Exploring What Drives E-Learning Satisfaction and Continued Use Among Undergraduate Students in Jiangxi, China

Main Article Content

Shiqi Zhang

Abstract

Purpose: This paper generally explores the key factors influencing undergraduate students’ satisfaction and continued use intentions at a university in Jiangxi, China, when engaging in e-learning. Research design, data, and methodology: The study’s student population was 500 undergraduate students. Questionnaires were used to survey university students at a Jiangxi, China university with experience with e-learning to get statistical data. The gathered data was analyzed using Systematic Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) to determine the correlations between the variables. Results: The research indicates high-quality course content will likely meet students’ expectations and needs. Students generally have certain expectations for online courses, including the content’s relevance, depth, and practicality. Students feel their choice has been validated when course content meets or exceeds these expectations. Therefore, the quality of course content helps students gain recognition for online learning. Conclusions: With the progression of the times and continuous advancements in information technology, e-learning has become the preferred choice for most learners, especially during the widespread adoption of online learning during the COVID-19 pandemic. E-learning has greatly complemented traditional teaching methods.

Downloads

Download data is not yet available.

Article Details

How to Cite
Zhang, S. (2025). Exploring What Drives E-Learning Satisfaction and Continued Use Among Undergraduate Students in Jiangxi, China. AU-GSB E-JOURNAL, 18(3), 193-202. https://doi.org/10.14456/augsbejr.2025.72
Section
Articles
Author Biography

Shiqi Zhang

Nanchang Institute of Science and Technology, Jiangxi, China.

References

Adeyinka, T., & Mutula, S. (2010). A proposed model for evaluating the success of WebCT course content management system. Computers in Human Behavior, 26(6), 1795-1805. https://doi.org/10.1016/j.chb.2010.07.007

Aggelidis, V. P., & Chatzoglou, P. D. (2012). Hospital information systems: Measuring end user computing satisfaction (EUCS). Journal of Biomedical Informatics, 45(3), 566-579. https://doi.org/10.1016/j.jbi.2012.02.009

Al-Mamary, Y. H., & Shamsuddin, A. (2015). Testing of the technology acceptance model in context of Yemen. Mediterranean Journal of Social Sciences, 6(4), 268-273. https://doi.org/10.5901/mjss.2015.v6n4s1p268

Ambalov, I. A. (2018). A meta-analysis of IT continuance: an evaluation of the expectation confirmation model. Telematics and Informatics, 35(6), 1561-1571. https://doi.org/10.1016/j.tele.2018.03.016

Aoyama, H. (1954). A study of stratified random sampling. Ann. Inst. Stat. Math, 6(1), 1-36. https://doi.org/10.1007/bf02960514

Awang, Z. (2012). Structural equation modeling using AMOS graphic (1st ed.). Penerbit Universiti Teknologi MARA.

Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238-246.

https://doi.org/10.1037/0033-2909.107.2.238

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370. https://doi.org/10.2307/3250921

Bloomfield, J., & Fisher, M. J. (2019). Quantitative research design. Journal of the Australasian Rehabilitation Nurses Association, 22(2), 27-30. https://doi.org/10.33235/jarna.22.2.27-30

Brown, T. A., & Moore, M. T. (2012). Confirmatory factor analysis (1st ed.). Handbook of structural equation modeling.

Burke, R. R. (1997). Do you see what I see? The future of virtual shopping. Journal of the Academy of marketing Science, 25(4), 352-360. https://doi.org/10.1177/009207039725400

Chen, C. W. (2010). Impact of quality antecedents on taxpayer satisfaction with online tax-filing systems—An empirical study. Information & Management, 47(5-6), 308-315. https://doi.org/10.1016/j.im.2010.06.005

Cheng, Y. M. (2020). Students' satisfaction and continuance intention of the cloud-based e-learning system: roles of interactivity and course quality factors. Education+ Training, 62(9), 1037-1059. https://doi.org/10.1108/et-10-2019-0245

Cheok, M. L., & Wong, S. L. (2015). Predictors of e-learning satisfaction in teaching and learning for school teachers: A literature review. International Journal of Instruction, 8(1), 75-90. https://doi.org/10.12973/iji.2015.816a

