Entrepreneurship Education and Health-Stress Analysis of College Teachers and Students Using Backpropagation Neural Network Model - Fu, Leiming; Cheng, Qi (Frontiers in Psychology, 2022)
The purpose is to solve the problem of college students' employment difficulties. It is the development trend of the times to master the basic psychological pressure state of students and analyze students' problems by using modern technology and science. First, based on Marxist theory, the theory of entrepreneurship education and the characteristics of teachers and students in colleges are expounded, and the principle and algorithms of Backpropagation Neural Network (BPNN) are introduced. Second, from the perspective of entrepreneurship education and mental health factors of college students, the sample set of the BPNN model is collected using a Questionnaire Survey (QS). Then, the sample set is normalized to analyze the current college entrepreneurship education and the health and stress of college students. The results show that the comprehensive BPNN output of entrepreneurship education is 0.726, indicating that entrepreneurship education in colleges is at a moderate level. The proposed BPNN model can perform better than the traditional prediction methods in predicting college students' mental health, and the data fitting results are satisfactory. Overall, college students’ entrepreneurship education should be improved, and schools should take more incentives to help adjust college students’ mentality.