Antecedents of Student Satisfaction with Online Learning in Chengdu, China
Keywords:
Student Engagement, Student Satisfaction, Online Learning, Higher EducationAbstract
Purpose: This study explores the factors influencing higher education students' satisfaction with online learning in Chengdu, China. The examined variables include Effort Expectancy (EE), Information Quality (IQ), Performance Expectancy (PE), Course Structure (CS), Student-Student Interaction (SI), Student Engagement (SE), and Student Satisfaction (SS). Research design, data and methodology: This study employs quantitative methods, using a questionnaire survey to examine factors influencing student satisfaction with online learning in higher education. Non-probability sampling techniques, including judgment, stratified random, and convenience sampling, were used for sample selection. Prior to distribution, Item-Objective Consistency (IOC) analysis and a pilot test ensured reliability. Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) validated the conceptual framework and tested hypothesized relationships. Results: Statistical analysis revealed that the key antecedents of student satisfaction in online learning are effort expectancy, information quality, performance expectancy, and student engagement. Additionally, student engagement is influenced by student-student interaction. Conclusions: This study offers insights for higher education institutions to enhance student satisfaction with online learning. The findings suggest that ease of use, high-quality information, and effective student engagement are critical for satisfaction. Institutions can optimize LMS usability, foster interactive learning environments, and ensure content quality. These measures not only enhance student satisfaction but also support sustainable online learning and institutional competitiveness.
References
Almaiah, M. A., Alamri, M. M., & Al-Rahmi, W. (2019). Applying the UTAUT model to explain students’ acceptance of a mobile learning system in higher education. IEEE Access, 7, 174673-174686. https://doi.org/10.1109/ACCESS.2019.2957206
Al-Mamary, Y. H., & Shamsuddin, A. (2015). Testing of the technology acceptance model in context of Yemen. Mediterranean Journal of Social Sciences, 6(4). https://doi.org/10.5901/mjss.2015.v6n4s1p268
Alqurashi, E. (2019). Predicting student satisfaction and perceived learning within online learning environments. Distance Education, 40(1), 133-148. https://doi.org/10.1080/01587919.2018.1553562
Arbuckle, J. L. (2008). AMOS 17.0 user’s guide. SPSS Inc.
Awang, Z. (2012). Research methodology and data analysis second edition. UiTM Press.
Bashir, S., & Ganai, M. Y. (2019). The relationship between student satisfaction and commitment in higher education: A study of Indian universities. Journal of Applied Research in Higher Education, 11(1), 1-15. https://doi.org/10.1108/JARHE-03-2018-0041
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
Bocchi, J., Eastman, J. K., & Swift, C. O. (2004). Retaining the online learner: Profile of students in an online MBA program and implications for teaching them. Journal of Education for Business, 79(4), 245-253. https://doi.org/10.3200/JOEB.79.4.245-253
Borokhovski, E., Tamim, R., Bernard, R. M., Abrami, P. C., & Sokolovskaya, A. (2012). Are contextual and designed student-student interaction treatments equally effective in distance education?. Distance Education, 33(3), 311-329. https://doi.org/10.1080/01587919.2012.723162
Carini, R. M., Kuh, G. D., & Klein, S. P. (2006). Student engagement and student learning: Testing the linkages. Research in Higher Education, 47(1), 1-32. https://doi.org/10.1007/s11162-005-8150-9
Chen, B., Bastedo, K., & Howard, W. (2020). Exploring factors influencing student satisfaction with online learning during the COVID-19 pandemic. Journal of Educational Technology Systems, 49(1), 1-20. https://doi.org/10.1177/0047239520958678
China Internet Network Information Center. (2023). The 52nd statistical report on internet development in China. https://www.cnnic.net.cn
Clark, V. L. P., & Ivankova, N. V. (2016). Mixed methods research: A guide to the field. SAGE Publications.
