The Effect of Overall Quality and Self-Efficacy on Learners' Flow and Satisfaction in Post-Pandemic Distance Learning
DOI:
https://doi.org/10.59188/eduvest.v4i11.1399Keywords:
Distance Learning, Flow, Satisfaction, Overall Quality, Self-EfficacyAbstract
The objective of this study is to determine the effect of overall quality and self-efficacy on the flow and satisfaction of distance learning learners in the post-pandemic period in public sector organizations. Research data were collected through an online survey of distance learning participants in public sector organizations. A total of 701 data were analyzed. The data analysis method used was CB-SEM using Lisrel 8.80. This study found that system quality, information quality, and flow significantly and positively affected the satisfaction of distance learning participants. Self-efficacy, information quality, and service quality also have a positive and significant effect on the satisfaction of distance learning participants through the mediation of flow. Many previous studies have explored the effect of overall quality on online learning satisfaction in school or universities. However, this study is different in that it focuses on the context of public sector organizations by adding self-efficacy variables as internal factors of learners and including flow variables as mediators, considering that learners and instructors are not in the same location during distance learning. According to the findings from the conducted research, this study recommends that education and training organizers in the public sector can pay attention to factors that affect learner satisfaction in distance learning which include self-efficacy, overall learning quality, and flow in learning.
References
Aldholay, A., Abdullah, Z., Isaac, O., & Mutahar, A. M. (2019). Perspective of Yemeni students on use of online learning: Extending the information sys-tems success model with transformational leadership and compatibility. In-formation Technology & People, 33(1), 106–128. https://doi.org/10.1108/ITP-02-2018-0095
Aldholay, A., Isaac, O., Abdullah, Z., Abdulsalam, R., & Al-Shibami, A. H. (2018). An extension of Delone and McLean IS success model with self-efficacy: Online learning usage in Yemen. The International Journal of In-formation and Learning Technology, 35(4), 285–304. https://doi.org/10.1108/IJILT-11-2017-0116
Alqurashi, E. (2016). Self-Efficacy In Online Learning Environments: A Litera-ture Review. Contemporary Issues in Education Research (CIER), 9(1), 45–52. https://doi.org/10.19030/cier.v9i1.9549
Alyoussef, I. Y., & Omer, O. M. A. (2023). Investigating Student Satisfaction and Adoption of Technology-Enhanced Learning to Improve Educational Out-comes in Saudi Higher Education. Sustainability, 15(19), 14617. https://doi.org/10.3390/su151914617
Balaban, I., Mu, E., & Divjak, B. (2013). Development of an electronic Portfolio system success model: An information systems approach. Computers & Ed-ucation, 60(1), 396–411. https://doi.org/10.1016/j.compedu.2012.06.013
Cheng, Y.-M. (2014). Extending the expectation-confirmation model with quality and flow to explore nurses’ continued blended e-learning intention. Infor-mation Technology & People, 27(3), 230–258. https://doi.org/10.1108/ITP-01-2013-0024
Cheng, Y.-M. (2020). Students’ satisfaction and continuance intention of the cloud-based e-learning system: Roles of interactivity and course quality fac-tors. Education + Training, 62(9), 1037–1059. https://doi.org/10.1108/ET-10-2019-0245
Cheng, Y.-M. (2021). Investigating medical professionals’ continuance intention of the cloud-based e-learning system: An extension of expectation–confirmation model with flow theory. Journal of Enterprise Information Management, 34(4), 1169–1202. https://doi.org/10.1108/JEIM-12-2019-0401
Eom, S. B. (2012). Effects of LMS, self-efficacy, and self-regulated learning on LMS effectiveness in business education. Journal of International Education in Business, 5(2), 129-144. doi:https://doi.org/10.1108/18363261211281744
Fornell, C., & Larcker, D. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Re-search (18:1), 39–50
Goh, T.-T., & Yang, B. (2021). The role of e-engagement and flow on the con-tinuance with a learning management system in a blended learning envi-ronment. International Journal of Educational Technology in Higher Educa-tion, 18(1), 49. https://doi.org/10.1186/s41239-021-00285-8
Hair, J. F. (Ed.). (2014). Multivariate data analysis (7. ed., Pearson new internat. ed). Pearson.
Hettiarachchi, S., Damayanthi, B., Heenkenda, S., Dissanayake, D., Ranagalage, M., & Ananda, L. (2021). Student Satisfaction with Online Learning during the COVID-19 Pandemic: A Study at State Universities in Sri Lanka. Sus-tainability, 13(21), 11749. https://doi.org/10.3390/su132111749
Hongsuchon, T., Emary, I. M. M. E., Hariguna, T., & Qhal, E. M. A. (2022). As-sessing the Impact of Online-Learning Effectiveness and Benefits in Knowledge Management, the Antecedent of Online-Learning Strategies and Motivations: An Empirical Study. Sustainability, 14(5), 2570. https://doi.org/10.3390/su14052570
Huang, L.-C., Shiau, W.-L., & Lin, Y.-H. (2017). What factors satisfy e-book store customers? Development of a model to evaluate e-book user behavior and satisfaction. Internet Research, 27(3), 563–585. https://doi.org/10.1108/IntR-05-2016-0142
Huang, M.-H. (2003). Designing website attributes to induce experiential encoun-ters. Computers in Human Behavior, 19(4), 425–442. https://doi.org/10.1016/S0747-5632(02)00080-8
Huang, X., & Zhi, H. (2023). Factors Influencing Students’ Continuance Usage Intention with Virtual Classroom during the COVID-19 Pandemic: An Em-pirical Study. Sustainability, 15(5), 4420. https://doi.org/10.3390/su15054420
Joo, Y. J., Joung, S., & Kim, E. K. (2012). Structural Relationships among E-learners’ Sense of Presence, Usage, Flow, Satisfaction, and Persistence. Journal of Educational Technology & Society, 16(2), 310-324.
