<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In recent years, the number of psychological problems occurring in college students has been increasing day by day, and timely, convenient, and accurate psychological warning is an important way to prevent college students from psychological crises. Starting from the basic needs of the system and aiming at realizing the embedding of data mining technology in the psychological management system, this paper elaborates on the design and implementation of the data mining technology module suitable for the psychological management system. The clustering algorithm-K mean algorithm of data mining is used to distinguish groups of students with different categories of psychological problems, which provides data support for the next decision-making. Through simulation experiments between the system designed in this paper and four other mental health management systems, the clustering performance and system evaluation performance of this paper’s system are better than those of the other systems. The result of mining the mental health of college students through this system shows that 82.2% of the student’s assessment results show normal, and 8.35% of the students need to focus on, and this result is not much different from that obtained from the statistical survey of a personality questionnaire, which indicates that the use of clustering analysis in the system can be an effective prediction of the mental health of college students.</p>
</abstract>

In recent years, the number of psychological problems occurring in college students has been increasing day by day, and timely, convenient, and accurate psychological warning is an important way to prevent college students from psychological crises. Starting from the basic needs of the system and aiming at realizing the embedding of data mining technology in the psychological management system, this paper elaborates on the design and implementation of the data mining technology module suitable for the psychological management system. The clustering algorithm-K mean algorithm of data mining is used to distinguish groups of students with different categories of psychological problems, which provides data support for the next decision-making. Through simulation experiments between the system designed in this paper and four other mental health management systems, the clustering performance and system evaluation performance of this paper’s system are better than those of the other systems. The result of mining the mental health of college students through this system shows that 82.2% of the student’s assessment results show normal, and 8.35% of the students need to focus on, and this result is not much different from that obtained from the statistical survey of a personality questionnaire, which indicates that the use of clustering analysis in the system can be an effective prediction of the mental health of college students.

Development of a Big Data Analysis and Management Decision Support System for Student Mental Health in Higher Education

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In recent years, the number of psychological problems occurring in college students has been increasing day by day, and timely, convenient, and accurate...

Development of a Big Data Analysis and Management Decision Support System for Student Mental Health in Higher Education

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 02. Apr. 2024

Akzeptiert: 28. Juni 2024

DOI: https://doi.org/10.2478/amns-2024-2144

Schlüsselwörter
K-mean algorithm, Cluster analysis, Data mining, Mental health management system

© 2024 Fenping Zheng, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Development of a Big Data Analysis and Management Decision Support System for Student Mental Health in Higher Education

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 02. Apr. 2024

Akzeptiert: 28. Juni 2024

DOI: https://doi.org/10.2478/amns-2024-2144

SchlüsselwörterK-mean algorithm, Cluster analysis, Data mining, Mental health management system

© 2024 Fenping Zheng, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
K-mean algorithm, Cluster analysis, Data mining, Mental health management system