Investigating Key Factors Influencing Student Satisfaction in Online Learning for Construction Engineering Students in Guizhou, China
Article Sidebar
Main Article Content
Abstract
Purpose: This study explores the influencing factors of student satisfaction in online learning platforms in vocational colleges in Guizhou, China. The conceptual framework proposes causal relationships among computer self-efficacy, perceived ease of use, group participation, teachers' technical readiness, student engagement, students' self-efficacy, and student satisfaction, Research Design, data, and Methods: Researcher conducted a quantitative method to survey 500 students in three representative higher vocational colleges in Guizhou. Nonprobability sampling includes judgmental, quota, and convenient sampling. Structural Equation Model and confirmatory factor analysis were used to analyze the data, including model fit, reliability and structure validity. Result: The results showed that computer self-efficacy had a significant impact on students' perceived ease of use, perceived ease of use, teachers' technical preparation, students' self-efficacy, and students' involvement significant affect student satisfaction, while group participation had no significant impact on students' satisfaction when using online learning platforms. In addition, students' perceived ease of use has the greatest impact on their satisfaction, followed by students' self-efficacy, teachers' technical preparation, and students' input. Conclusion: It is recommended that management teams and teachers at vocational colleges provide assessments to measure the impact of the online platform on the development of teaching models to enhance students' satisfaction with online learning.
Downloads
Article Details
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.
References
Abdullah, F., & Ward, R. (2016). Developing a general extended technology acceptance model for e-learning (GETAMEL) by analyzing commonly used external factors. Computers in Human Behavior, 56, 238–256. https://doi.org/10.1016/j.chb.2015.11.036
Alavi, M. (1994). Computer-mediated collaborative learning: An empirical evaluation. MIS quarterly, 18(2), 159-174. https://doi.org/10.2307/249763
Alfadda, H. A., & Mahdi, H. S. (2021). Measuring Students’ Use of Zoom Application in Language Course Based on the Technology Acceptance Model (TAM). Journal of Psycholinguistic Research, 50(4), 883-900. https://doi.org/10.1007/s10936-020-09752-1
Alhazmi, A. (2015). Student satisfaction among learners: Illustration by Jazan University students. Journal of Education and Human Development, 4(2), 1-10. https://doi.org/10.15640/jehd.v4n2_1a20
Al-Mamary, Y. H., & Shamsuddin, A. (2015). Testing of The Technology Acceptance Model in Context of Yemen. Mediterranean Journal of Social Sciences, 6(4), 1-10. https://doi.org/10.5901/mjss.2015.v6n4s1p268
Awang, Z. (2012). Structural equation modeling using AMOS graphic (1st ed.). Penerbit Universiti Teknologi MARA.
Azli, W. U. A. W., Shah, P. M., & Mohamad, M. (2018). Perception on the usage of mobile assisted language learning (MALL) in English as a second language (ESL) learning among vocational college students. Creative Education, 9(01), 84- 98. https://doi.org/10.4236/ce.2018.91008
Bates, R., & Khasawneh, S. (2007). Self-Efficacy and College Students’ Perceptions and Use of Online Learning Systems. Computers in Human Behavior, 23, 175-191. https://doi.org/10.1016/j.chb.2004.04.004
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
Bolliger, D. U. (2004). Key Factors for Determining Student Satisfaction in Online Courses (1st ed.). Association for the Advancement of Computing in Education.
