Optimal Path of Music Education in Higher Vocational Colleges under the Background of Big Data

Abstract

With the rapid increase in the number of vocational colleges (VC) in my country, improving the comprehensive quality of students in VC is an important task facing vocational education today. Among them, improving students' music literacy is a very effective way. At present, the application of computers and big data (BD) algorithms is becoming more and more common, and a large amount of data has been accumulated. Applying data mining technology to the analysis of music teaching data in higher VC can help teachers understand the music quality of students and improve students' music quality in a targeted manner. The purpose of this article is to analyze the optimization path of music education in higher VC under the background of BD. This paper uses path analysis BD algorithm to optimize and analyze the music education data of higher VC, analyzes the related concepts and internal and external structural elements of the music education system in higher VC, and elaborates the composition of the music education path in higher VC. The internal and external structure of the elements, the path and the operation mechanism of the path are solved by programming using GAMS software, and all the best feasible solutions are solved through the mixed integer linear programming (MILP) BD algorithm, and the optimization path related to music education in VC is studied. The path analysis experiment shows that when higher VC fully develop music teaching activities, the main source of music education promotion in higher VC is the conversion of internal and external integrated pathways and internal model pathways, which account for more than 80%, while the external model pathway accounts for more than 80% The allocation is relatively small, less than 10%.