Monitoring and Model Analysis of Vocal Performance Teaching Environment Using Cluster Analysis from the Perspective of Core Literacy. (6th October 2022)

• Record Type: Journal Article
• Authors: Long, Tao
• Other Names: Kaifa Zhao Academic Editor.
• Is Part Of: Journal of environmental and public health. Volume 2022(2022)
• Publication Date: 2022-10-06
• Subjects: Environmental health -- Periodicals; Occupational diseases -- Periodicals; Public health -- Periodicals; 613.105
• DOI: 10.1155/2022/1477309
• Languages: English
• ISSNs: 1687-9805

Abstract

Abstract : To cultivate students' artistic quality, enhance their vocal music quality, and prepare them to make great contributions to the innovation and development of my country's vocal music art is the main goal of opening vocal music performance major in colleges and universities. With the advancement of technology and the demands of talent development, the vocal music teaching methodology for the vocal music performance major in colleges and universities must be continuously enhanced. Otherwise, there will be an issue of disconnect between teaching style and talent development, which will harm both the development of high-quality vocal music talents and the innovation and growth of vocal music performance majors in colleges and universities. The vocal music performance major at colleges and universities should actively support the reform and innovation of the vocal music teaching mode in order to extend students' knowledge, develop their all-around ability, and provide a strong foundation for vocal music performance, to develop students' all-encompassing musical abilities. This research suggests a design strategy for the monitoring and model optimization of the teaching environment for vocal performance majors from the standpoint of core literacy. To increase the efficiency and objectivity of course instruction, cluster analysis aids students in categorising and searching for vocal music performance main repertoire as well as using collaborative filtering recommendations to locate their own vocal music performance. The simulation test analysis is completed lastly. The method has a certain accuracy, which is 7.59% higher than the conventional algorithm, according to the simulation findings. In addition to significantly increasing student interest in studying vocal music performance courses, we further reform and innovation of the teaching method for these courses at colleges and universities can also strengthen students' understanding of various repertoire styles and significantly enhance their musical literacy.