Case in Indonesia. International Journal of Science and Research, 2017, 6(7): 377–379.

CIGDEM H., & OZTURK M. Factors affecting students' behavioral intention to use LMS at a Turkish post-secondary vocational school. International Review of Research in Open and Distance Learning, 2016, 17(3): 276–295.

KAO C. P., LIN K. Y., and CHIEN H. M. Predicting Teachers' behavioral intentions regarding web-based professional development by the theory of planned behavior. Eurasia Journal of Mathematics, Science and Technology Education, 2018, 14(5): 1887–1897.

MEHTA A. Technology acceptance of e-learning within a blended vocational course in West Africa. Proceedings of the International Conference e-Learning 2014. Multi Conference on Computer Science and Information Systems, Lisbon, 2014, pp. 324–328.

PHAM C. H., VU N. H., and TRAN G. T. H. The role of e-learning service quality and e-trust on e-loyalty. Management Science Letters, 2020, 10(12): 2741–2750.

NAUJOKAITIENE J., TERESEVICIENE M., and ZYDZIUNAITE V. Organizational support for employee engagement in technology-enhanced learning. SAGE Open, 2015, 5(4): 1-9.

KUSTONO A. S. How total quality management mediates antecedent variables of employee performance? The Journal of Asian Finance, Economics, and Business, 2020, 7(12): 523–534.

TARHINI A., HONE K., and LIU X. User acceptance towards web-based learning systems: investigating the role of social, organizational, and individual factors in European higher education. Procedia Computer Science, 2013, 17: 189–197.

GALY E., DOWNEY C., and JOHNSON J. The effect of using e-learning tools in online and campus-based classrooms on student performance. Journal of Information Technology Education: Research, 2011, 10(1): 209–230.

ABDULLAH F., & WARD R. Developing a general extended Technology Acceptance Model for e-learning (GETAMEL) by analyzing commonly used external factors. Computers in Human Behavior, 2016, 56: 238–256.

WINARTO P. M., & TAMBUNAN A. P. Students' acceptance towards blended learning implementation. Journal of Physics: Conference Series, 2019, 1280(3): 032031.

RADIF, M., & MOHAMMED, N. A. Computer science teacher’s perception and needs towards E-learning in Iraq. Journal of Southwest Jiaotong University, 2019, 54(5).

ALRUBAIE, S.A., ALRUBAIE, M.A., and HASSOON, I.M. The Role of Activating Electronic Training in Increasing Efficiency of Training Process. Journal of Southwest Jiaotong University, 2020, 55(1).


  • There are currently no refbacks.