Comprehensive Evaluation of Music Course Teaching Level Based on Improved Multi-attribute Fuzzy Evaluation Model

Authors

  • Liuqing Yang Henan Radio & Television University, Zhengzhou, China

DOI:

https://doi.org/10.3991/ijet.v15i19.17411

Abstract


Aiming at the problems of multi-attribute fuzzy information and imperfect evaluation system existing in the current evaluation process of music course teaching level, the paper studies the multi-attribute fuzzy evaluation of music course teaching level, analyzes the influencing factors of music course teaching level, and establishes an improved music course teaching level evaluation system; then on this basis, combining with the fuzzy system theory, grey system theory and entropy weight method, it proposes a multi-attribute fuzzy evaluation model of music course teaching level to realize the quantitative analysis of music course teaching level, which has good engineering application value. At the same time, the paper also puts forward some strategies and suggestions to improve the teaching level of music courses, which are of good guidance and reference significance for improving the teaching quality of music courses.

Author Biography

Liuqing Yang, Henan Radio & Television University, Zhengzhou, China

Liuqing Yang, female (1986.06-), graduated from Henan University with a master's degree in art. She is currently working as a lecturer at Henan Radio & Television University. Her research directions include music functions, music talent training, music teaching methods, etc. In terms of scientific research: she has published 9 papers, participated in editing 2 textbooks, 1 book, presided over 4 department-level projects, and has 1 utility model patent. In terms of teaching: she won the provincial second prize in the teaching skills competition, and has guided students to participate in provincial competitions and won many awards.

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Published

2020-10-05

How to Cite

Yang, L. (2020). Comprehensive Evaluation of Music Course Teaching Level Based on Improved Multi-attribute Fuzzy Evaluation Model. International Journal of Emerging Technologies in Learning (iJET), 15(19), pp. 107–121. https://doi.org/10.3991/ijet.v15i19.17411

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Section

Papers