LAUSR

Reflecting students' mental health data through vocal music teaching expressive system is a research hotspot in vocal music teaching psychology. Based on the theory of students' expressiveness in vocal music teaching, this paper constructs a psychological model of vocal music teaching. The model uses psychological data mining technology to conduct a feasibility study and analysis on the mental health education of vocal music students, solves the quantitative problem of mental health, and analyzes the relationship between psychological problems and students. In the simulation process, the psychological data of the vocal music freshmen of a certain college was taken as the research object, and the association rule Apriori algorithm was used to analyze the relationship between the factors of the psychological dimension. Psychological data mining was carried out, and descriptive indicators and univariate analysis methods were used to analyze the current situation of students' mental health and personality characteristics, and Pearson correlation analysis and structural equation model were used to explore the relationship between their mental health and personality characteristics. The amount of vocal music learning is the duration of the load and the total number of tasks completed within a single exercise or a series of exercises. ASP-NET and SQLServer2008 and other experimental results show that the chi-square test value of the overall fit of the model is 20.078, and the ratio of the chi-square value to the degree of freedom is 4.016, which has a relatively high accuracy and effectively enhances the psychological data mining technology in vocal music students for operation and practicality of applications in health data analysis.