Factors Influencing the Quality of Higher Vocational Education in Chengdu during the COVID-19

Authors

  • Jian Feng

DOI:

https://doi.org/10.14456/shserj.2024.28
CITATION
DOI: 10.14456/shserj.2024.28
Published: 2024-08-20

Keywords:

Quality, Higher Education, Satisfaction, Loyalty, COVID-19

Abstract

Purpose: The purpose of this study is to explore the key factors that significantly influence the teaching quality of four different types of higher vocational colleges in the Chengdu region after the novel coronavirus epidemic. The conceptual framework proposed a causal relationship among academic aspects, reputation, information quality, instructor quality, perceived value, satisfaction, and loyalty. Research design, data, and methodology: The research approach utilized in this study was quantitative, with a sample size of 500 third-year students from various higher vocational colleges. A multistage sampling method was employed, which included judgmental sampling for selection, stratified random sampling for determining the number of students, and convenient sampling for data collection and online/offline survey dissemination. The data analysis used Structural Equation Model (SEM) and Confirmatory Factor Analysis (CFA) techniques to evaluate construct validity, reliability, and model fit. Results: The findings of this investigation demonstrated that reputation, information quality, instructor quality, and perceived value significantly influence satisfaction and loyalty, while the impact of academic aspects was found to be insignificant. Conclusions: Schools should not blindly invest in academic research but should focus more on the teaching interaction between students and teachers, the application of information technology in school management and the teaching process, and improving students' skills in school.

Author Biography

Jian Feng

Sichuan Post and Telecommunication College, China.

References

Abdullah, F. (2005). HEdPERF versus SERVPERF: the quest for ideal measuring instrument of service quality in higher education sector. Quality Assurance in Education, 13(4), 305-328. https://doi.org/10.1108/09684880510626584

AbuSeman, S. A., Hashim, M. J., Mohd Roslin, R., & Mohd Ishar, N. I. (2019). Millennial Learners’ Acceptance and Satisfaction of Blended Learning Environment. Asian Journal of University Education, 15(3), 129-141.

https://doi.org/10.24191/ajue.v15i3.04

Ali, F., Zhou, Y., Hussain, K., Nair, P. K., & Ragavan, N. A. (2016). Does higher education service quality effect student satisfaction, image, and loyalty? A study of international students in Malaysian public universities. Quality assurance in education, 24(1), 70-94. https://doi.org/10.1108/qae-02-2014-0008

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

Angell, R. J., Heffernan, T. W., & Megicks, P. (2008). Service quality in postgraduate education. Quality Assurance in Education, 16(3), 236-54. https://doi.org/10.1108/09684880810886259

Annamdevula, S., & Bellamkonda, R. S. (2016). Effect of student perceived service quality on student satisfaction, loyalty, and motivation in Indian universities. Journal of Modelling in Management, 11(2), 488-517.

https://doi.org/10.1108/jm2-01-2014-0010

Ataburo, H., Muntaka, A. S., & Quansah, E. K. (2017). Linkages among e-service quality, satisfaction, and usage of e-services within higher educational environments. International Journal of Business and Social Research, 7(3), 10-26.

https://doi.org/10.18533/ijbsr.v7i3.1040

Athiyaman, A. (1997). Linking student satisfaction and service quality perceptions: the case of university education. European journal of marketing, 31(7), 528-540. https://doi.org/10.1108/03090569710176655

Awang, Z. (2012). Structural equation modeling using AMOS graphic. Penerbit University Technology 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

Besseah, B., Achiro, D., Mhando, J., & Salau, S. A. (2017). Embedding digital and research-literacy support program into postgraduate studies curriculum: a proposed program for Sub-Saharan African postgraduate schools. Library Review, 66(8-9), 586-594. https://doi.org/10.1108/lr-02-2017-0012

Bharatia, P., & Chaudhury, A. (2004). An empirical investigation of decision-making satisfaction in web-based decision support systems. Decision support systems, 37(2), 187-197. https://doi.org/10.1016/s0167-9236(03)00006-x