Chiu, C. M., Sun, S. Y., Sun, P. C., & Ju, T. L. (2007). An Empirical Analysis of the Antecedents of Web-based Learning Continuance. Computers & Education, 49(4), 1224-1245. https://doi.org/10.1016/j.compedu.2006.01.010

Chow, W. S., & Shi, S. (2014). Investigating students’ satisfaction and continuance intention toward e-learning: An extension of the expectation–confirmation model. Procedia-Social and Behavioral Sciences, 141, 1145-1149.

https://doi.org/10.1016/j.sbspro.2014.05.193

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008

De Smet, P. A. G. M., Dautzenberg, M., & Dupont, A. G. (2012). Combining antidepressants in the treatment of severe and/or treatment-resistant depression: A systematic review. Journal of Clinical Psychopharmacology, 32(5), 692-698.

https://doi.org/10.1097/JCP.0b013e3182665729

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104

Gay, G. H. E. (2016). An assessment of online instructor e-learning readiness before, during, and after course delivery. Journal of Computing in Higher Education, 28(2), 199-220.

https://doi.org/10.1007/s12528-016-9115-z

Humbani, M., & Wiese, M. (2019). An integrated framework for the adoption and continuance intention to use mobile payment apps. International Journal of Bank Marketing, 37(2), 646-664. https://doi.org/10.1108/ijbm-03-2018-0072

Isik, H. (2008). The Effects of Combination of the History Subjects with Local History on the Success of Students in Primary School. Uluslararasi Sosyal Arastirmalar Dergisi, 2(3), 290-310.

Joo, S., & Choi, N. (2016). Understanding users’ continuance intention to use online library resources based on an extended expectation-confirmation model. The Electronic Library, 34(4), 554-571. https://doi.org/10.1108/el-02-2015-0033

Khan, A. W. (1997). Introduction in educational technology 2000: A global vision for open and distance learning. Conference Papers.

Khasawneh, M., & Yaseen, A. B. (2017). Critical success factors for e-learning satisfaction, Jordanian Universities’ experience. Journal of Business & Management (COES&RJ-JBM), 5, 56-69. https://doi.org/10.25255/jbm.2017.5.1.56.69

Kumar, V., & Reinartz, W. (2016). Creating enduring customer value. Journal of marketing, 80(6), 36-68.

https://doi.org/10.1509/jm.15.0414

Larsen, T. J., Sørebø, A. M., & Sørebø, Ø. (2009). The role of task-technology fit as users’ motivation to continue information system use. Computers in Human behavior, 25(3), 778-784. https://doi.org/10.1016/j.chb.2009.02.006

Lee, M. C. (2010). Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model. Computers & education, 54(2), 506-516. https://doi.org/10.1016/j.compedu.2009.09.002

Lee, Y. C. (2006). An empirical investigation into factors influencing the adoption of an e‐learning system. Online information review, 30(5), 517-541. https://doi.org/10.1108/14684520610706406

Liaw, S. S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system. Computers & Education, 51(2), 864-873. https://doi.org/10.1016/j.compedu.2007.09.005

Lin, X., Featherman, M., & Sarker, S. (2017). Understanding factors affecting users’ social networking site continuance: A gender difference perspective. Information & Management, 54(3), 383-395. https://doi.org/10.1016/j.im.2016.09.004

Malhotra, N. K., Kim, S. S., & Agarwal, J. (2007). Information load and consumer decision making. Journal of Consumer Research, 34(1), 47-56. https://doi.org/10.1086/518545

Mazuri, M. A., Mohamed, A., & Mohamed, M. (2017). The effects of leadership styles on employee performance in Malaysian healthcare industry. Journal of Management Development, 36(9), 1173-1188.

McDougall, G. H., & Levesque, T. (2000). Customer satisfaction with services: putting perceived value into the equation. Journal of services marketing, 14(5), 392-410.

