A teaching quality evaluation model based on a wavelet neural network improved by particle swarm optimization

Abstract

In order to improve the teaching quality of higher education, the paper constructed a teaching quality evaluation index system with five first level indicators and twenty two second level indicators according to the teaching level evaluation index system of ordinary higher education. For the complex nonlinear relationships between the evaluation indices, a mathematical model for evaluating the teaching quality based on WNN, whose parameters were optimized by PSO, was presented in the paper. The experimental results showed that the method proposed could better improve the accuracy of the teaching quality evaluation target by making the mean square error of the actual output value and the desired output value smaller. Simultaneously, the method has been widely used in teaching quality evaluation of our college.