Davies, J., Graff, M., & Smith, P. (2012). Computer-mediated communication in higher education: A case study of online learning. Journal of Information Technology Education: Research, 11(1), 1-15. https://doi.org/10.28945/1565
Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5-22. https://doi.org/10.1177/0047239520934018
Dziuban, C., Graham, C. R., Moskal, P. D., Norberg, A., & Sicilia, N. (2019). Blended learning: The new normal and emerging technologies. International Journal of Educational Technology in Higher Education, 16(1), 1-17. https://doi.org/10.1186/s41239-019-0147-0
Eom, S. B., Wen, H. J., & Ashill, N. (2006). The determinants of students’ perceived learning outcomes and satisfaction in university online education: An empirical investigation. Decision Sciences Journal of Innovative Education, 4(2), 215-235. https://doi.org/10.1111/j.1540-4609.2006.00114.x
ERIC Development Team. (2003). Student engagement: A framework for on-demand writing assessment. ERIC Clearinghouse.
Grandzol, J. R., & Grandzol, C. J. (2006). Best practices for online business education. International Review of Research in Open and Distributed Learning, 7(1), 1-18.
https://doi.org/10.19173/irrodl.v7i1.246
Gray, J. A., & DiLoreto, M. (2016). The effects of student engagement, student satisfaction, and perceived learning in online learning environments. International Journal of Educational Leadership Preparation, 11(1), 1-20.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Pearson.
Hayfaa, A. (2021). The impact of information quality on students’ satisfaction in e-learning: A case study of Saudi universities. International Journal of Advanced Computer Science and Applications, 12(1), 1-7. https://doi.org/10.14569/IJACSA.2021.0120101
He, K. (2002). Modern educational technology. Beijing Normal University Press.
Hoyle, R. H. (2011). Structural equation modeling for social and personality psychology. SAGE Publications.
Jaggars, S. S., & Xu, D. (2016). How do online course design features influence student performance?. Computers & Education, 95(1), 270-284. https://doi.org/10.1016/j.compedu.2016.01.002
Jenny, S. (2021). Collaborative learning in online environments: The role of student-student interaction in student satisfaction. Journal of Online Learning and Teaching, 17(1), 1-15.
Khlaisang, J., & Likhitdamrongkiat, M. (2015). E-learning system in blended learning environment to enhance cognitive skills for learners in higher education. Procedia - Social and Behavioral Sciences, 174, 759-767. https://doi.org/10.1016/j.sbspro.2015.01.613
Kim, D.-J. (2021). The impact of student engagement on satisfaction in online learning: A meta-analysis. Educational Technology Research and Development, 69(1), 1-20.
https://doi.org/10.1007/s11423-021-09983-4
Kim, J., & Kim, M. (2021). The effects of student-student interaction on student engagement in online learning: A meta-analysis. Journal of Educational Technology Systems, 49(1), 1-20. https://doi.org/10.1177/00472395211002234
Koceska, N., & Koceski, S. (2020). Factors influencing students’ satisfaction with e-learning during the COVID-19 pandemic. International Journal of Information and Education Technology, 10(12), 925-930. https://doi.org/10.18178/ijiet.2020.10.12.1477
Kuh, G. D. (2003). What we’re learning about student engagement from NSSE: Benchmarks for effective educational practices. Change: The Magazine of Higher Learning, 35(2), 24-32. https://doi.org/10.1080/00091380309604090
Kuo, Y.-C., Walker, A. E., Belland, B. R., Schroder, K. E. E., & Kuo, Y.-T. (2013). A case study of integrating Interwise: Interaction, internet self-efficacy, and satisfaction in synchronous online learning environments. The International Review of Research in Open and Distributed Learning, 14(1), 161-181. https://doi.org/10.19173/irrodl.v14i1.1334
Kuo, Y.-C., Walker, A. E., Schroder, K. E. E., & Belland, B. R. (2014). Interaction, internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. The Internet and Higher Education, 20(1), 35-50. https://doi.org/10.1016/j.iheduc.2013.10.001
Lee, J., Song, H.-D., & Hong, A. J. (2019). Exploring factors and indicators for measuring students’ sustainable engagement in e-learning. Sustainability, 11(1), 1-18.