Mtebe, J. S., & Raisamo, R. (2014). A model for assessing Learning Management System success in higher education in Sub‐Saharan countries. The Electronic Journal of Information Systems in Developing Countries, 61(1), 1-17.

https://doi.org/10.1002/j.1681-4835.2014.tb00436.x

Oh, J. H., & Ma, J. (2018). Multi-stage expectation-confirmation framework for salespeople expectation management. Journal of Business & Industrial Marketing, 33(8), 1165-1175. https://doi.org/10.1108/jbim-01-2018-0027

Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469. https://doi.org/10.1177/002224378001700405

Oliver, R. L. (1999). Whence consumer loyalty?. Journal of marketing, 63(4), 33-44. https://doi.org/10.1177/00222429990634s105

Pedroso, C. B., Da Silva, A. L., & Tate, W. L. (2016). Sales and Operations Planning (S&OP): Insights from a multi-case study of Brazilian Organizations. International Journal of Production Economics, 182, 213-229.

Perwitasari, A. W. (2022). The Effect of Perceived Usefulness and Perceived Easiness towards Behavioral Intention to Use Fintech by Indonesian MSMEs. The Winners, 23(1), 1-9. https://doi.org/10.21512/tw.v23i1.7078

Phuong, N. N. D., Luan, L. T., Dong, V. V., & Khanh, N. L. N. (2020). Examining customers' continuance intentions towards e-wallet usage: The emergence of mobile payment acceptance in Vietnam. The Journal of Asian Finance, Economics and Business, 7(9), 505-516. https://doi.org/10.13106/jafeb.2020.vol7.no9.505

Prebensen, N. K., Woo, E., Chen, J. S., & Uysal, M. (2013). Motivation and involvement as antecedents of the perceived value of the destination experience. Journal of travel research, 52(2), 253-264.

Raykov, T. (2001). Estimation of congeneric scale reliability using covariance structure analysis with nonlinear constraints. British Journal of Mathematical and Statistical Psychology, 54(2), 315-323. https://doi.org/10.1348/000711001159582

Seçkin, Z., Doğan, M., & Yalçın, A. (2016). The impact of information and communication technologies on educational performance: A case study from Turkey. Education and Information Technologies, 21(2), 273-289.

Seddon, P., & Kiew, M. Y. (1996). A partial test and development of DeLone and McLean's model of IS success. Australasian Journal of Information Systems, 4(1), 20-80. https://doi.org/10.3127/ajis.v4i1.379

Sharma, G. P., Verma, R. C., & Pathare, P. (2005). Mathematical modeling of infrared radiation thin layer drying of onion slices. Journal of Food Engineering, 71(3), 282-286. https://doi.org/10.1016/j.jfoodeng.2005.02.010

Sharpe, R., & Benfield, G. (2005). The student experience of e-learning in higher education. Brookes e-Journal of Learning and Teaching, 1(3), 1-9.

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 Science Publishers.

Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., & Yeh, D. (2008). What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & education, 50(4), 1183-1202.

https://doi.org/10.1016/j.compedu.2006.11.007

Taylor, D. (2014). Interactions in online courses and student academic success (Doctoral dissertation, University of Kansas).

Tudor-Locke, C., Williams, J. E., Reis, J. P., & Pluto, D. (2002). Utility of pedometers for assessing physical activity: convergent validity. Sports medicine, 32(12), 795-808. https://doi.org/10.2165/00007256-200434050-00001

Wang, Y. S. (2015). Examining the role of social influence, quality, and satisfaction in the acceptance of e-government services: A case study in Taiwan. Journal of Educational Technology & Society, 18(4), 117-129.

Watson, S. L. (2015). Effects of practice and feedback on student performance in online learning environments. Journal of Educational Technology Systems, 43(3), 269-287. https://doi.org/10.1177/0047239515588166

Wibisono, G., & Ang, S. Y. (2019). Intention to use voluntary disclosure information on social media for investment decisions: Analysis using perceived ease of use and perceived usefulness. Indonesian Journal of Sustainability Accounting and Management, 3(2), 137-146. https://doi.org/10.28992/ijsam.v3i2.90

Wijana, I. D. P. (2010). Kartun: Studi tentang permainan bahasa. Humaniora, 22(1), 34-43.

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. https://doi.org/10.1016/j.im.2006.05.002

Zhang, H., Lu, Y., Gupta, S., & Gao, P. (2015). Understanding group-buying websites continuance: An extension of expectation confirmation model. Internet research, 25(5), 767-793. https://doi.org/10.1108/intr-05-2014-0127