AFFECTING FACTORS OF STUDENTS’ SATISFACTION ON E-LEARNING AND UNIVERSITY BRAND IMAGE IN YANGON, MYANMAR DURING COVID-19
Keywords:
E-Learning, Student Satisfaction, University Brand Image, Marketing Innovation, Covid-19Abstract
This research aims to determining factors affecting students’ satisfaction on e-learning and university brand image during covid-19 pandemic in the top ten private universities in Yangon, Myanmar. Population and sample size are 500 students who have been experiencing e-learning at least one semester at the top ten private universities in Yangon, Myanmar. The sample techniques used were judgmental, quota, convenience and snowball sampling. Before collecting the data, the results of index of item objective congruence (IOC) and Cronbach’s Alpha coefficient of 50 samples were reserved. After the data collection, confirmatory factor analysis (CFA) and structural equation modeling (SEM) approach were used to measure data’s validity, reliability and goodness of fit. The results showed that student satisfaction was affected by e-learning system quality, e-learning instructor and course materials quality, administrative and support service quality, and marketing innovation towards university brand image. In contrary, information quality and interaction in e-learning environment had no effect on student satisfaction. Academic practitioners and universities can promote advantages of e-learning system to create better students’ satisfaction and ensure the good image of the university.
References
Almaiah M.A. , & Alismaiel, O. A. (2019). Examination of factors influencing the use of mobile learning system: An empirical study. Education and Information Technologies, 24(1), 885–909.
Alves, H., & Raposo, M. (2010). The influence of university image on student behaviour. International Journal of Educational Management, 24(1), 73-85.
Amir, M. K. (2012). Determinants of students’ satisfaction with university portal services in Jordan [Master dissertation, Addis Ababa University]. Ethiopia.
Baumgartner, H., & Homburg, C. (1996). Applications of Structural Equation Modeling in Marketing and Consumer Research: a review. International Journal of Research in Marketing, 13(2), 139-161.
Boyd, P. W. (2008). Analyzing students’ perceptions of their learning in online and hybrid first-year composition courses. Computers and Composition, 25(2), 224-243.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297-334.
Daultani, Y., Goswami, M., Kumar, A., & Pratap, S. (2021). Perceived outcomes of e-learning: identifying key attributes affecting user satisfaction in higher education institutes. Measuring Business Excellence, 25(2), 216-229.
Davies, G., Chun, R., Da-Silva, R., & Roper, S. (2003). Corporate reputation and competitiveness. Corporate Communications: An International Journal, 8(2), 148-149.
Ei Su, C., Thae Su, M., Li., C. K., & Liu, L. (2020). An Exploration of Online Learning Readiness for University Students in Myanmar. Journal of Graduate School, Buriram Rajabhat University, 8(2), 109-127.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Gorla, N., & Somers, T. M. (2014). The impact of IT outsourcing on information systems success. Information & Management, 51(3), 320–335.
Gurkut, C., & Nat, M. C. (2017). Important Factors Affecting Student Information System Quality and Satisfaction. Eurasia Journal of Mathematics, Science and Technology Education, 14(3).
Hair, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate Data Analysis (6th ed.). Pearson Education.
Hassanzadeh, A., Kanaani, F., & Elahi, S. (2012). A model for measuring e-learning systems success in universities. Expert Systems with Applications, 39, 10959–10966.
Hirumi, A. (2002). The Design and Sequencing of eLearning Interactions: A Grounded Approach. International Journal on E-Learning, 1.
Khaing, S.S., Win. A., Aung T. N. (2016). SWOT Analysis of E-learning Course Operation in Higher Education (Case Study: University of Technology, Yatanarpon Cyber City). Advances in Intelligent Systems and Computation, 338. Springer.
Majed, M. S. O. A. (2013). The impact of system quality in e-learning system. Journal of Computer Science and Information Technology, 1(2), 14.
Marzo Navarro, M., Pedraja Iglesias, M., & Rivera Torres, P. (2005). A new management element for universities: satisfaction with the offered courses. International Journal of Educational Management, 19(6), 505-526.
Michnik, J., & Lo, M. (2007). The assessment of the information quality with the aid of multiple criteria analysis. European Journal of Operational Research, 195(3), 850-856.
OECD (2005), Oslo Manual, Guidelines for Collecting and Interpreting Innovation Data. OECD.
Pedroso, R., Zanetello, L., Guimaraes, L., Pettenon, M., Goncalves, V., Scherer, J., Kessler, F., & Pechansky, F. (2016). Confirmatory factor analysis (CFA) of the crack use relapse scale (CURS). Archives of Clinical Psychiatry, 43(3), 37-40.
Pham, L., Limbu, Y. B., Bui, T. K., Nguyen, H. T., & Pham, H. T. (2019). Does e-learning service quality influence e-learning student satisfaction and loyalty? Evidence from Vietnam. International Journal of Educational Technology in Higher Education, 16(7), 1-26.
Rosenberg, M. J. (2001). E-learning: Strategies for delivering knowledge in the digital age. McGraw Hill.
Shehzadi, S., Nisar, Q. A., Hussain, M. S., Basheer, M. F., Hameed, W. U., & Chaudhry, N. I. (2021). The role of digital learning toward students' satisfaction and university brand image at educational institutes of Pakistan: a post-effect of COVID-19. Asian Education and Development Studies, 10(2), 276-294.
Sica, C. & Ghisi, M. (2007). The Italian versions of the Beck Anxiety Inventory and the Beck Depression Inventory-II: Psychometric properties and discriminant power. In M.A. Lange (Ed.), Leading - Edge Psychological Tests and Testing Research (pp. 27-50). Nova.
Sims, R., Dobbs, G., & Hand, T. (2002). Enhancing quality in online learning: scaffolding planning and design through proactive evaluation. Distance Education, 23(2), 135– 148.
Soper, D. S. (2022). A-priori Sample Size Calculator for Structural Equation Models [Software]. www.danielsoper.com/statcalc/default.aspx
Stefanovic, D., Drapsin, M., Nikolic, J., Scepanovic, D., Radjo, I., & Drid, P. (2011). Empirical study of student satisfaction in e-learning system environment. Technics Technologies Education Management, 6(4), 1152-1164.
Veer Ramjeawon, P., & Rowley, J. (2018). Knowledge management in higher education institutions in Mauritius. International Journal of Educational Management, 32(7), 1319–1332.
Wong, W. T., & Huang, N. T. N. (2011). The Effects of E-Learning System Service Quality and Users' Acceptance on Organizational Learning. International Journal of Business and Information, 6(2), 205-225.
Wu, J. H., & Wang, Y. M. (2006). Measuring KMS success: A respecification of the DeLone and McLean’s model. Information and Management, 43(6), 728–739.
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