Application of big data analysis in optimizing music education

With the rapid development of big data technology, its application in the field of education, especially music education, has become a new research field. This study is dedicated to exploring the application of big data in optimizing music education and evaluating the impact of big data technology on music teaching effectiveness through questionnaires, data analysis and model construction. The questionnaire revealed the attitudes of music teachers and students toward the application of big data, while statistical analysis and model building provided specific insights into the optimization of teaching methods and the enhancement of learning outcomes. The study found that big data technology can promote the development of personalized teaching, optimize teaching strategies, and provide data support for music education decisions. Nevertheless, the study also points out limitations such as sample selection and geographical restrictions, which can be expanded in the future. Overall, this study provides empirical basis and practical guidance for the application of big data technology in music education.

Authors

Publication Details

Journal
Journal of Computational Methods in Sciences and Engineering
Published
2025-01-01
DOI
https://doi.org/10.1177/14727978251321629
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
0.00
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article

Application of big data analysis in optimizing music education

Seung‐Ki Min
Journal of Computational Methods in Sciences and Engineering
E-commerce and Technology Innovations
article

Application of big data analysis in optimizing music education

Seung‐Ki Min
article en

Abstract

With the rapid development of big data technology, its application in the field of education, especially music education, has become a new research field. This study is dedicated to exploring the application of big data in optimizing music education and evaluating the impact of big data technology on music teaching effectiveness through questionnaires, data analysis and model construction. The questionnaire revealed the attitudes of music teachers and students toward the application of big data, while statistical analysis and model building provided specific insights into the optimization of teaching methods and the enhancement of learning outcomes. The study found that big data technology can promote the development of personalized teaching, optimize teaching strategies, and provide data support for music education decisions. Nevertheless, the study also points out limitations such as sample selection and geographical restrictions, which can be expanded in the future. Overall, this study provides empirical basis and practical guidance for the application of big data technology in music education.

Journal of Computational Methods in Sciences and EngineeringVol. 25(1)
Openalex Percentile: Top 92%
E-commerce and Technology Innovations
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Application of big data analysis in optimizing music education — Seung‐Ki Min · Journal of Computational Methods in Sciences and Engineering (2025) | TGRS Research Map | TGRS