STUDENTS’ SATISFACTION TOWARDS ONLINE LEARNING DURING THE COVID-19 PANDEMIC THROUGH END-USER COMPUTING SATISFACTION (EUCS)

Wahyuni Wahyuni, Siti Habsari Pratiwi

Abstract


The Covid-19 pandemic has brought significant changes to learning systems. Thus, it is highly important to evaluate the implementation of online learning. This study aimed to investigate students’ satisfaction with online learning through End-User Computing Satisfaction (EUCS) proposed by Doll. There were five EUCS indicators utilized to determine the level of satisfaction, namely: content, accuracy, format, ease of use, and punctuality. EUCS instruments were adopted, modified, and tested for the validity of 12 items. This study involved 108 respondents consisting of students from four faculties at IAIN Langsa. Data were collected by using a google form questionnaire. The findings showed that the score for the indicator of the content of online learning was 67% (satisfied) while the score for the indicator of the accuracy of online learning was 54, 54% (quite satisfied). Moreover, the score of the indicator of the form of online learning was 56, 48% (quite satisfied), and the score of the indicator of the convenience of the access of online learning was 78, 79% (satisfied). At last, the score of the indicator of punctuality of online learning was 64, 26% (satisfied). This data showed that the highest score of students’ satisfaction was the convenience of the access of online learning while the lowest score of students’ satisfaction was the indicator of accuracy.


Keywords


satisfaction, online learning, end user computing satisfaction (EUCS)

References


Abdinnour-Helm, S. F., Chaparro, B. S., & Farmer, S. M. (2005). Using the End-User Computing satisfaction (EUCS) instrument to measure satisfaction with a Web Site. Decision Sciences, 36(2), 341–364. https://doi.org/10.1111/j.1540-5414.2005.00076.x

Alshehri, A., & O’Keefe, R. (2019). Analyzing Social Media to Assess User Satisfaction with Transport for London’s Oyster. International Journal of Human-Computer Interaction, 35(15), 1378–1387. https://doi.org/10.1080/10447318.2018.1526442

Dedić, N., & Stanier, C. (2017). Measuring the success of changes to Business Intelligence solutions to improve Business Intelligence reporting. Journal of Management Analytics, 4(2), 130–144. https://doi.org/10.1080/23270012.2017.1299048

Deng, X., Doll, W. J., Al-Gahtani, S. S., Larsen, T. J., Pearson, J. M., & Raghunathan, T. S. (2008). A cross-cultural analysis of the end-user computing satisfaction instrument: A multi-group invariance analysis. Information and Management, 45(4), 211–220. https://doi.org/10.1016/j.im.2008.02.002

Doll, W J, & Torkzadeh, G. (1988). The Measurement of End-User Computing Satisfaction End-User Satisfaction The Measurement of End-User Computing Satisfaction Professor of MIS and Strategic Management The University of Toledo Gholamreza Torkzadeh Assistant Professor of Information Systems. Source: MIS Quarterly, 1213512(2), 259–274. Retrieved from http://www.jstor.org/stable/248851%0Ahttp://www.jstor.org/page/info/about/policies/terms.jsp%0Ahttp://www.jstor.org

Doll, William J, Xia, W., & Torkzadeh, G. (2011). A confirmatory factor analysis of the EUCS Instrument. MIS Quarterly, 18(4), 453–461.

Edirisinghe, S. D., & Roshantha, L. M. D. (2018). Statistical Analysis on Enterprise Resource Planning Systems ( ERP ) On End User Satisfaction. Journal of Business and Management (IOSR-JBM), 20(7), 24–34. https://doi.org/10.9790/487X-2007042434

Fitriantoro, M. J., & Husnah, N. (2018). The Implementation of the End-User Computing Satisfaction Model into SCeLE: A Study of the Undergraduate Program of the Accounting Department in Universitas Indonesia. Advances in Economics, Business and Management Research (AEBMR), 55(Iac 2017), 151–155. https://doi.org/10.2991/iac-17.2018.27

Harlen, W., & Deakin Crick, R. (2003). Testing and motivation for learning. Assessment in Education: Principles, Policy and Practice, 10(2), 169–207. https://doi.org/10.1080/0969594032000121270

Hendrickson, A. R., Glorfeld, K., & Cronan, T. P. (1994). On the Repeated Test-Retest Reliability of the End-User Computing Satisfaction Instrument: A Comment. Decision Sciences, 25(4), 655–665. https://doi.org/10.1111/j.1540-5915.1994.tb01864.x

Hou, C. K. (2018). Examining users’ intention to continue using business intelligence systems from the perspectives of end-user computing satisfaction and individual performance. 8(1), 49–70. https://doi.org/10.1504/IJBCRM.2018.090593

