An Innovative Exploration of Music Integration into Art Education Teaching in the Context of Big Data

Abstract

The interdisciplinary integration of art and music into education majors is a significant reform effort that benefits students’ overall artistic literacy. This study focuses on integrating music into art education teaching, with the goal of teaching concepts and empowering music applications. It uses k-means clustering to analyze the group profile of art teachers’ integration literacy. Then, we selected the influencing factors for music integration in art teaching, explored the relationship between them and the effects of art teaching, and proposed an effective way to integrate music into art education teaching. The results show that the group of teachers’ integration literacy can be divided into four categories: conservative (27.19%), ambivalent (47.50%), balanced (10.31%), and transformational (15.00%), and transformational teachers have the most vital ability to teach music integration. There was a significant positive correlation between the five dimensions of music integration in art teaching and art teaching effectiveness. The most essential effects on teaching effectiveness were found in creating a teaching context (0.217) and guiding the learning of art knowledge (0.154). The study can provide a basis for teaching music and art integration and individualized development of teachers’ integration literacy.

Keywords

• k-means clustering
• multiple regression analysis
• evaluation indicators
• correlation
• art education teaching
• 97p10