Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Sun, Lixina; * | Wang, Qiuyingb
Affiliations: [a] School of Science and Data, Yantai Nanshan University, Yantai, Shandong, China | [b] Jiangxi Science and Technology Normal University, Nanchang, China
Correspondence: [*] Corresponding author: Lixin Sun, School of Science and Data, Yantai Nanshan University, Yantai, Shandong, China. E-mail: sun_lixin1982@hotmail.com.
Abstract: With the rapid development of the information age, big data technology has been widely penetrated into various industries, and has brought profound impact on its structure and operation mode. In the field of music education, big data provides advanced tools and platforms for teaching, and provides a new perspective for the formulation of music teaching strategies and the sharing of educational resources. The purpose of this study is to deeply study the music teaching strategies based on big data and make a comparative analysis with traditional strategies. Based on an extensive literature review, this study summarizes the basic concepts, core features and applications of big data in music teaching. In order to have a more comprehensive understanding of the actual effects of big data in music teaching, we designed a series of experiments to compare the performance of music teaching strategies based on big data and traditional strategies in terms of student learning outcomes, learning engagement, student satisfaction, teaching progress and efficiency. The results show that the music teaching strategy based on big data can better meet the personalized learning needs of students, improve the learning engagement, and significantly improve the teaching effect and the quality of resource sharing. This study provides scientific ideas and methods for music teaching, and hopefully provides beneficial enlightenment for the application of big data technology in the field of education.
Keywords: Big data, music teaching strategy, educational resource sharing
DOI: 10.3233/JCM-247462
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2391-2407, 2024
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl