Students’ Satisfaction with Blended Learning in a Public College in Chengdu, China
Keywords:
System Quality, Information Quality, Perceived Usefulness, Self-Efficacy, Blended LearningAbstract
Purpose: The study comprehensively explores the impact of five independent variables: teaching presence, system quality, information quality, perceived usefulness, and self-efficacy. The dependent variable is students’ satisfaction. Research design, data, and methodology: The research utilized the Index of Item-Objective Congruence (IOC) to assess validity and employed Cronbach’s Alpha in a pilot test with 40 participants to establish reliability. Subsequently, 80 valid responses from students at Chengdu Vocational and Technical College of Industry were subjected to multiple linear regression analysis. This analysis aimed to ascertain the significant relationships among the variables. Following this, a cohort of 30 students participated in a 14-week strategic plan. The quantitative data obtained before and after the strategic plan implementation were compared using a paired-sample t-test, providing a comprehensive evaluation of the plan’s effectiveness. Results: In the multiple linear regression analysis, it was found that factors such as teaching presence, system quality, information quality, perceived usefulness, and self-efficacy significantly impacted students’ satisfaction. Additionally, the paired-sample t-test results indicated a notable difference in students’ satisfaction before and after the implementation of the strategic plan. Conclusions: This research is dedicated to identifying and implementing strategies that effectively meet students’ specific needs and expectations in this region, thereby contributing to an improved educational experience.
References
Akyol, Z., & Garrison, D. R. (2008). The development of a community of inquiry over time in an online course: Understanding the progression and integration of social, cognitive, and teaching presence. Journal of Asynchronous Learning Networks, 12, 3-22. https://doi.org/10.24059/olj.v12i3-4.1680
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 Information and Learning Technology, 35(4), 285-304. https://doi.org/10.1108/ijilt-11-2017-0116
Ali, M., Puah, C. H., Fatima, S., Hashmi, A., & Ashfaq, M. (2022). Student e-learning service quality, satisfaction, commitment, and behaviour towards finance courses in COVID-19 pandemic. International Journal of Educational Management, 36(6), 892-907. https://doi.org/10.1108/ijem-04-2021-0133
Alla, M. M. S. O., Faryadi, Q., & Fabil, N. B. (2013). The impact of system quality in e-learning system. Journal of Computer Science and Information Technology, 1(2), 14-23.
Al Natour, S., & Woo, C. (2021). The determinants of learner satisfaction with the online video presentation method. Internet Research, 31(1), 234-261. https://doi.org/10.1108/intr-04-2019-0155
Al-Rahmi, W. M., Yahaya, N., Aldraiweesh, A. A., Alamri, M. M., Aljarboa, N. A., Alturki, U., & Aljeraiwi, A. A. (2019). Integrating technology acceptance model with innovation diffusion theory: An empirical investigation on students’ intention to use E-learning systems. IEEE Access, 7, 26797-26809. https://doi.org/10.1109/access.2019.2899368
Anderson, T., Rouke, L., Garrison, D. R., & Archer, W. (2001). Assessing teaching presence in a computer conferencing context. Journal of Asynchronous Learning Networks, 5(2), 1-17. https://doi.org/10.24059/olj.v5i2.1875
Azila-Gbettor, E. M., Mensah, C., & Abiemo, M. K. (2022). Self-efficacy and academic programme satisfaction: mediating effect of meaningfulness of study. International Journal of Educational Management, 36(3), 261-276.
https://doi.org/10.1108/ijem-09-2021-0353
Bandura, A. (1994). Self-Efficacy. In V. S. Ramachaudran (Ed.), Encyclopaedia of Human Behaviour (pp. 71-81). Academic Press.
Caskurlu, S., Maeda, Y., Richardson, J. C., & Lv, J. (2020). A meta-analysis addressing the relationship between teaching presence and students’ satisfaction and learning. Computers & Education, 157, 103966. https://doi.org/10.1016/j.compedu.2020.103966
Chang, C. C. (2013). Exploring the determinants of e-learning systems continuance intention in academic libraries. Library Management, 34(1/2), 40-55. https://doi.org/10.1108/01435121311298261
Cheng, Y.-M. (2014). Extending the expectation-confirmation model with quality and flow to explore nurses continued blended e-learning intention. Information 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 factors. Education + Training, 62(9), 1037-1059. https://doi.org/10.1108/et-10-2019-0245
Chopra, G., Madan, P., Jaisingh, P., & Bhaskar, P. (2019). Effectiveness of e-learning portal from students' perspective: A structural equation model (SEM) approach. Interactive Technology and Smart Education, 16(2), 94-116.
https://doi.org/10.1108/itse-05-2018-0027
Cole, M. T., Shelley, D. J., & Swartz, L. B. (2014). Online instruction, e-learning, and student satisfaction: A three-year study. The International Review of Research in Open and Distributed Learning, 15(6), 111-131.
https://doi.org/10.19173/irrodl.v15i6.1748
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
DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4), 9-30.
D’Souza, C., Kappelides, P., Sithole, N., Chu, M. T., Taghian, M., & Tay, R. (2023). Learning self-efficacies influence on e-servicescapes: rethinking post-pandemic pedagogy. Journal of Services Marketing, 37(5), 636-649.
https://doi.org/10.1108/jsm-05-2022-0179
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. https://doi.org/10.1108/18363261211281744
Farid, S., Ahmad, R., Alam, M., Akbar, A., & Chang, V. (2018). A sustainable quality assessment model for the information delivery in E-learning systems. Information Discovery and Delivery, 46(1), 1-25. https://doi.org/10.1108/idd-11-2016-0047
Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. The internet and higher education, 2(2-3), 87-105. https://doi.org/10.1016/s1096-7516(00)00016-6
Gashi, A., Zhushi, G., & Krasniqi, B. (2022). Exploring determinants of student satisfaction with synchronous e-learning: evidence during COVID-19. The International Journal of Information and Learning Technology, 38(5), 454-472.
