To address the current shortcomings in monitoring and implementing strategies for graduate classroom teaching,this paper proposes a method using BP neural network machine learning to dynamically evaluate the quality of graduate classroom teaching.The BP neural network method can reduce dependence on experts through learning,thereby saving human and material resources required for teaching evaluation,while ensuring the accuracy and stability of classroom teaching evaluation.This paper elaborates the practical measures of using the BP neural network in evaluating the quality of postgraduate classroom teaching,including the construction of an evaluation index system,data collection and processing,BP neural network model design and optimization,practical application and assessment,and continuous improvement and promotion.This study achieves interdisciplinary integration between teaching monitoring and the field of neural networks,bringing new ideas and methods for the reform of graduate education quality monitoring.
BP neural networkteaching monitoringclassroom teachinggraduate educationteaching method
万方数据
维普