Bhattacharya, C. B., & Elsbach, K. D. (2002). Us versus them: The roles of organizational identification and disidentification in social marketing initiatives. Journal of Public Policy & Marketing, 21(1), 26-36.

https://doi.org/10.1509/jppm.21.1.26.17608

Bromley, D. B. (2002). An examination of issues that complicate the concept of reputation in business studies. International Studies of Management & Organization, 32(3), 65-81. https://doi.org/10.1080/00208825.2002.11043666

Camp, W. G. (2001). Formulating and Evaluating Theoretical Frameworks for Career and Technical Education Research. Journal of Vocational Education Research, 26(1), 4-25. https://doi.org/10.5328/jver26.1.4

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

Chen, Y. S., & Chang, C. H. (2013). Green organizational identity's influence on green innovation. Social Behavior and Personality: an international journal, 41(8), 1297-1304. https://doi.org/10.1108/md-09-2011-0314

Clemes, M. D., Cohen, D. A., & Wang, Y. (2013). Understanding Chinese university students' experiences: an empirical analysis. Asia Pacific Journal of Marketing and Logistics, 25(3), 391-427. https://doi.org/10.1108/apjml-07-2012-0068

Deephouse, D. L. (2000). Media reputation as a strategic resource: An integration of mass communication and resource-based theories. Journal of management, 26(6), 1091-1112. https://doi.org/10.1177/014920630002600602

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.

Demir, A., Pesque-Cela, V., Altunbas, Y., & Murinde, V. (2020). Fintech, financial inclusion, and income inequality: a quantile regression approach. European Journal of Finance, 28(2), 1-22. https://doi.org/10.1080/1351847x.2020.1772335

Demiray, U., & Sharma, R. C. (2015). MOOCs: A Review of the State-of-the-Art. Eurasia Journal of Mathematics, Science & Technology Education, 11(5), 993-1006. https://doi.org/10.12973/eurasia.2015.1389a

Demirgünescedil, B. K. (2015). Relative importance of perceived value, satisfaction, and perceived risk on willingness to pay more. International Review of Management and Marketing, 5(4), 211-220.

Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological Bulletin, 125(2), 276-302. https://doi.org/10.1037/0033-2909.125.2.276

Dlačić, J., Arslanagić, M., Kadić-Maglajlić, S., Marković, S., & Raspor, S. (2014). Exploring perceived service quality, perceived value, and repurchase intention in higher education using structural equation modelling. Total Quality Management & Business Excellence, 25(1-2), 141-157. https://doi.org/10.1080/14783363.2013.824713

Ducharme, J. (2020). World Health Organization Declares COVID-19 a 'Pandemic.' Time. https://time.com/5791661/who-coronavirus-pandemic-declaration/

El-Adly, M. I., & Eid, R. (2016). Factors affecting students’ satisfaction and achievement in electronic learning environments: A review of the literature. Journal of Education and Practice, 7(3), 78-88.

Fernandes, C., & Ross, K. (2013). Understanding student satisfaction and loyalty in the UAE HE sectors. International Journal of Educational. 27(6), 613-630. https://doi.org/10.1108/ijem-07-2012-0082

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

Ghazal, S., Aldowah, H., & Umar, I. (2017). Critical Factors to Learning Management System Acceptance and Satisfaction in a Blended Learning Environment. In F. Saeed, N. Gazem, S. Patnaik, A. S. S. Balaid & F. Mohammed (Eds.), Research Trends in Information and Communication Technology, Lecture Notes on Data Engineering and Communication Technologies (pp. 688-698). Springer. https://doi.org/10.1007/978-3-319-59427-9_71

Greenspoon, P. J., & Saklofske, D. H. (1998). Confirmatory factor analysis of the multidimensional students' life satisfaction scale. Personality and Individual Differences 25(5), 965-972. https://doi.org/10.1016/s0191-8869(98)00115-9

Hair, J. F., Anderson, R. E., Babin, B. J., & Black, W. C. (2010). Multivariate data analysis: A global perspective (7th ed.). Pearson Prentice Hall.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed). Pearson Prentice Hall.

