A BP Neural Network-Assisted Smart Decision Method for Education Quality

Deep neural network-based decision support has been more prevalent in many cross-discipline applications, as their strong computation ability can facilitate knowledge discovery and rule mining. In this context, this work explores its utilization to the field of education quality evaluation, in order to bring more automatic elements for this purpose. Therefore, a BP neural network-assisted smart decision method for education quality is proposed in this paper. Specifically, the method of questionnaires is utilized to screen indicators, expert evaluation method is adopted to determine the weight of evaluation indexes, and a comprehensive education evaluation index system is accordingly built. After constructing a complete evaluation system, this paper establishes an evaluation model of ideological and political education by using BP neural network algorithm and takes University as an example to compare the performance of W University students before and after applying the model. This model has been applied and demonstrated, and the evaluation way of college teaching quality has been innovated. At last, some simulation experiments are carried out for further assessment, and the results show that the proposal can work well in terms of automatic education quality evaluation.