Research on Innovative Methods of Dance Teaching in Colleges and Universities under Big Data Thinking

This paper combines big data technology to design and construct the choreography process of dance movements in colleges and universities, decompose the dance movement features and use Kalman filtering to process the extracted dance movement data. Through the world coordinate system to complete the modeling of dance movements, feature Comparison and center of gravity velocity movement analysis. Examples are used to analyze the feasibility of integrating big data thinking into dance teaching in colleges and universities, and the teaching effect is verified by combining students’ essential dance performance, affective performance and comprehensive ability evaluation. After applying the model, students in both classes improved their independent learning ability. Still, the difference between the experimental and control classes was significant in both dimensions of learning motivation and learning strategy, with t-values of 23.012 and 23.127, respectively, p<0.05.