Application Research of BP Neural Network in English Teaching Evaluation

Teaching evaluation plays a key role for universities to improve its teaching quality and becomes a hotspot research field for related researchers. The paper takes university English teaching for example and presents a new model for evaluating English course teaching based on improved BP neural network. Firstly an evaluation indicator system of university English teaching is designed through analyzing the aspects of teaching effects and teacher factors and student factors. Secondly, BP Neural network is improved by improving its Non-monotone linear search and adaptive step change to overcome its shortages of low convergence in calculation. Thirdly data from of some universities are taken for examples to verify the validity and feasibility of the model and the experimental results show that the model can evaluate university English teaching practically and can help university and English teachers take corresponding concrete measures to enhance its education performance.