Research Article
Statistical Application of Mental Health Data of College Students Under the Background of Informationization
@INPROCEEDINGS{10.1007/978-3-030-87900-6_65, author={Yanan Li}, title={Statistical Application of Mental Health Data of College Students Under the Background of Informationization}, proceedings={Application of Big Data, Blockchain, and Internet of Things for Education Informatization. First EAI International Conference, BigIoT-EDU 2021, Virtual Event, August 1--3, 2021, Proceedings, Part I}, proceedings_a={BIGIOT-EDU}, year={2021}, month={10}, keywords={Data mining Psychological management system K-means algorithm}, doi={10.1007/978-3-030-87900-6_65} }- Yanan Li
Year: 2021
Statistical Application of Mental Health Data of College Students Under the Background of Informationization
BIGIOT-EDU
Springer
DOI: 10.1007/978-3-030-87900-6_65
Abstract
Mental health is an important basic condition for college students to become adults. Educators gradually attach importance to strengthening the mental health education of college students. Traditional colleges and universities on mental health data only stay in the operation of adding, deleting and checking, and do not effectively analyze the potential psychological information of the data. This paper proposes a kind of psychological management system based on K-means clustering analysis method, which uses the idea of data mining to make secondary use of students’ psychological data on the basis of traditional system functions. By optimizing the iterative process of K-means algorithm, the valuable part of a large number of precipitation students’ psychological data is extracted, and the data model is established to provide decision-making guidance for managers, Scientific management of students’ mental health process can not only effectively improve the overall efficiency of psychological counseling, but also play an early warning role in the prevention of risk factors.
