Research on Comprehensive Evaluation of Teaching Quality in Colleges and Universities Based on Deep Learning BP Neural Network Technology

This article explores the utilization of BP neural network technology in deep learning to evaluate teaching quality in colleges and universities. It emphasizes the core position of teaching quality in higher education and points out the limitations of traditional evaluation methods in dealing with the nonlinear problems of teaching quality. To overcome these limitations, the article proposes a BP neural network model based on deep learning and discusses the construction process and evaluation methods of the model, including three-fold cross-validation and the calculation of accuracy, precision, recall, and F1 score. The experimental results demonstrate that the BP neural network model integrated with deep learning performs excellently in teaching quality evaluation and outperforms other traditional evaluation methods. Finally, the article suggests future research directions, including model improvement, dataset expansion, and enhancement of model interpretability.