Jung, J.-H., & Shin, J.-I. (2021). Assessment of University Students on Online Remote Learning during COVID-19 Pandemic in Korea: An Empirical Study. Sustainability, 13(19), 10821. https://doi.org/10.3390/su131910821
Kim, S.-H., & Park, S. (2021). Influence of learning flow and distance e-learning satisfaction on learning outcomes and the moderated mediation effect of so-cial-evaluative anxiety in nursing college students during the COVID-19 pandemic: A cross-sectional study. Nurse Education in Practice, 56, 103197. https://doi.org/10.1016/j.nepr.2021.103197
Kreitner, R., & Kinicki, A. (2013). Organizational behavior (10th ed). McGraw-Hill/Irwin.
Lu, Y., Wang, B., & Lu, Y. (2019). Understanding Key Drivers Of Mooc Satis-faction And Continuance Intention To Use. 20(2). Journal of Electronic Commerce Research, 20(2), 105-117.
Maqableh, M., & Alia, M. (2021). Evaluation online learning of undergraduate students under lockdown amidst COVID-19 Pandemic: The online learning experience and students’ satisfaction. Children and Youth Services Review, 128, 106160. https://doi.org/10.1016/j.childyouth.2021.106160
Martins, J., Branco, F., Gonçalves, R., Au-Yong-Oliveira, M., Oliveira, T., Naranjo-Zolotov, M., & Cruz-Jesus, F. (2019). Assessing the success behind the use of education management information systems in higher education. Telematics and Informatics, 38, 182–193. https://doi.org/10.1016/j.tele.2018.10.001
Petter, S., & McLean, E. R. (2009). A meta-analytic assessment of the DeLone and McLean IS success model: An examination of IS success at the individ-ual level. Information & Management, 46(3), 159–166. https://doi.org/10.1016/j.im.2008.12.006
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 loy-alty? Evidence from Vietnam. International Journal of Educational Tech-nology in Higher Education, 16(1), 7. https://doi.org/10.1186/s41239-019-0136-3
Prasetyo, Y. T., Ong, A. K. S., Concepcion, G. K. F., Navata, F. M. B., Robles, R. A. V., Tomagos, I. J. T., Young, M. N., Diaz, J. F. T., Nadlifatin, R., & Redi, A. A. N. P. (2021). Determining Factors Affecting Acceptance of E-Learning Platforms during the COVID-19 Pandemic: Integrating Extended Technology Acceptance Model and DeLone & McLean IS Success Model. Sustainability, 13(15), 8365. https://doi.org/10.3390/su13158365
Salam, M., & Farooq, M. S. (2020). Does sociability quality of web-based col-laborative learning information system influence students’ satisfaction and system usage? International Journal of Educational Technology in Higher Education, 17(1), 26. https://doi.org/10.1186/s41239-020-00189-z
Shahzad, A., Hassan, R., Aremu, A. Y., Hussain, A., & Lodhi, R. N. (2021). Ef-fects of COVID-19 in E-learning on higher education institution students: The group comparison between male and female. Quality & Quantity, 55(3), 805–826. https://doi.org/10.1007/s11135-020-01028-z
Shim, M., & Jo, H. S. (2020). What quality factors matter in enhancing the per-ceived benefits of online health information sites? Application of the updat-ed DeLone and McLean Information Systems Success Model. International Journal of Medical Informatics, 137, 104093. https://doi.org/10.1016/j.ijmedinf.2020.104093
Su, C., & Guo, Y. (2021). Factors impacting university students’ online learning experiences during the COVID ‐19 epidemic. Journal of Computer Assisted Learning, 37(6), 1578–1590. https://doi.org/10.1111/jcal.12555
Tas, Y. (2016). The contribution of perceived classroom learning environment and motivation to student engagement in science. European Journal of Psy-chology of Education, 31(4), 557–577. https://doi.org/10.1007/s10212-016-0303-z
Wang, T., Manta, O., & Zhang, Y. (2023). The Relationship Between Learning Motivation and Online Learning Performance: The Mediating Role of Aca-demic Self-Efficacy and Flow Experience. International Journal of Emerg-ing Technologies in Learning (iJET), 18(23), 27–38. https://doi.org/10.3991/ijet.v18i23.43977
Xiao, Q., & Li, X. (2021). Exploring the Antecedents of Online Learning Satis-faction: Role of Flow and Comparison Between use Contexts. International Journal Of Computers Communications & Control, 16(6). https://doi.org/10.15837/ijccc.2021.6.4398
Zhao, Y. (Audrey), Bandyopadhyay, K., & Bandyopadhyay, S. (2020). Evaluat-ing Complex Online Technology-enabled Course Delivery: A Contextual-ized View of a Decomposed IS Success Model. Communications of the As-sociation for Information Systems, 209–229. https://doi.org/10.17705/1CAIS.04609
Zimmerman, W. A., & Kulikowich, J. M. (2016). Online Learning Self-Efficacy in Students With and Without Online Learning Experience. American Jour-nal of Distance Education, 30(3), 180–191. https://doi.org/10.1080/08923647.2016.1193801
Published
Issue
Section
License
Copyright (c) 2024 Diana Setiawati, Fanny Martdianty
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.