Chen, H., Islam, A. A., Gu, X., Teo, T., & Peng, Z. (2019). Technology-enhanced learning and research using databases in higher education: The application of the ODAS model. Educational Psychology, 40(9), 1056-1075. https://doi.org/10.1080/01443410.2019.1614149
Chen, J. (2022). Adoption of M-learning apps: A sequential mediation analysis and the moderating role of personal innovativeness in information technology. Computers in Human Behavior Reports, 8, 100237. https://doi.org/10.1016/j.chbr.2022.100237
Coffman, D. L., & Gilligan, T. D. (2002). Social support, stress, and self-efficacy: Effects on students' satisfaction. Journal of College Student Retention: Research, Theory and Practice, 4(1), 53–66. https://doi.org/10.2190/BV7X-F87X-2MXL-2B3L
Collis, B. (1995). Anticipating the impact of multimedia in education: Lessons from literature. International journal of computers in adult education and training, 2(2), 136-149.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: development of a measure and initial test (1st ed.). MIS Quarterly
Dassanayaka, I. M. S., Weerasinghe, S. N. S., Dahanayaka, H., & Muthuweera, N. K. G. (2022). Academics’ attitudes towards online education amidst the Covid-19 outbreak. International Journal of Educational Management, 36(5), 661-677. https://doi.org/10.1108/ijem-10-2021-0414
Davis, F. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13, 319-340.https://doi.org/10.2307/249008
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer-technology: A comparison of two theoretical models.Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
Eom, S. B., & Estelami, H. (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
Finn, J. D. (1989). Withdrawing from school. Review of educational research, 59(2), 117-142. https://doi.org/10.2307/1170412
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
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: potential of the concept, state of the evidence. Review of Educational Research, 4(1), 59-109. https://doi.org/10.3102/00346543074001059
Freire, P. (2005). Teachers as cultural workers: Letters to those who dare teach with new commentary by Peter McLaren (1st ed.). Shirley Steinberg Expanded Edition.
Ghada, W., Estrella, N., Ankerst, D., & Menzel, A. (2021). Universal thermal climate index associations with mortality, hospital admissions, and road accidents in Bavaria. PLOS ONE, 16(11), 0259086.
Global. (2022, August 12). Global EdTech Venture Capital Report - Full Year 2021. https://www.holoniq.com/notes/
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.
Gunawardena, C., Linder-VanBerschot, J., Deborah, L., & Rao, L. (2010). Predictors of Learner Satisfaction and Transfer of Learning in a Corporate Online Education Program. The Amer. Jrnl. of Distance Education, 24(4), 207-226. https://doi.org/10.1080/08923647.2010.522919
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2010). Multivariate data analysis (7th ed.). Prentice Hall.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. (2006). Multivariant Data Analysis (6th ed.). Pearson International Edition.
Hsu, C. L., & Lin, J. C. C. (2008). Acceptance of Blog Usage: The Roles of Technology Acceptance, Social Influence and Knowledge Sharing Motivation. Information & Management, 45, 65-74. https://doi.org/10.1016/j.im.2007.11.001
Ibrahiem, D. M., & Sameh, R. (2020). How do clean energy sources and financial development affect unemployment? Empirical evidence from Egypt. Environmental Science and Pollution Research, 27(18), 22770-22779. https://doi.org/10.1007/s11356-020-08696-2
Islam, A. Y. M. A. (2016). Development and validation of the technology adoption and gratification (TAG) model in higher education: A cross-cultural study between Malaysia and China. International Journal of Technology and Human Interaction, 12(3), 78–105. https://doi.org/10.4018/ijthi.2016070106
Islam, A. Y. M. A., Mok, M. M. C., Qian, X., & Leng, C. H. (2018). Factors influencing students’ satisfaction in using wireless internet in higher education: Cross-validation of TSM. The Electronic Library, 36(1), 2–20. https://doi.org/10.1108/el-07-2016-0150
Islam, A. Y. M. A., & Sheikh, A. (2020). A study of the determinants of postgraduate students’ satisfaction of using online research databases. Journal of Information Science, 46(2), 273–287. https://doi.org/10.1177/0165551519834714
Jabali, A. K. (2022). The perception of engineering students and instructors in a Saudi University toward E-learning. Computer Applications in Engineering Education, 30(4), 1190–1207.
Jerusalem, M., & Mittag, W. (1995). Self-efficacy in stressful life transitions. In A. Bandura (Ed.), Self-efficacy in changing societies (pp. 177–201). Cambridge University Press. https://doi.org/10.1017/CBO9780511527692.008
Joo, Y. J., Lim, K. Y., & Kim, E. K. (2011). Online university students' satisfaction and persistence: Examining perceived level of presence, usefulness, and ease of use as predictors in a structural model. Computers & Education, 57(2), 1654-1664. https://doi.org/10.1016/j.compedu.2011.02.008
Joseph, A., Frangi, J. P., & Aranyossy, J. F. (2002). The economics of immense risk, urgent action, and radical change: towards new approaches to the economics of climate change (1st ed.). LSE Research Online Documents on Economics.
