Examing Determinants of High School Students’ Satisfaction and Learning Outcome in Heilongjiang, China

Authors

  • Ji Shi

DOI:

https://doi.org/10.14456/au-ejir.2025.1
CITATION
DOI: 10.14456/au-ejir.2025.1
Published: 2025-04-25

Keywords:

Student Satisfaction, High School Education, Academic Staff Quality, School Facilities, Heilongjiang Province

Abstract

Purpose: This study aims to examine the factors influencing the satisfaction of 4th-year high school students in Heilongjiang Province, China. Gaining insights into these factors will help improve the overall quality of education and student experience. Research design, data and methodology: A quantitative research design was employed, using survey data collected from a sample of 550 male 4th-year high school students in Heilongjiang Province. The questionnaire assessed variables such as the quality of academic staff, school facilities, curriculum relevance, and student support services. Structural equation modeling (SEM) was used to analyze the relationships between these factors and student satisfaction. Results: The analysis has shown that all proposed factors positive influence overall satisfaction, by having student support services, school’s reputation, and the quality of programs as the greatest contributors. The research framework demonstrated strong reliability, with factor loadings and goodness-of-fit indices meeting acceptable thresholds. Conclusions: The findings suggest that improving access to resources, enhancing academic programs, and building institutional reputation are key strategies for increasing both student satisfaction and learning outcomes in high schools. Educational policymakers should focus on these areas to foster a more engaging and fulfilling learning experience for students.

Author Biography

Ji Shi

School of graduate school of business and advanced technology management, Assumption University, Thailand.

References

Adam, S. (2008). Learning outcomes: Current developments in Europe: Update on the issues and applications of learning outcomes associated with the Bologna Process. European Higher Education Area.

Adeyemi, J. K., & Uko-Aviomoh, E. E. (2004). Effective technological delivery in Nigerian polytechnics: Need for academic manpower development policy. Education Policy Analysis Archives, 12(24), 1-15.

https://doi.org/10.14507/epaa.v12n24.2004

Altbach, P. G., Reisberg, L., & Rumbley, L. E. (2014). The globalization of higher education: Education and globalization. Springer.

Awang, Z. (2012). Research methodology and data analysis second edition. UiTM Press.

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

Biggs, J., & Tang, C. (2011). Teaching for quality learning at university: What the student does (4th ed.). McGraw-Hill Education.

Brooks, D. C. (2011). Space matters: The impact of formal learning environments on student learning. British Journal of Educational Technology, 42(5), 719-726. https://doi.org/10.1111/j.1467-8535.2010.01098.x

Douglas, J., Douglas, A., & Barnes, B. (2006). Measuring student satisfaction at a UK university. Quality Assurance in Education, 14(3), 251-267. https://doi.org/10.1108/09684880610678568

Elliott, K. M., & Shin, D. (2002). Student satisfaction: An alternative approach to assessing this important concept. Journal of Higher Education Policy and Management, 24(2), 197-209. https://doi.org/10.1080/1360080022000013518

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

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis (7th ed.). Pearson.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). SAGE Publications.

Hazelkorn, E. (2015). Rankings and the reshaping of higher education: The battle for world-class excellence. Palgrave Macmillan.

Hill, M. C., & Epps, K. K. (2010). The impact of physical classroom environment on student satisfaction and student evaluation of teaching in the university environment. Academy of Educational Leadership Journal, 14(4), 65-79.

Hossler, D., Schmit, J., & Vesper, N. (1999). Going to college: How social, economic, and educational factors influence the decisions students make. Johns Hopkins University Press.

Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). The Guilford Press.

Kuh, G. D., Kinzie, J., Buckley, J. A., Bridges, B. K., & Hayek, J. C. (2011). Piecing together the student success puzzle: Research, propositions, and recommendations. ASHE Higher Education Report, 36(6), 1-144.

https://doi.org/10.1002/aehe.3606

Kuh, G. D., Kinzie, J., Schuh, J. H., & Whitt, E. J. (2005). Student success in college: Creating conditions that matter. John Wiley & Sons.

Li, J., Li, S., & Li, X. (2019). Challenges and opportunities in improving student satisfaction in Chinese higher education. Journal of Higher Education Policy and Management, 41(6), 570-583. https://doi.org/10.1080/1360080X.2019.1670938

Marginson, S. (2014). University rankings and social science. European Journal of Education, 49(1), 45-59.

https://doi.org/10.1111/ejed.12055

Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students: A third decade of research. Jossey-Bass.

Pedroso, B., Pilatti, L. A., Gutierrez, G. L., & Picinin, C. T. (2016). Measurement model for innovation management assessment in the Brazilian automotive industry. International Journal of Innovation, 4(2), 71-84. https://doi.org/10.5585/iji.v4i2.107

Selwyn, N. (2014). Digital technology and the contemporary university: Degrees of digitization. Routledge.

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. https://doi.org/10.1016/j.jbusres.2003.10.007

Sica, C., & Ghisi, M. (2007). The Italian versions of the Beck Anxiety Inventory and the Beck Depression Inventory-II: Psychometric properties and discriminant power. Psychological Reports, 101(2), 521-532.

https://doi.org/10.2466/pr0.101.2.521-532

Teixeira, P. N., & Koryakina, A. (2013). Improving university reputation through global partnerships, research excellence, and innovative teaching. Higher Education Review, 42(3), 157-174. https://doi.org/10.1007/s11579-013-0248-7

Thomas, L., & Quinn, J. (2007). First generation entry into higher education: An international study. Open University Press.

Umbach, P. D., & Wawrzynski, M. R. (2005). Faculty do matter: The role of college faculty in student learning and engagement. Research in Higher Education, 46(2), 153-184.

https://doi.org/10.1007/s11162-004-1598-1

Voorhees, C. M., Brady, M. K., Calantone, R., & Ramirez, E. (2016). Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44(1), 119-134.

https://doi.org/10.1007/s11747-015-0455-4

Wong, L. P. W., Leung, P. K. K., & Chan, K. W. C. (2015). The effect of university ranking on graduate starting salary in Hong Kong. Education + Training, 57(8/9), 936-951.

https://doi.org/10.1108/ET-02-2015-0011

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

Zhang, Y., Xiong, W., Yuan, C., & Yu, C. (2022). Analysis of student satisfaction in Chinese universities: Influencing factors and improvement strategies. Frontiers in Psychology, 13, 1023420. https://doi.org/10.3389/fpsyg.2022.1023420

Downloads

Published

2025-04-25

How to Cite

Shi, J. (2025). Examing Determinants of High School Students’ Satisfaction and Learning Outcome in Heilongjiang, China. Journal of Interdisciplinary Research (ISSN: 2408-1906), 10(1), 1-9. https://doi.org/10.14456/au-ejir.2025.1