College English Classroom Teaching Evaluation Based On Particle Swarm Optimization - Extreme Learning Machine Model

The quality evaluation of English classroom teaching carries great significance in promoting English teaching reform and raising the quality of English education at university level in China. In this paper, a quality evaluation index system is introduced for the classroom teaching of English as a foreign language (Extreme Learning Machine), and an EFL classroom teaching quality evaluation model is built based on the Particle Swarm Optimization (PSO) -Extreme Learning Machine (ELM) algorithm with an ELM model constructed for comparison. A comparison shows that the PSO-ELM algorithm can obtain better accuracy with less hidden layer neurons, hence lowering the demand upon experiment samples and strengthening the fitting ability of the model. Experiment results show that the PSO-ELM algorithm is feasible to evaluate classroom teaching of English as a foreign language. The designed English classroom teaching quality evaluation index system is thus confirmed as effective, and is expected to improve the quality and management of classroom teaching of English as a foreign language.