The use of online interactive teaching mode in university music teaching under the background of informationization

This research method uses vocal recognition, classroom interaction analysis and social network analysis theory to cluster audio data through the process of data collection and feature extraction, active speech detection and speaker change detection, and finally quantifies and visualizes classroom data based on S-T analysis and social network analysis methods, and calculates corresponding indicators for qualitative analysis. After reforming the teaching mode, 80% of students expressed great satisfaction. The information-based teaching tools resulted in an overall upward trend in the grades of the three classes. In the middle and high score range of 80-89, Class 1 increased by 34%, Class 2 by 37%, and Class 3 by 28%, and all three classes showed a more significant increase. Regarding classroom interaction behaviors, teachers' verbal behavior rates decreased from 55.86% and 44.01% to 27.48%, while students' verbal behavior rates increased from 21.92% and 21.23% to 39.73%. © 2023 Meiying Ni, Fangling Yang and Mei Liu, published by Sciendo.