Koller, D. (2012, June 28). What we are learning from online education. https://www.ted.com/talks/daphne_
Lakshmi, Y. V., Das, J., & Majid, I. (2020). Assessment of e-Learning Readiness of Academic Staff & Students of Higher Education Institutions in Gujarat, India. Indian Journal of Educational Technology, 2(1), 31.
Lewis, A. D., Huebner, E. S., Malone, P. S., & Valois, R. F. (2011). Life satisfaction and student engagement in adolescents. Journal of Youth and Adolescence, 40(3), 249–262. https://doi.org/10.1007/s10964-010-9517-6
Liao, H. L., & Lu, H. P. (2008). The Role of Experience and Innovation Characteristics in the Adoption and Continued Use of E-Learning Websites. Computers and Education, 51, 1405-1416. http://dx.doi.org/10.1016/j.compedu.2007.11.006
Liao, J. J., Chung, K. J., & Huang, K. N. (2013). A Deterministic Inventory Model for Deteriorating Items with Two Warehouses and Trade Credit in a Supply Chain System. International Journal of Production Economics, 146, 557-565. https://doi.org/10.1016/j.ijpe.2013.08.001
Lin, W. S., & Wang, C. H. (2012). Antecedences to continued intentions of adopting e- learning system in blended learning instruction: A contingency framework based on models of information system success and task-technology fit. Computers & Education, 58(1), 88-99. https://doi.org/10.1016/j.compedu.2011.07.008
Locke, E. A. (1969). Handbook of industrial and organizational psychology (1st ed.). John Wiley of Sons.
Martin, F., & Bolliger, D. U. (2018). Engagement matters: student perceptions on the importance of engagement strategies in the online learning environment. Online Learning, 22(1), 205-222. https://doi.org/10.24059/olj.v22i1.1092
Min, Y., Huang, J., Varghese, M. M., & Jaruwanakul, T. (2022). Analysis of Factors Affecting Art Major Students’ Behavioral Intention of Online Education in Public Universities in Chengdu. AU-GSB E-JOURNAL, 15(2), 150-158. https://doi.org/10.14456/augsbejr.2022.80
MIT Sloan Management. (2022, December 25). Our summer 2022 issue addresses C-suite turnover, end user AI anxiety, and employee motivation. https://sloanreview.mit.edu/issue/2022-summer/
Mosher, R., & McGowan, B. (1985). Assessing student engagement in secondary schools: Alternative conceptions, strategies of assessing, and instruments (1st ed.). University of Wisconsin. Research and Development Center.
Mulligan, N. W., Smith, S. A., & Buchin, Z. L. (2019). The generation effect and experimental design. Journal of Experimental Psychology: Learning, Memory, and Cognition, 45(8), 1422–1431. https://doi.org/10.1037/xlm0000663
Parasuraman, A. (2000). Technology readiness index (TRI): A multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307-320. https://doi.org/10.1177/109467050024001
Pedroso, R., Zanetello, L., Guimarães, L., Pettenon, M., Gonçalves, V., Scherer, J., & Pechansky, F. (2016). Confirmatory factor analysis (CFA) of the crack use relapse scale (CURS). Archives of Clinical Psychiatry (São Paulo), 43, 37-40.
Rashmi, T. R. (2021). Information security breaches due to ransomware attacks-a systematic literature review. International Journal of Information Management Data Insights, 1(2), 100013.
