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Volume 3,Issue 9

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26 October 2025

Construction and Practice Optimization of the Teaching Quality Management System for Music Courses in Higher Education

Fang Liu*
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1 Centro Escolar University, 9 Mendiola Street, San Miguel, Manila City 1005, Philippines
LNE 2025 , 3(9), 73–78; https://doi.org/10.18063/LNE.v3i9.961
© 2025 by the Author. Licensee Whioce Publishing, Singapore. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract

As the core carrier of aesthetic education, music courses in universities directly affect the cultivation of students’ aesthetic literacy and artistic practical abilities. Currently, the teaching quality management of university music courses is plagued by issues such as vague standards, loose processes, and simplistic evaluation methods, which restrict the continuous improvement of teaching quality. This paper constructs four core modules, “Goal Setting, Process Control, Evaluation Feedback, and Continuous Optimization,” designs a multi-dimensional quality management evaluation system, and verifies the effectiveness of the system through practical implementation paths.

Keywords
University music courses
Teaching quality management system
Construction
Practical optimization
References

[1] Yang D, Zhu W, Liu Y, et al, 2018, Method and Path Selection for Optimization and Promotion of Teaching Quality of Applied Courses–Taking Steel Structure Course as an Example. Educational Sciences: Theory & Practice, 18(6): 2742–2749.

[2] Liu J, Wang C, Wu Y, 2021, Construction and Optimization of Higher Education Management System Based on Internet Video Online Technology. Scientific Programming, 2021: 1–11.

[3] Li G, Zhao F, 2019, A Teaching Reform and Practice of Small-Class System in Optional Courses of Engineering Postgraduates. ICEDEM, 2019: 269–272.

[4] Ji C, Dong M, Li D, et al, 2025, Research on the Path to Improve the Teaching Ability of College Teachers Based on Artificial Intelligence. LatIA, 3(3): 135.

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