Open AccessThe Training Mode of Individualized Music Teaching Talents in Universities Based on Big Data
Author(s) -
Yang Ye
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1648/4/042087
Subject(s) - big data , personalized learning , training (meteorology) , music education , the internet , mathematics education , psychology , teaching method , computer science , pedagogy , world wide web , data mining , meteorology , open learning , cooperative learning , physics
The Internet and big data have deeply penetrated into various fields, which has greatly affected and changed our music education. The purpose of this article is to explore the cultivation of personalized music teaching talents in universities based on big data, with a view to promoting the cultivation of personalized music talents in universities under big data. This article conducted a questionnaire survey on some students majoring in music in our sophomore and junior colleges. Through analysis, it can be concluded that 85.29% of the students believe that the school’s music teaching method is relatively traditional and the talent training model is backward; 74.51% of the students think that the school has neglected personalized training and still adopts the traditional "one size fits all" teaching model. Based on this, the recommendations for the cultivation of personalized music teaching talents in colleges and universities are put forward, which is expected to meet the personalized and diverse music learning needs of students and promote the cultivation of personalized music talents in my country.