Hakanen, J. J., Bakker, A. B., & Schaufeli, W. B. (2006). Burnout and work engagement among teachers. Journal of School Psychology, 43(6), 495-513. https://doi.org/10.1016/j.jsp.2005.11.001

Huili, Y. A. O., & Jing, Y. U. (2012). Empirical research and model building about customer satisfaction index on postgraduate education service quality. Canadian Social Science, 8(1), 108-113.

Imenda, S. (2017). In Search of a Psychology of Teaching and Learning for the 21st Century. Journal of Psychology, 8(2), 83-94. https://doi.org/10.1080/09764224.2017.1409330

Jiewanto, A., Laurens, C., & Nelloh, L. (2012). Influence of service quality, university image, and student satisfaction toward WOM intention: A case study on Universitas Pelita Harapan Surabaya. Procedia-Social and Behavioral Sciences, 40, 16-23.

https://doi.org/10.1016/j.sbspro.2012.03.155

Jiménez-Castillo, D., Sánchez-Fernández, R., & Iniesta-Bonillo, M. Á. (2013). Segmenting university graduates on the basis of perceived value, image, and identification. International Review on Public and Nonprofit Marketing, 10(3), 235-252. https://doi.org/10.1007/s12208-013-0102-z

Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). Guilford Press.

Lee, S. J., Lee, H., & Kim, T. T. (2018). A study on the instructor role in dealing with mixed contents: How it affects learner satisfaction and retention in e-learning. Sustainability, 10(3), 850. https://doi.org/10.3390/su10030850

Liaw, S.-S., & Huang, H.-M. (2013). Perceived satisfaction, perceived usefulness, and interactive learning environments as predictors to self-regulation in e-learning environments. Computers & Education, 60(1), 14-24.

https://doi.org/10.1016/j.compedu.2012.07.015

Liguori, E., & Winkler, C. (2020). From offline to online: Challenges and opportunities for entrepreneurship education following the COVID-19 pandemic. Entrepreneurship Education and Pedagogy, 3(4), 346-351.

Liu, M., Kang, J., & Wu, X. (2019). Use of educational technology in higher education: A mixed-methods systematic review. Journal of Educational Technology & Society, 22(2), 1-14.

Manohar, S., Mittal, A., & Marwah, S. (2019). Service innovation, corporate reputation, and word-of-mouth in the banking sector: a test on multigroup-moderated mediation effect. Benchmarking: An International Journal, 27(1), 406-429. https://doi.org/10.1108/bij-05-2019-0217

Mao, V., & Zhang, B. (2020, February 18). New business opportunities emerging in China under COVID-19 outbreak. China Briefing. https://www.china-briefing.com/news/china-business-opportunities-covid-19-outbreak/

McGaghie, W. C., Bordage, G., & Shea, J. A. (2001). Problem Statement, Conceptual Framework, and Research Question. Academic Medicine, 76(9), 923-924. https://doi.org/10.1097/00001888-200109000-00021

Mewburn, I., & Thomson, P. (2013). Why do academics blog? An analysis of audiences, purposes, and challenges. Studies in Higher Education, 38(8), 1105-1119. https://doi.org/10.1080/03075079.2013.835624

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

Momen, M. A., Sultana, S., & Haque, A. K. M. A. (2019). Web-based marketing communication to develop brand image and brand equity of higher educational institutions: A structural equation modelling approach. Global Knowledge, Memory and Communication, 69(3), 151-169. https://doi.org/10.1108/gkmc-10-2018-0088

Mtebe, J. S., & Raphael, C. (2018). Key factors in learners’ satisfaction with the e-learning system at the University of Dar es Salaam, Tanzania. Australasian Journal of Educational Technology, 34(4), 107-122. https://doi.org/10.14742/ajet.2993

Nguyen, N., & LeBlanc, G. (2001). Image and reputation of higher education institutions in students’ retention decisions. International journal of educational management, 15(6), 303-311. https://doi.org/10.1108/eum0000000005909

Nitzan, I., & Libai, B. (2011). Social effects on customer retention. Journal of marketing, 75(6), 24-38.

https://doi.org/10.1509/jm.10.0209

Oliver, R. L. (1997). Satisfaction: A Behavioral Perspective on the Consumer (1st ed.). The McGraw-Hill Companies.

