Evaluation and Analysis of the Effect of College Students’ Mental Health Education Based on Association Rules Mining Algorithm

This article aims to evaluate and analyze the effectiveness through association rule mining algorithms. Firstly, we collect and organize a certain amount of data on college students’ mental health education, and then use the Apriori algorithm to mine association rules to obtain the key feature factors and corresponding educational effects. Education for college students include family, friendship, love, etc. These factors are closely related to the students’ psychological state and mental health. Meanwhile, by mining data from educational practices, we have found that combining online and offline mental health education for students can effectively improve their mental health status. The conclusion of this article indicates that providing mental health education to college students and creating appropriate educational environments and methods can effectively improve their mental health level, enhance their awareness and attention to themselves and others, and facilitate better self-management and emotional communication. The above research results provide practical reference value for relevant education departments and educators, and can provide theoretical basis and practical guidance for the promotion and application of mental health education for college students.