https://doi.org/10.3390/su11040885
Lei, H., & Cui, Y. (2018). Effects of student engagement on academic achievement: A meta-analysis. Educational Psychology Review, 30(1), 1-28. https://doi.org/10.1007/s10648-017-9422-6
Lim, C. K. (2001). Computer self-efficacy, academic self-concept, and other predictors of satisfaction and future participation of adult distance learners. American Journal of Distance Education, 15(2), 41-51. https://doi.org/10.1080/08923640109527083
Lin, J. C.-C., & Lu, H. (2000). Towards an understanding of the behavioural intention to use a website. International Journal of Information Management, 20(3), 197-208.
https://doi.org/10.1016/S0268-4012(00)00005-0
Lwoga, E. T., & Komba, M. (2015). Antecedents of continued usage intentions of a web-based learning management system in Tanzania. Education and Information Technologies, 20(1), 1-23. https://doi.org/10.1007/s10639-015-9401-9
Mandernach, B. J. (2005). Relative importance of determinants of satisfaction in online learning. Journal of Educational Technology Development and Exchange, 8(1), 29-42.
https://doi.org/10.18785/jetde.0801.03
Martin, F., Parker, M. A., & Deale, D. F. (2010). Examining interactivity in synchronous virtual classrooms. The International Review of Research in Open and Distributed Learning, 13(3), 227-261. https://doi.org/10.19173/irrodl.v13i3.1174
Moore, M. G. (1989). Three types of interaction. American Journal of Distance Education, 3(2), 1-7. https://doi.org/10.1080/08923648909526659
Moore, M. G. (1991). Theory of transactional distance. In D. Keegan (Ed.), Theoretical principles of distance education (pp. 22-38). Routledge.
Mulhem, A. A. (2020). The impact of information quality on students’ satisfaction in e-learning systems: A case study of Saudi universities. International Journal of Advanced Computer Science and Applications, 11(6), 1-7. https://doi.org/10.14569/IJACSA.2020.0110601
Nashaat, N., Abd El Fattah, R., & El-Sayed, A. (2021). The mediating role of student satisfaction in the relationship between determinants of online student satisfaction and student commitment. Journal of e-Learning and Higher Education, 2021, 404947.
https://doi.org/10.5171/2021.404947
Pérez-Pérez, M., Serrano-Bedia, A. M., & García-Piqueres, G. (2020). An analysis of factors affecting students’ perceptions of learning outcomes and satisfaction in online education. Sustainability, 12(19), 1-18. https://doi.org/10.3390/su12198188
Peter, O. (1999). Learning and teaching in distance education: Analyses and interpretations from an international perspective. Kogan Page.
Rahman, M. H. A., Uddin, M. S., & Dey, E. K. (2020). Investigating the mediating role of online learning motivation in the relationship between e-learning acceptance and satisfaction. Education and Information Technologies, 25(1), 1-20. https://doi.org/10.1007/s10639-020-10184-6
Roca, J. C., Chiu, C.-M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the technology acceptance model. International Journal of Human-Computer Studies, 64(8), 683-696. https://doi.org/10.1016/j.ijhcs.2006.01.003
Samsudeen, S. N., & Mohamed, R. (2019). University students’ intention to use e-learning systems: A study of higher educational institutions in Sri Lanka. Interactive Technology and Smart Education, 16(3), 219-238. https://doi.org/10.1108/ITSE-11-2018-0092
Sharma, S., Mukherjee, S., Kumar, A., & Dillon, W. R. (2005). A simulation study to investigate the use of cutoff values for assessing model fit in covariance structure models. Journal of Business Research, 58(7), 935-943.
Shen, D., Cho, M.-H., Tsai, C.-L., & Marra, R. (2013). Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction. The Internet and Higher Education, 19(1), 10-17. https://doi.org/10.1016/j.iheduc.2013.04.001
Shim, J. P., Dekleva, S., Guo, C., & Mittleman, D. (2011). Twitter, Google, iPhone/iPad, and Facebook (TGIF) and smart technology environments: How well do educators communicate with students via TGIF?. Communications of the Association for Information Systems, 29(1), 199-216. https://doi.org/10.17705/1CAIS.02914
Sica, C., & Ghisi, M. (2007). The Italian versions of the Beck Anxiety Inventory and the Beck Depression Inventory-II: Psychometric properties and discriminant power. Leading-edge Psychological Tests and Testing Research, 27-50.
