Monitoring and Sharing of Music Teaching Environment Resources Using Big Data Technology

Author:

Yang Caifen12ORCID

Affiliation:

1. Northwest Normal University, Lanzhou, 730070, China

2. Lanzhou No.2 Middle School, Lanzhou, 730030, China

Abstract

The teaching materials for different music courses in schools are getting more and more plentiful as education continues to become more and more digitised. This paper develops a resource monitoring and recommendation algorithm for the music teaching environment based on big data analysis technology, achieves the unified management and parallel retrieval of large music teaching resources, and completes the construction and sharing of music teaching resources with the goal of promoting online music teaching courses and increasing the efficiency of instruction. According to the experimental findings, the algorithm’s recall and precision may both approach 95.84% and 95.19%, respectively. This demonstrates the benefits of this strategy. With the ability to analyse and retrieve large teaching resources and data quickly and accurately, this model can offer an advantageous solution for the storage and sharing of existing and future massive teaching resources. In order to effectively integrate music curriculum materials into our lessons, music teachers need to have a thorough awareness of not just the knowledge found in textbooks but also the adaptable use of music resources both within and outside of the classroom.

Publisher

Hindawi Limited

Subject

Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Analysis for Online Music Education Under Internet and Big Data Environment;International Journal of Web-Based Learning and Teaching Technologies;2023-10-02

2. Retracted: Monitoring and Sharing of Music Teaching Environment Resources Using Big Data Technology;Journal of Environmental and Public Health;2023-06-28

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3