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<p>This paper introduces mental health education into student management, utilizes ID3 algorithm of data mining technology to realize the classification of student information data, and designs the security algorithm of data storage based on C/S structure to complete the security calculation of mental health assessment. Combining the actual measurement results of students’ mental health development, a proposal is made to strengthen mental health education in student management. Taking the development of mental health education as the central perspective, exploring the specific influencing factors of the development of the level and quality of student management information technology construction, the Analysis shows that there is a significant difference between the 22-year-old students and the 18-19-year-old students in terms of information technology application ability. There is also a substantial difference in the quality of students’ participation in student management work with different levels of mental health, and the quality level of management work participated by students with good mental health status is 137.48±7.56, which is more capable of dealing with student management work than student workers with poor mental health status.</p>
</abstract>

This paper introduces mental health education into student management, utilizes ID3 algorithm of data mining technology to realize the classification of student information data, and designs the security algorithm of data storage based on C/S structure to complete the security calculation of mental health assessment. Combining the actual measurement results of students’ mental health development, a proposal is made to strengthen mental health education in student management. Taking the development of mental health education as the central perspective, exploring the specific influencing factors of the development of the level and quality of student management information technology construction, the Analysis shows that there is a significant difference between the 22-year-old students and the 18-19-year-old students in terms of information technology application ability. There is also a substantial difference in the quality of students’ participation in student management work with different levels of mental health, and the quality level of management work participated by students with good mental health status is 137.48±7.56, which is more capable of dealing with student management work than student workers with poor mental health status.

Analysis of the Role and Influencing Factors of Strengthening Mental Health Education in Student Management

Applied Mathematics and Nonlinear Sciences

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

This paper introduces mental health education into student management, utilizes ID3 algorithm of data mining technology to realize the classification of...

Analysis of the Role and Influencing Factors of Strengthening Mental Health Education in Student Management

Data publikacji: 03 maj 2024

Zakres stron: -

Otrzymano: 04 kwi 2024

Przyjęty: 15 kwi 2024

DOI: https://doi.org/10.2478/amns-2024-1004

Słowa kluczowe
Data mining technology, ID3 algorithm, Security algorithm, Mental health education, Student management

© 2024 Ying Xu, published by Sciendo

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

Analysis of the Role and Influencing Factors of Strengthening Mental Health Education in Student Management

Data publikacji: 03 maj 2024

Zakres stron: -

Otrzymano: 04 kwi 2024

Przyjęty: 15 kwi 2024

DOI: https://doi.org/10.2478/amns-2024-1004

Słowa kluczoweData mining technology, ID3 algorithm, Security algorithm, Mental health education, Student management

© 2024 Ying Xu, published by Sciendo

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

Słowa kluczowe
Data mining technology, ID3 algorithm, Security algorithm, Mental health education, Student management