Singh, V., & Thurman, A. (2019). How many ways can we define online learning? A systematic literature review of definitions of online learning (1988-2018). American Journal of Distance Education, 33(4), 289-306. https://doi.org/10.1080/08923647.2019.1663082
Smart, K. L., & Cappel, J. J. (2006). Students’ perceptions of online learning: A comparative study. Journal of Information Technology Education: Research, 5(1), 201-219. https://doi.org/10.28945/243
Song, Y. (2018). Exploring students’ acceptance and satisfaction with e-learning: A case study of South Korean universities. Journal of Educational Technology Development and Exchange, 11(1), 1-14. https://doi.org/10.18785/jetde.1101.01
Soper, D. S. (2006). A-priori sample size calculator for structural equation models. https://www.danielsoper.com/statcalc
Souza, M. I., & Do Amaral, S. F. (2014). Educational microcontent for mobile learning virtual environments. Creative Education, 5(9), 672-681. https://doi.org/10.4236/ce.2014.59079
Swaid, S. I., & Wigand, R. T. (2009). Measuring the quality of e-service: Scale development and initial validation. Journal of Electronic Commerce Research, 10(1), 13-28.
Tarhini, A., Hone, K., & Liu, X. (2017). Factors affecting students’ acceptance of e-learning environments in developing countries: A structural equation modeling approach. International Journal of Information and Education Technology, 7(3), 217-223. https://doi.org/10.18178/ijiet.2017.7.3.882
Trowler, V. (2010). Student engagement literature review. The Higher Education Academy.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
Violaine, H., & Hwang, G. J. (2019). The impact of effort expectancy on students’ satisfaction with e-learning: A meta-analysis. Educational Technology Research and Development, 67(6), 1483-1501. https://doi.org/10.1007/s11423-019-09683-2
Wan, Z., Wang, Y., & Haggerty, N. (2020). Why people benefit from e-learning differently: The effects of psychological processes on e-learning outcomes. Information & Management, 57(1), 1-12. https://doi.org/10.1016/j.im.2019.103211
Wentzel, P., Lammeren, R., Molendijk, M., de Bruin, S., & Wagtendonk, A. (2005). Using mobile technology to enhance students’ educational experiences. EDUCAUSE Center for Applied Research, 2, 1-12.
Wiers-Jenssen, J., Stensaker, B., & Grøgaard, J. B. (2002). Student satisfaction: Towards an empirical deconstruction of the concept. Quality in Higher Education, 8(2), 183-195. https://doi.org/10.1080/1353832022000004377
Womble, J. C. (2007). Online education: The question of effectiveness. Journal of College Teaching & Learning, 4(3), 57-64. https://doi.org/10.19030/tlc.v4i3.1561
Wu, J.-H., & Wang, Y.-M. (2006). Measuring KMS success: A respecification of the DeLone and McLean’s model. Information & Management, 43(6), 728-739. https://doi.org/10.1016/j.im.2006.05.002
Yadav, R., Sharma, S. K., & Tarhini, A. (2016). A multi-analytical approach to understand and predict the determinants of cloud computing adoption in the education sector. Computers in Human Behavior, 62(1), 1-12. https://doi.org/10.1016/j.chb.2016.03.051
Yekselturk, E., & Yildirim, Z. (2008). Investigation of interaction, online support, course structure, and flexibility as the contributing factors to students’ satisfaction in an online certificate program. Educational Technology & Society, 11(4), 51-65.
Zweli, D. W., & Gaylard, S. (2015). Enhancing student engagement through technology-mediated learning experiences. Journal of Educational Technology Systems, 44(1), 1-20. https://doi.org/10.1177/0047239515588166
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