Design of Experiential Teaching System for Solfeggio in Normal Universities Based on Machine Learning Algorithm

Abstract

At present, with the rapid development of the Internet and its close connection with our life, more and more educators apply the Internet to teaching. However, there is little research on the application of the Internet in solfeggio teaching, and there are some problems in the teaching process, such as nonstandard use methods, inability to highlight teaching objectives, and mismatch with students’ professional level. On the premise of fully understanding the teaching objectives of solfeggio in China, this paper designs an experiential teaching system of solfeggio in normal universities based on machine learning algorithm, studies the application of digital technology in solfeggio, including Internet technology, multimedia digital technology, and the use of music software, and analyzes the auxiliary role of digital technology in solfeggio teaching by combining the specific teaching contents of online solfeggio teaching during the epidemic period. In this experiment, the average classification accuracy of WNB algorithm is 0.767, while that of BP algorithm is 0.683. Experimental results show that WNB algorithm outperforms BP algorithm in classification. At the same time, in terms of time efficiency, the average time consumption of WNB algorithm in this experiment is about 0.026 s, while that of BP algorithm is about 0.45 s. Compared with WNB algorithm, the time consumption of WNB algorithm is less. Through concrete practice, it is proved that the combination of solfeggio teaching and digital technology is of great significance to both teachers’ teaching and students’ learning.