| Literature DB >> 36193387 |
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.Entities:
Mesh:
Year: 2022 PMID: 36193387 PMCID: PMC9525802 DOI: 10.1155/2022/7605593
Source DB: PubMed Journal: J Environ Public Health ISSN: 1687-9805
Figure 1Neuron model.
Specific content table of music instructional level assessment index system.
| Primary index | Secondary index |
|---|---|
| Instructional attitude | Rigorous lesson preparation and complete lesson plan |
| Correct homework and tutor students | |
|
| |
| Instructional ability | Systematization of content |
| Complex problems are clearly expressed | |
| Integrating theory with practice | |
| Auxiliary instructional means | |
| Treatment of key and difficult points | |
| Language and writing on the blackboard | |
| Mobilize students' enthusiasm | |
|
| |
| Instructional content | Proper selection of content |
| Accurate and clear concept | |
| Give prominence to the key points | |
|
| |
| Instructional method | Flexible method |
| Pay attention to inspiration and ability. | |
| Pay attention to communication and interaction with students | |
|
| |
| Instructional and educating people | Teach and educate people, be a teacher by example |
| Be strict and fair to students | |
|
| |
| Instructional effect | Students master all knowledge points. |
| Improve students' comprehensive ability | |
|
| |
| Student assessment | Students' mutual assessment |
| Supervision and assessment | |
| Teachers' assessment of learning | |
| Student self-assessment | |
|
| |
Figure 2BPNN model structure.
Figure 3Training of the network.
Figure 4MSE situation of algorithm.
Figure 5RMSE situation of algorithm.
Figure 6MAE situation of algorithm.
Figure 7Assessment accuracy of different algorithms.
Experimental results of each index of the algorithm.
| Algorithm | MSE | RMSE | MAE | Assessment accuracy |
|---|---|---|---|---|
| Traditional NN | 0.115 | 0.324 | 0.582 | 0.831 |
| Traditional genetic algorithm | 0.109 | 0.309 | 0.547 | 0.842 |
|
| 0.095 | 0.287 | 0.578 | 0.865 |
| Methods of this paper | 0.071 | 0.245 | 0.523 | 0.961 |
Comparison between NN training results and actual assessment results.
| Algorithm | 1 | 1 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|
| Expert assessment | 0.784 | 0.859 | 0.859 | 0.761 | 0.912 | 0.854 |
| Network assessment | 0.790 | 0.862 | 0.866 | 0.754 | 0.916 | 0.857 |