Operational Mechanisms of Curriculum Quality Monitoring Systems in Higher Education Administration

Authors

  • Yifei Song Lee Shau Kee School of Business Administration Hong Kong Metropolitan University, HongKong, China

DOI:

https://doi.org/10.54097/1jwsq175

Keywords:

Curriculum Quality Monitoring, Higher Education Administration, Operational Mechanisms, Closed-loop Management, Data-driven

Abstract

The curriculum quality monitoring system directly affects the quality of talent cultivation in universities and is a key link in higher education administration. Curriculum quality control in contemporary universities still requires further optimization. Based on this, this paper aligns with the requirements of the Ministry of Education's "Implementation Plan for Undergraduate Teaching Audit and Evaluation in Ordinary Higher Education Institutions (2021-2025)", drawing on the teaching practices of public and application-oriented universities, and integrates relevant theories of Total Quality Management and closed-loop management to focus on analyzing the operational logic of the curriculum quality monitoring system. This paper sorts out the core components of the system, including organizational structure, indicator design, and implementation process. At the same time, this paper draws on the quality assurance practice of Lanzhou University's "One Platform, Four Systems" and summarizes an operational model featuring hierarchical management, diversified evaluation, data-driven support, and continuous improvement. Practice demonstrates that improving this monitoring system can effectively strengthen the control of the entire teaching process, improve talent cultivation quality, and offer practical references for universities to optimize higher education administration and enhance curriculum quality.

Downloads

Download data is not yet available.

References

[1] Nicol, D., Thomson, A., & Breslin, C. (2014). Rethinking feedback practices in higher education: a peer review perspective. Assessment & Evaluation in Higher Education, 39(1), 102–122. https://doi.org/10. 1080/ 02602938. 2013. 787247.

[2] Sallis, E. (2014). Total quality management in education. Routledge. https://doi.org/10.4324/9781315710956.

[3] Hativa, N. (2001). Teaching for effective learning in higher education. Springer Science & Business Media. https://doi.org/ 10.1007/978-94-010-0820-0.

[4] Spooren, P., Brockx, B., & Mortelmans, D. (2013). On the validity of student evaluation of teaching: The state of the art. Review of Educational Research, 83(4), 598–642. https://doi. org/10.3102/0034654313486561.

[5] Morris, R., Perry, T., & Wardle, L. (2021). Formative assessment and feedback for learning in higher education: A systematic review. Review of Education, 9(3), e3292. https://doi.org/10.1002/rev3.3292.

[6] Venkatraman, S. (2007). A framework for implementing TQM in higher education programs. Quality Assurance in Education, 15(1), 92–112. https://doi.org/10.1108/09684880710726842.

[7] Ghedin, E., & Aquario, D. (2008). Moving towards multidimensional evaluation of teaching in higher education: A study across four faculties. Higher Education, 56(5), 583–597. https://doi.org/10.1007/s10734-008-9112-1.

[8] Banihashem, S. K., Noroozi, O., Van Ginkel, S., Macfadyen, L. P., & Biemans, H. J. (2022). A systematic review of the role of learning analytics in enhancing feedback practices in higher education. Educational Research Review, 37, 100489. https://doi.org/10.1016/j.edurev.2022.100489.

[9] Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009.

[10] Jasti, N. V. K., Venkateswaran, V., & Kota, S. (2022). Total Quality Management in higher education: a literature review on barriers, customers and accreditation. The TQM Journal, 34(5), 1250–1272. https://doi.org/10.1108/TQM-08-2021-0240.

[11] Stroebe, W. (2020). Student evaluations of teaching encourages poor teaching and contributes to grade inflation: A theoretical and empirical analysis. Basic and Applied Social Psychology, 42(4), 276–294. https://doi.org/ 10.1080/ 019 73533. 2020.1783797.

Downloads

Published

02-06-2026

Issue

Section

Articles

How to Cite

Song, Y. (2026). Operational Mechanisms of Curriculum Quality Monitoring Systems in Higher Education Administration. Academic Journal of Education, 1(3), 1-4. https://doi.org/10.54097/1jwsq175