Effectiveness of E-Learning Management During Covid- 19 Pandemic in Indonesia
Keywords:
e-learning management, Delone and Mclean Model, Virtual Learning Effectiveness, covid-19
Abstract
This research aims to analyze the effectiveness of e-learning management during the Covid-19 pandemic in Indonesia with Delone and Mclean Model and Virtual Learning Effectiveness approach. The research method used is quantitative, with a sample of students in Indonesia. The data collection method uses an online questionnaire sent by email and an actual phone number. The data analysis method uses structural equation modeling based on Partial Least Square (PLS). This study found empirical evidence that technological factors, namely the quality of the system and the quality of information, and psychological factors, namely self-efficacy and human factors that are the services of lecturers, have a significant effect on user perception and user satisfaction. User perception and user satisfaction have a significant effect on the effectiveness of e-learning. This study develops research models DM and VLE. Future research planned to extend this research model into an integrated model structure that could help define factors in the performance of e-learning systems and important e-learning success factors, or superior to conventional face-to-face learning systems
References
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Bailey, J. E., Pearson, S. W., Science, S. M., and May, N. (1983). Development of a Tool for Measuring and Analyzing Computer User Satisfaction. Manage. Sci. Vol. 29(5): 530–545.
Bandura, A. (1994), “Self-efficacy”, in Ramachaudran, V.S. (Ed.), Encyclopedia of Human Behavior, Academic Press, New York, NY, pp. 71-81.
Bhuasiri, W., Xaymoungkhoun, O., Zo, H., Jeung, J., & Ciganek, A. P. (2012). Computers & Education Critical success factors for e-learning in developing countries: A comparative analysis between ICT experts and faculty. Computers & Education, 58(2), 843–855. https://doi.org/10.1016/j.compedu.2011.10.010
Ching-Ter Chang., Su C.-R. & Hajiyev J., (2017). Examining the students’ behavioral intention to use e-learning in Azerbaijan? The General Extended Technology Acceptance Model for Elearning approach, Computers & Education (2017), doi: 10.1016/j.compedu.2017.04.010.
Chin, W.W. (1998), “The partial least squares approach to structural equation modeling”, in Marcoulides, G.A. (Ed.), Modern Methods for Business Research, Lawrence Erlbaum Associates, Mahwah, NJ, pp. 295-336.
Chiu, C.-M. and Wang, E.T.G. (2008), “Understanding web-based learning continuance intention:
the role of subjective task value”, Information & Management, Vol. 45, pp. 194-201.
Cidral, W. A., Oliveira, T., Felice, M. Di, & Aparicio, M. (2018). E-learning success determinants: Brazilian empirical study. Computers & Education. https://doi.org/10.1016/j.compedu.2017.12.001
Compeau, D.R. and Higgins, C.A. (1995), “Computer self-efficacy: development of a measure and initial test”, MIS Quarterly, Vol. 19 No. 2, pp. 189-211.
DeLone, W. H., McLean, E. R. 1992. Information Systems Success: The Quest for the Dependent Variable. Inf. Syst. Res., vol. 3, no. 4,:60–95.
DeLone, W. H., McLean, E. R. 2003. The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. J. Manag. Inf. Syst. Vol. 19(4): 9–30.
Eom, S. B., & Eom, S. B. (2012). business education Effects of LMS, self-efficacy, and self- regulated learning on LMS effectiveness in business education. https://doi.org/10.1108/18363261211281744
Eom, S.B., Ashill, N. and Wen, H.J. (2006), “The determinants of students’ perceived learning outcome and satisfaction in university online education: an empirical investigation”, Decision Sciences Journal of Innovative Education, Vol. 4 No. 2, pp. 215-36.
Falk, R.F. and Miller, N.B. (1992), A Primer for Soft Modeling, The University of Akron Press, Akron, OH
Fornell, C.R. and Bookstein, F.L. (1982), “A comparative analysis of two structural equation models: LISREL and PLS applied to market data”, in Fornell, C. (Ed.), A Second Generation of Multivariate Analysis, Praeger, New York, NY, pp. 289-394.
Fornell, C.R. and Larcker, D. (1981), “Evaluating structural equation models with unobservable variables and measurement error”, Journal of Marketing Research, Vol. 18 No. 1, pp. 39- 50.
Furukawa, M., Minami, A. 2013. A Study on the ‘Flexibility’ of Information Systems (Part 1): Why Do They Need to Be Flexible?. Int. J. Bus. Manag. Vol. 8(20): 48–61.
Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. (2010), Multivariate Data Analysis, 7th ed., Prentice-Hall, Upper Saddle River, NJ
Holsapple, C.W. and Lee-Post, A. (2006), “Defining, assessing, and promoting e-learning success: an information systems perspective”, Decision Sciences Journal of Innovative Education, Vol. 4 No. 1, pp. 67-85
Hong, J., Tai, K., Hwang, M., Kuo, Y., & Chen, J. (2017). Computers in Human Behavior Internet cognitive failure relevant to users ’ satisfaction with content and interface design to reflect continuance intention to use a government e-learning system. Computers in Human Behavior, 66, 353–362. https://doi.org/10.1016/j.chb.2016.08.044
Iivari, J. 2005. An Empirical Test of the Model of Information System Success. DATA BASE Adv. Inf. Syst. Vol. 36(2): 8–27.
Johnson, R.D., Hornik, S. and Salas, E. (2008), “An empirical examination of factors contributing to the creation of successful e-learning environments”, International Journal of Human-Computer Studies, Vol. 66 No. 5, pp. 356-69.
Kerta, J. M. and Suryawan, A. D. 2013. Analysis of information System Implementation in Binus University using Delone and Mclean Information System Success Model and Cobit Framework. International Journal of Communication & Information Technology (CommIT). Vol. 7(1): 13–17.
King, F.B., Harner, M. and Brown, S.W. (2000), “Self-regulatory behavior influences in distance earning”, International Journal of Instructional Media, Vol. 27 No. 2, pp. 147-56.
Landry, B.J.L., Griffeth, R. and Hartman, S. (2006), “Measuring student perceptions of blackboard using the technology acceptance model”, Decision Sciences Journal of Innovative Education, Vol. 4 No. 1, pp. 87-99.
Leidner, D.E. and Jarvenpaa, S.L. (1995), “The use of information technology to enhance management school education: a theoretical view”, MIS Quarterly, Vol. 19 No. 3, pp. 265- 91.
Nunnally, J.C. and Bernstein, I.H. (1994), Psychometric Theory, 3rd ed., McGraw-Hill, New York, NY
Piccoli, G., Ahmad, R. and Ives, B. (2001), “Web-based virtual learning environments: a research framework and a preliminary assessment of effectiveness in basic IT skills training”, MIS Quarterly, Vol. 25 No. 4, pp. 401-26
Rai, A., Lang, S.S. and Welker, R.B. (2002), “Assessing the validity of IS success models: an empirical test and theoretical analysis”, Information Systems Research, Vol. 13 No. 1, pp. 50-69.
Sean B. Eom, (2012) "Effects of LMS, self‐efficacy, and self‐regulated learning on LMS effectiveness in business education", Journal of International Education in Business, Vol. 5 Issue: 2, pp.129-144, https:// doi.org/10.1108/18363261211281744
Seddon, P. B. 1997. A Respecification and Extension of the Delone and Mclean Models of IS success.
Straub, D., Boudreau, M.-C. and Gefen, D. (2004), “Validation guidelines for IS positivist research”, Communications of the Association for Information Systems, Vol. 13 No. 24, pp. 380-427.
Simmering, M.J., Posey, C. and Piccoli, G. (2009), “Computer self-efficacy and motivation to learn in a self-directed online course”, Decision Sciences Journal of Innovative Education, Vol. 7 No. 1, pp. 99-121.
Wang, T. H. (2010). Web-based dynamic assessment: Taking assessment as teaching and learning strategy for improving students’ e-Learning effectiveness. Computers and Education, 54(4), 1157–1166. https://doi.org/10.1016/j.compedu.2009.11.001
Wang, Y.-S., Wang, H.-Y. and Shee, D.Y. (2007), “Measuring e-learning systems success in an organizational context: scale development and validation”, Computers in Human Behavior, Vol. 23 No. 4, pp. 1792-808
Womble, J. (2008), “E-learning: the relationship among learner satisfaction, self-efficacy, and usefulness”, The Business Review, Vol. 10 No. 1, pp. 182-8.
Younis, A., Cater-steel, A., & Soar, J. (2016). Computers in Human Behavior Determinants of perceived usefulness of e-learning systems. Computers in Human Behavior, 64, 843–858. https://doi.org/10.1016/j.chb.2016.07.065
Zimmerman, B.J. (1995), “Self-efficacy and educational development”, in Bandura, A. (Ed.), Self Efficacy and Changing Society, Cambridge University Press, New York, NY, pp. 202-31.
Zimmerman, B.J. (1989), “A social cognitive view of self-regulated academic learning”, Journal of Educational Psychology, Vol. 81 No. 3, pp. 329-39
