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基于神经网络的大学音乐教育发展与能力教育环境下师范院校音乐教育改革。

Development of University Music Education Based on Neural Network and the Reform of Music Education in Normal University under the Environment of Ability Education.

机构信息

Xuzhou University of Technology, Xuzhou 221000, China.

出版信息

J Environ Public Health. 2022 Sep 23;2022:7605593. doi: 10.1155/2022/7605593. eCollection 2022.

Abstract

Competency education has grown in importance as a component of music education in teachers' colleges in the modern era. This essay conducts a thorough investigation into the evolution of college music education and the reform of music education at teachers' universities based on the notion of competency education. This essay highlights the crucial role that music education plays in competence education, with aesthetics at its center. It also examines the crucial part that music education plays in developing college students' all-round abilities. This study evaluates the reform process and current state of the music education curriculum system in teachers' universities based on these factors as well as the development trend of modern music curriculum reform, and it suggests various reform avenues. Additionally, a model for assessing the degree of music instruction is built in this research using the NN (Neural network) technique. This work employs MATLAB for empirical research in order to validate the validity of the method. According to experimental findings, this algorithm's evaluation accuracy can reach 96.11%, which is almost 13% greater than that of the conventional NN technique. The outcomes demonstrate the accuracy and dependability of this methodology. This study is intended to serve as a reference for the advancement of collegiate music education as well as the reform and innovation of music in teacher education programs.

摘要

能力本位教育在现代师范院校音乐教育中日益重要。本文以能力本位教育理念为基础,对高校音乐教育和师范院校音乐教育改革进行了深入研究。本文强调了音乐教育在能力本位教育中的核心地位,以美学为中心。本文还探讨了音乐教育在培养大学生全面能力方面的重要作用。本研究基于这些因素以及现代音乐课程改革的发展趋势,对师范院校音乐教育课程体系的改革过程和现状进行了评价,并提出了各种改革途径。此外,本研究还利用神经网络(NN)技术构建了音乐教学程度评估模型。本研究采用 MATLAB 进行实证研究,以验证该方法的有效性。根据实验结果,该算法的评估准确率可达 96.11%,比传统的神经网络技术高出近 13%。研究结果表明了该方法的准确性和可靠性。本研究旨在为高校音乐教育的发展以及师范院校音乐教育的改革与创新提供参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e532/9525802/b7e3c7cfe0e8/JEPH2022-7605593.001.jpg

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