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Influence and Analysis of Music Teaching Environment Monitoring on Students' Mental Health Using Data Mining Technology
Students currently mostly experience psychological issues like worry and fear, which are primarily brought on by the high demands placed on them. One psychotherapy technique is music therapy. The goal is to use music to enhance health, particularly as a tool to break down barriers both inside and ou...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9560828/ https://www.ncbi.nlm.nih.gov/pubmed/36246468 http://dx.doi.org/10.1155/2022/1120156 |
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author | Dong, Xinlei Kang, Xin Ding, Xiaolei |
author_facet | Dong, Xinlei Kang, Xin Ding, Xiaolei |
author_sort | Dong, Xinlei |
collection | PubMed |
description | Students currently mostly experience psychological issues like worry and fear, which are primarily brought on by the high demands placed on them. One psychotherapy technique is music therapy. The goal is to use music to enhance health, particularly as a tool to break down barriers both inside and outside the body. Based on data mining (DM) technologies, this paper examines the impact of music education on students' psychological health. The study demonstrates that the DM algorithm utilised in this work has the lowest error rate, with an average error rate of only 6.90%, followed by the ACA method with an average error rate of 17.48%, and finally the AI algorithm with an average error rate of 29.35%. As can be shown, this approach is more suited to research the effects of music instruction on students' psychological well-being. The functional module based on DM is developed through simulation experiments to confirm the application effectiveness of the DM algorithm. This is done by using the data source of DM and the structural model of the mining system to build this module on the foundation of the original psychological evaluation system. |
format | Online Article Text |
id | pubmed-9560828 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-95608282022-10-14 Influence and Analysis of Music Teaching Environment Monitoring on Students' Mental Health Using Data Mining Technology Dong, Xinlei Kang, Xin Ding, Xiaolei J Environ Public Health Research Article Students currently mostly experience psychological issues like worry and fear, which are primarily brought on by the high demands placed on them. One psychotherapy technique is music therapy. The goal is to use music to enhance health, particularly as a tool to break down barriers both inside and outside the body. Based on data mining (DM) technologies, this paper examines the impact of music education on students' psychological health. The study demonstrates that the DM algorithm utilised in this work has the lowest error rate, with an average error rate of only 6.90%, followed by the ACA method with an average error rate of 17.48%, and finally the AI algorithm with an average error rate of 29.35%. As can be shown, this approach is more suited to research the effects of music instruction on students' psychological well-being. The functional module based on DM is developed through simulation experiments to confirm the application effectiveness of the DM algorithm. This is done by using the data source of DM and the structural model of the mining system to build this module on the foundation of the original psychological evaluation system. Hindawi 2022-10-06 /pmc/articles/PMC9560828/ /pubmed/36246468 http://dx.doi.org/10.1155/2022/1120156 Text en Copyright © 2022 Xinlei Dong et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Dong, Xinlei Kang, Xin Ding, Xiaolei Influence and Analysis of Music Teaching Environment Monitoring on Students' Mental Health Using Data Mining Technology |
title | Influence and Analysis of Music Teaching Environment Monitoring on Students' Mental Health Using Data Mining Technology |
title_full | Influence and Analysis of Music Teaching Environment Monitoring on Students' Mental Health Using Data Mining Technology |
title_fullStr | Influence and Analysis of Music Teaching Environment Monitoring on Students' Mental Health Using Data Mining Technology |
title_full_unstemmed | Influence and Analysis of Music Teaching Environment Monitoring on Students' Mental Health Using Data Mining Technology |
title_short | Influence and Analysis of Music Teaching Environment Monitoring on Students' Mental Health Using Data Mining Technology |
title_sort | influence and analysis of music teaching environment monitoring on students' mental health using data mining technology |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9560828/ https://www.ncbi.nlm.nih.gov/pubmed/36246468 http://dx.doi.org/10.1155/2022/1120156 |
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