Panda, S., Pandey, S. C., Bennett, A., & Tian, X. (2019). University brand image as competitive advantage: a two-country study. International Journal of Educational Management, 33(2), 234-251. https://doi.org/10.1108/ijem-12-2017-0374

Pedroso, R., Zanetello, L., Guimarães, L., Pettenon, M., Gonçalves, V., Scherer, J., Kessler, F., & Pechansky, F. (2016). Confirmatory factor analysis (CFA) of the Crack Use Relapse Scale (CURS). Archives of Clinical Psychiatry (São Paulo), 43(3), 37-40. https://doi.org/10.1590/0101-60830000000081

Plano Clark, V. L. (2017). Mixed methods research. The Journal of Positive Psychology, 12(3), 305-306.

https://doi.org/10.1080/17439760.2016.1262619

Record Trend. (2022, May 31). 2020 Digital China Development Report from State Network Information Office. https://recordtrend.com/industry-information/2020-digital-china-development-report-from-state-network-information-office/

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

Rowley, J. (1996). Measuring Quality in Higher Education. Quality in Higher Education, 2(3), 237-255.

https://doi.org/10.1080/1353832960020306

Rowley, J. (1996). Motivation and academic staff in higher education. Quality Assurance in Education, 4, 11-16.

https://doi10.1108/09684889610125814.

Rughoobur-Seetah, S., & Hosanoo, Z. A. (2021). An evaluation of the impact of confinement on the quality of e-learning in higher education institutions. Quality Assurance in Education, 29(4), 422-444. https://doi.org/10.1108/qae-03-2021-0043

Seok, S. (2008). Teaching aspects of e-learning. International journal on e-learning, 7(4), 725-741.

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

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

Snoj, B., Korda, A. P., & Mumel, D. (2004). The relationships among perceived quality, perceived risk, and perceived product value. Journal of Product & Brand Management, 13(3), 156-167. https://doi.org/10.1108/10610420410538050

Sultan, P., & Wong, H. Y. (2013). Antecedents and consequences of service quality in a higher education context. Quality Assurance in Education, 21(1), 70-95.

Thomas, E. H., & Galambos, N. (2004). What satisfies students? Mining student-opinion data with regression and decision tree analysis. Research in Higher Education, 45(3), 251-269. https://doi.org/10.1023/b:rihe.0000019589.79439.6e

Vovides, Y., Sanchez-Alonso, S., Mitropoulos, P., Nickmans, G., Dogba, M. J., & Sales, D. (2019). Digital technologies in medical education: A paradigm shift from a teacher disseminating knowledge to a facilitator assisting the development of learning networks. Medical Teacher, 41(10), 1117-1121.

Wang, K., & Lin, C. L. (2012). The adoption of mobile value‐added services: Investigating the influence of IS quality and perceived playfulness. Managing Service Quality, 22(2), 184-208.

Wang, Q., & Chen, L. (2009). Educational podcasting: A feasibility study using iTunes. Computers & Education, 52(1), 315-327. https://doi.org/10.1016/j.compedu.2008.08.013

World Health Organization. (2020, March 12). Statement on the second meeting of the international health regulations. https://www.who.int/news-room/detail/30-01-2020-statement-on-the-second-meeting-of-the-international-health-regulations-%282005%29-emergency-committee-regarding-theoutbreak-of-novel-coronavirus-%282019-ncov%29

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

Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. Journal of marketing, 52(3), 2-22. https://doi.org/10.2307/1251446

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2024-08-20

How to Cite

Feng, J. (2024). Factors Influencing the Quality of Higher Vocational Education in Chengdu during the COVID-19. Scholar: Human Sciences, 16(2), 10-20. https://doi.org/10.14456/shserj.2024.28