Roblyer, M. D., & Knezek, G. A. (2003). New millennium research for educational technology: A call for a national research agenda. Journal of research on Technology in Education, 36(1), 60-71. https://doi.org/10.1080/15391523.2003.10782403
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
Saadé, R. G., & Kira, D. (2009). Computer anxiety in e-learning: The effect of computer self-efficacy. Journal of Information Technology Education: Research, 8(1), 177-191. https://doi.org/10.28945/166
Saba, A. H. (2020). Participatory culture and reinvention of everyday life, international webinar. Post-Pandemic, Participation Matters, 1(2), 1-10.
Salas, E., Dickinson, T. L., Converse, S. A., & Tannenbaum, S. I. (1992). Toward an understanding of team performance and training. In R. W. Swezey & E. Salas (Eds.), Teams: Their training and performance (pp. 3–29). Ablex Publishing.
Sharma, G. P., Verma, R. C., & Pathare, P. B. (2005). Thin-layer infrared radiation drying of onion slices. Journal of Food Engineering, 67(3), 361-366.
Shen, L. J., Wang, J. M., & Li, P. (2013). The Changes and Influencing Factors of Wuhan Atmospheric Visibility and Aerosol in January 2013. 2013 Chinese Environmental Science Conference, 5, 4661-4667.
Shih, H. P. (2006). Assessing the effects of self-efficacy and competence on individual satisfaction with computer use: an IT student perspective. Computers in Human Behavior, 22(6), 1012-1026. https://doi.org/10.1016/j.chb.2004.03.025
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.
Slavin, R. E. (1980). Cooperative learning. Review of educational research, 50(2), 315. https://doi.org/10.2307/1170149
Sterling, K. (2015). Student Satisfaction with Online Learning (1st ed.). UC Santa Barbara.
Tahereh, H., Hosseini, F. A., & Behzad, G. (2021). The relationship between critical thinking, self-regulation, and teaching style preferences among EFL teachers: A path analysis approach. Journal of Language and Education, 7(25), 96-108.
Tannenbaum, S. I., Beard, R. L., & Salas, E. (1992). Team building and its influence on team effectiveness: An examination of conceptual and empirical developments. In K. Kelley (Ed.), Issues, theory, and research in industrial/organizational psychology (pp. 117-153). Amsterdam: Elsevier. http://dx.doi.org/10.1016/S0166-4115(08)62601-1
Thiruchelvi, A., Karthikeyan, N., & Karthik, S. (2019). Energy Aware Sink Relocation and Routing to Extend Network Lifetime in Wireless Sensor Network. Sensor Letters, 17(6), 456-469. https://doi.org/10.1166/sl.2019.4090
Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision sciences, 27(3), 451-481. https://doi.org/10.1111/j.1540-5915.1996.tb01822.x
Wageman, R., & Baker, G. (1997). Incentives and cooperation: The joint effects of task and reward interdependence on group performance. Journal of Organizational Behavior, 18(2), 139–158. https://doi.org/10.1002/(SICI)1099-1379(199703)18:2<139::AID-JOB791>3.0.CO;2-R
Webster, J., & Hackley, P. (1997). Teaching effectiveness in technology-mediated distance learning. Academy of Management Journal, 40(6), 1282-1309. https://doi.org/10.5465/257034
Womble, J. C. (2007). E-learning: The relationship among learner satisfaction, self-efficacy, and usefulness (1st ed.). Alliant International University
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
Young, N. D., Debelle, F., & Roe, B. A. (2011). The Medicago genome provides insight into the evolution of rhizobial symbioses. Nature, 480, 520–524
Zhai, Y., Lin, Q., Zhou, X., Zhang, X., Liu, T., & Yu, Y. (2014). Identification and validation of reference genes for quantitative real-time PCR in Drosophila suzukii (Diptera: Drosophilidae). PLoS One, 9(9), e106800. https://doi.org/10.1371/journal.pone.0106800
Zhang, X., De Pablos, P. O., & Zhang, Y. (2012). The relationship between incentives, explicit and tacit knowledge contribution in online engineering education project. International Journal of Engineering Education, 28(6), 1341.
Zmuda, N. (2021, August 12). Year in Search: 2021 self-improvement trends. https://www.thinkwithgoogle.com /consumer-insights/consumer-trends/2021-self-impr ovement-trends/