Personalized teaching and learning in college music education innovation based on big data analysis

Abstract

With the increasing popularity of big data technology in the field of education, its application in college music education has become a new field of concern. The purpose of this study is to explore the application and effect of big data technology in personalized teaching and learning innovation in college music education. Through the comprehensive use of questionnaire survey, experiment design and big data analysis model, the research finds that big data technology can significantly improve the teaching quality of music education and the learning effect of students. The questionnaire revealed the cognition and attitude of teachers and students toward big data technology, while the experimental results showed that the teaching class using big data technology outperformed traditional teaching methods in terms of academic achievement and motivation. In addition, the constructed big data analysis model showed high accuracy in predicting students’ learning outcomes. However, the study also points out that there are still technical, privacy and adaptability challenges when it comes to practical application of big data technology. This study provides a scientific basis for the further application of big data technology in music education, and puts forward suggestions for future educational practice and research direction.