An Intelligent Evaluation Path for English Teaching Quality: Construction of an Evaluation Model Based on Improved BPNN

The current intelligent evaluation methods for English teaching quality are inefficient and have poor accuracy effective assessment. paper suggests an model based on upgraded Back Propagation Neural Network to overcome the aforementioned issues. First, principal component analysis is utilized lessen dimensionality of index system as we build with reference results existing study. Then, adopt a multi-strategy improved dragonfly optimization algorithm evaluate its defects; improve it. Finally, increase efficacy objectivity evaluation, IDA-BPNN developed. experimental demonstrate that has 98.96%, F1 value 0.950 training set 0.968 test set, Recall 0.948 0.966 set. indicators all superior most recent state-of-the-art approaches evaluating quality. findings thus suggested in study high performance can successfully efficiency which positive impact development careers.