![]() ![]() The questionnaire was found to be reliable, valid and reproducible. The Pearson correlation coefficient was used to determine the association between the knowledge and attitude scores (P < 0.05). Differences in the scores between groups and genders were analysed by one-way analysis of variance (ANOVA). The following 3 groups of university students (n = 635) were recruited based on a convenience sampling technique and were distributed the questionnaire via an online survey system: dental students (DSs), medical students (MSs), and non-medical students (NSs). To assess the knowledge of and attitudes towards erosive tooth wear among dental, medical, and non-medical university students of two Chinese universities.Ī questionnaire containing 15 questions on knowledge of erosive tooth wear and 10 questions on attitudes towards erosive tooth wear was designed, and its psychometric properties (reliability and validity) were analysed in a pilot study (n = 120 students). The improved BP algorithm is applied to the evaluation system of education management theory, and the quality evaluation prediction of management education theory is realized. This can help overcome the limitations of the BP algorithm when dealing with large amounts of data. To improve algorithm execution efficiency and speed up neural network training, a large number of gradient operations can be avoided. BP neural networks are trained using the particle swarm optimization algorithm, and the backward propagation process in the BP algorithm is replaced with particle swarm iteration. To train a neural network with large amounts of data, the BP algorithm uses a lot of gradient calculation, which takes a long time and often results in training going to extremes in the local area. At the same time, the traditional BP algorithm is improved. Therefore, this paper uses neural network to conduct data mining on education management theory and conduct a comprehensive system evaluation of education management theory. By optimizing the artificial neural network, data mining of characteristic information data can be realized. It is possible to process a lot of information in parallel using the artificial neural network method. Designing a comprehensive and accurate educational management theory evaluation model has important theoretical value and practical significance. However, the existing research on the evaluation of educational management theory is still relatively small, and there is a lack of scientific educational management theory evaluation model. The improvement of the theoretical quality of education management is an indispensable part of a country’s education modernization. ![]()
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