Evaluation of the Online Music Flipped Classroom under Artificial Intelligence and Wireless Networks

Abstract

The study aims to explore the online music flipped classrooms based on artificial intelligence (AI) and wireless networks. A backpropagation neural network (BPNN) algorithm optimized by the genetic algorithm (GA) is proposed to evaluate the teaching quality of music flipped classrooms and analyze the problems in the current teaching mode. First, an evaluation index system is established for online music flipped classrooms; second, a questionnaire is designed according to the index system. After the data are collected, the GA-BPNN evaluation model is used to evaluate the teaching quality of the music flipped classrooms. Finally, the model’s performance is evaluated based on the forecast accuracy compared with the model implemented only by the BPNN. The simulation results show that the GA-BPNN evaluation model can effectively evaluate the teaching quality of flipped classrooms, and the evaluation results are objective and accurate. The model overcomes the shortcomings of traditional evaluation methods. The study has great practical significance and provides a basis for improving the teaching quality of online flipped classrooms.