Construction and Evaluation of College Students’ Psychological Education Evaluation Model Based on Joint Neural Network

The construction and evaluation of a college student psychological education evaluation model based on joint neural networks can provide personalized evaluations by analyzing the psychological characteristics and mental health status of different students. This study describes the construction of educational evaluation. This method combines two methods: one is to use the single-layer method to calculate the score of psychological education evaluation; Another approach is to use a multi-level psychological education scoring method. In addition, we also tested whether our method can serve as a substitute for other existing models in psychology. The construction of the model is as follows: Firstly, input data is selected from various psychological tests and other related factors. Then, use a neural network to obtain the output data to obtain the output value. Finally, the evaluation results were calculated based on this method. The evaluation model of college students’ psychological education based on the combined neural network combines Natural language processing technology to analyze and study the questionnaire survey of students, and uses neural network technology to train and optimize, so as to achieve accurate evaluation of college students’ psychological state. This evaluation model can provide more comprehensive, personalized, and targeted psychological education services for college students, helping them better identify and solve psychological problems, and improving their mental health level.