Giannousi, M., & Kioumourtzoglou, E. (2016). Cognitive, social, and teaching presence as predictors of students' satisfaction in distance learning. Mediterranean Journal of Social Sciences, 7(21), 439. https://doi.org/10.5901/mjss.2016.v7n2s1p439
Gorla, N., Somers, T. M., & Wong, B. (2010). Organizational impact of system quality, information quality, and service quality. The Journal of Strategic Information Systems, 19(3), 207-228. https://doi.org/10.1016/j.jsis.2010.05.001
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1995). Multivariate data analysis. Prentice-Hall.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modelling. Sage.
Hassanzadeh, A., Kanaani, F., & Elahi, S. (2012). A model for measuring e-learning systems success in universities. Expert systems with Applications, 39(12), 10959-10966. https://doi.org/10.1016/j.eswa.2012.03.028
Hobfoll, S. E. (2002). Social and psychological resources and adaptation. Review of general psychology, 6(4), 307-324.
https://doi.org/10.1037/1089-2680.6.4.307
Huh, Y. U., Keller, F. R., Redman, T. C., & Watkins, A. R. (1990). Data quality. Information and software technology, 32(8), 559-565.
Lee, B. C., Yoon, J. O., & Lee, I. (2009). Learners’ acceptance of e-learning in South Korea: Theories and results. Computers & education, 53(4), 1320-1329. https://doi.org/10.1016/j.compedu.2009.06.014
Maini, R., Sehgal, S., & Agrawal, G. (2021). Todays' digital natives: an exploratory study on students' engagement and satisfaction towards virtual classes amid COVID-19 pandemic. The International Journal of Information and Learning Technology, 38(5), 454-472. https://doi.org/10.1108/ijilt-03-2021-0055
Martin, F., Wu, T., Wan, L., & Xie, K. (2022). A Meta-Analysis on the Community of Inquiry Presences and Learning Outcomes in Online and Blended Learning Environments. Online Learning, 26(1), 325-359. https://doi.org/10.24059/olj.v26i1.2604
Mirabolghasemi, M., Shasti, R., & Hosseinikhah Choshaly, S. (2021). An investigation into the determinants of blended leaning satisfaction from EFL learners’ perspective. Interactive Technology and Smart Education, 18(1), 69-84.
https://doi.org/10.1108/itse-07-2020-0117
Nikou, S., & Maslov, I. (2023). Finnish university students’ satisfaction with e-learning outcomes during the COVID-19 pandemic. International Journal of Educational Management, 37(1), 1-21. https://doi.org/10.1108/ijem-04-2022-0166
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory. McGraw-Hill.
Salimon, M. G., Sanuri, S. M. M., Aliyu, O. A., Perumal, S., & Yusr, M. M. (2021). E-learning satisfaction and retention: A concurrent perspective of cognitive absorption, perceived social presence and technology acceptance model. Journal of Systems and Information Technology, 23(1), 109-129. https://doi.org/10.1108/jsit-02-2020-0029
Sedera, D., Gable, G., & Chan, T. (2004). A factor and structural equation analysis of the enterprise systems success measurement model. Proceedings of the 10th, Americas conference on information systems, 676-682.
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 Educ. Dev. Stud., 10, 276-294.
Siddiqui, S., Soomro, N. N., & Thomas, M. (2020). Blended learning source of satisfaction of psychological needs: an empirical study conducted on O-levels chemistry students in metropolis city of Pakistan. Asian Association of Open Universities Journal, 15(1), 49-67. https://doi.org/10.1108/aaouj-11-2019-0054
Szeto, E. (2015). Community of Inquiry as an instructional approach: What effects of teaching, social and cognitive presences are there in blended synchronous learning and teaching?. Computers & Education, 81, 191-201.
https://doi.org/10.1016/j.compedu.2014.10.015
Tan, C. (2021). The impact of COVID-19 pandemic on student learning performance from the perspectives of community of inquiry. Corporate Governance: The International Journal of Business in Society, 21(6), 1215-1228.
https://doi.org/10.1108/cg-09-2020-0419
Vongurai, R. (2022). Key Drivers of Operational Performance of E-commerce Distribution Service Providers in Thailand. Journal of Distribution Science, 20(12), 89–98. https://doi.org/10.15722/jds.20.12.202212.89
Wang, Y. S., Wang, H. Y., & Shee, D. Y. (2007). Measuring e-learning systems success in an organizational context: Scale development and validation. Computers in Human Behaviour, 23(4), 1792-1808. https://doi.org/10.1016/j.chb.2005.10.006
Wong, W. H., & Chapman, E. (2023). Student satisfaction and interaction in higher education. Higher Education, 85(5), 957-978. https://doi.org/10.1007/s10734-022-00874-0
Wu, J. H., Tennyson, R. D., & Hsia, T. L. (2010). A study of student satisfaction in a blended e-learning system environment. Computers & education, 55(1), 155-164. https://doi.org/10.1016/j.compedu.2009.12.012
Zheng, Y., Zhao, K., & Stylianou, A. (2013). The impacts of information quality and system quality on users' continuance intention in information-exchange virtual communities: An empirical investigation. Decision support systems, 56, 513-524. https://doi.org/10.1016/j.dss.2012.11.008
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Yuanwei Bao
This work is licensed under a Creative Commons Attribution 4.0 International License.
The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data, or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution License (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