Jury, M., Smeding, A., Stephens, N. M., Nelson, J. E., Aelenei, C., & Darnon, C. (2017). The Experience of Low-SES Students in Higher Education: Psychological Barriers to Success and Interventions to Reduce Social-Class Inequality. Journal of Social Issues, 73(1), 23–41. https://doi.org/10.1111/josi.12202

Kim, S., & Mchaney, R. (2000). Validation of the end-user computing satisfaction instrument in case tool environments. Journal of Computer Information Systems, 41(1), 49–52. https://doi.org/10.1080/08874417.2000.11646975

Klenke, K. (1992). Construct Measurement In Management Information Systems: A Review And Critique Of User Satisfaction And User Involvement Instruments. INFOR: Information Systems and Operational Research, 30(4), 325–348. https://doi.org/10.1080/03155986.1992.11732206

Larsen, T. J. (2009). A multilevel explanation of end-user computing satisfaction with an enterprise resource planning system within an international manufacturing organization. Computers in Industry, 60(9), 657–668. https://doi.org/10.1016/j.compind.2009.05.004

Lawson-Body, A., Willoughby, L., Lawson-Body, L., & Logossah, K. (2017). Developing and validating a cultural user satisfaction instrument in developing countries. Journal of Computer Information Systems, 57(4), 319–329. https://doi.org/10.1080/08874417.2016.1232977

Marakarkandy, B., & Yajnik, N. (2013). Re-examining and empirically validating the End User Computing Satisfaction models for satisfaction measurement in the internet banking context. International Journal of Bank Marketing, 31(6), 440–455. https://doi.org/10.1108/IJBM-06-2013-0051

Marginson, S. (2016). The worldwide trend to high participation higher education: dynamics of social stratification in inclusive systems. Higher Education, 72(4), 413–434. https://doi.org/10.1007/s10734-016-0016-x

McHaney, R., Hightower, R., & Pearson, J. (2002). A validation of the end-user computing satisfaction instrument in Taiwan. Information and Management, 39(6), 503–511. https://doi.org/10.1016/S0378-7206(01)00119-7

McHaney, R., Hightower, R., & White, D. (1999). EUCS test-retest reliability in representational model decision support systems. Information and Management, 36(2), 109–119. https://doi.org/10.1016/S0378-7206(99)00010-5

Norfazlina, G., Akma, A. S. S., Adrina, S. N., & Noorizan, M. M. (2016). Customer Information System Satisfaction and Task Productivity: The Moderating Effect of Training. Procedia Economics and Finance, 37(16), 7–12. https://doi.org/10.1016/s2212-5671(16)30085-5

Pikkarainen, K., Pikkarainen, T., Karjaluoto, H., & Pahnila, S. (2006). The measurement of end-user computing satisfaction of online banking services: Empirical evidence from Finland. International Journal of Bank Marketing, 24(3), 158–172. https://doi.org/10.1108/02652320610659012

Savoy, A., & Salvendy, G. (2016). Factors for Customer Information Satisfaction: User Approved and Empirically Evaluated. International Journal of Human-Computer Interaction, 32(9), 695–707. https://doi.org/10.1080/10447318.2016.1190137

Scott Rigby, C., Deci, E. L., Patrick, B. C., & Ryan, R. M. (1992). Beyond the intrinsic-extrinsic dichotomy: Self-determination in motivation and learning. Motivation and Emotion, 16(3), 165–185. https://doi.org/10.1007/BF00991650

Sebetci, Ö. (2018). Enhancing end-user satisfaction through technology compatibility: An assessment on health information system. Health Policy and Technology, 7(3), 265–274. https://doi.org/10.1016/j.hlpt.2018.06.001

Somers, T., Nelson, K., & Karimi, J. (2004). Erratum: Confirmatory factor analysis of the end-user computing satisfaction instrument: Replication within an ERP domain (Decision Sciences 34:3 (595-621)). Decision Sciences, 35(1), 145. https://doi.org/10.1111/j.1540-5414.2004.02437.x

Tjong, Y., Sugandi, L., Nurshafita, A., Magdalena, Y., Evelyn, C., & Yosieto, N. S. (2018). User Satisfaction Factors on Learning Management Systems Usage. Proceedings of 2018 International Conference on Information Management and Technology, ICIMTech 2018, (September), 11–14. https://doi.org/10.1109/ICIMTech.2018.8528171

Torkzadeh, G., Koufteros, X., & Doll, W. J. (2005). Confirmatory factor analysis and factorial invariance of the impact of information technology instrument. Omega, 33(2), 107–118. https://doi.org/10.1016/j.omega.2004.03.009




DOI: http://dx.doi.org/10.33578/pjr.v5i2.8165

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