Design of Data Mining and Evaluation System for College Students’ Mental Health

2021 ◽  
Author(s):  
Zhang Xilin ◽  
Yi Honglian
Keyword(s):  
Mental Health ◽  
College Students ◽  
Data Mining ◽  
Evaluation System

scholarly journals Evaluation of the Effect of Ideological and Political Education on Psychological Crisis Intervention for University Students Based on Data Mining Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Hexia Yao ◽  
Mohd. Dahlan Hj. A. Malek
Keyword(s):  
Mental Health ◽  
College Students ◽  
Data Mining ◽  
Health Education ◽  
University Students ◽  
Civic Education ◽  
Psychological Health ◽  
Mental Health Education ◽  
Ideological Education

The mental health level of university students not only directly affects their own growth, but also affects the stability of the campus, which in turn affects the harmony of society and the improvement of the quality of all people. The combination of ideological education and mental health education is an important educational project in contemporary universities. To enhance the quality of psychological health education of college students can promote the overall development of students’ comprehensive quality; the two are closely integrated together, so as to successfully promote the effective combination of ideological education and psychological education, thus realizing the role of ideological education and psychological health education in promoting the physical and mental health development of contemporary college students. This paper explains the technology of data mining and the current situation of the psychological impact of Civic Education on college students and analyzes in depth the feasibility of introducing data mining technology in Civic Education to intervene in the psychological crisis of college students. The results show that the application of the technology provides a new idea for the mental health education of college students and a new way for the construction of a preventive college student mental health education model.

An artificial intelligence data mining technology based evaluation model of education on political and ideological strategy of students

2020 ◽  
pp. 1-12
Author(s):  
Zheng Rong ◽  
Zheng Gang
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
College Students ◽  
Data Mining ◽  
University Students ◽  
Evaluation System ◽  
Evaluation Model ◽  
Ideological And Political Education ◽  
Political Education ◽  
Ideological Education

The student’s political and ideological practices is a vital portion of education, and it is related to optimization of task based on fundamental scenario in establishing morality. In order to establish a scientific, reasonable and operable evaluation model for students’ ideological education, and evaluate the status of college students’ ideological education. In this paper, firstly, in view of the shortcomings of evaluation objectives, single evaluation methods, lack of pertinence of evaluation indicators and subjectivity of evaluation standards in the current evaluation system of university students’ ideological and political education, the basic principles for constructing evaluation models of university students’ ideological and political education are put forward. Secondly, in case to meet changing needs of the times, an artificial neural network algorithm based on artificial intelligence data mining and a traditional multi-layer fuzzy evaluation model are designed to evaluate the ideological and political education of college students. This newly proposed model integrates learning, association, recognition, self-adaptive and fuzzy information processing, and at the same time, it overcomes their respective shortcomings. Finally, an example analysis is carried out with a nearby university as an example. The evaluation results display that the evaluation model of students’ ideological education established in this paper is in good agreement with the previous evaluation results. It fully shows that the comprehensive evaluation model of fuzzy neural network for college students’ ideological and political education established in this paper is scientific and effective.

scholarly journals Data Analysis of College Students’ Mental Health Based on Clustering Analysis Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yichen Chu ◽  
Xiaojian Yin
Keyword(s):  
Mental Health ◽  
College Students ◽  
Data Mining ◽  
Clustering Analysis ◽  
Management System ◽  
Clustering Algorithm ◽  
Analysis Algorithm ◽  
Advantages And Disadvantages ◽  
Clustering Model ◽  
Psychological Management

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. This paper makes a detailed analysis and research on college students’ mental health, expounds the development and application of clustering analysis algorithm, applies the distance formula and clustering criterion function commonly used in clustering analysis, and makes a specific description of some classic algorithms of clustering analysis. Based on expounding the advantages and disadvantages of fast-clustering analysis algorithm and hierarchical clustering analysis algorithm, this paper introduces the concept of the two-step clustering algorithm, discusses the algorithm flow of clustering model in detail, and gives the algorithm flow chart. The main work of this paper is to analyze the clustering algorithm of students’ mental health database formed by mental health assessment tool test, establish a data mining model, mine the database, analyze the state characteristics of different college students’ mental health, and provide corresponding solutions. In order to meet the needs of the psychological management system based on the clustering analysis method, the clustering analysis algorithm is used to cluster the data. Based on the original database, this paper establishes the methods of selecting, cleaning, and transforming the data of students’ psychological archives. Finally, it expounds on the application of data mining in students’ psychological management system and summarizes and prospects the implementation of the system.

Research on the model of college students’ ideological and political evaluation based on data mining

2021 ◽  
pp. 1-4
Author(s):  
Linting
Keyword(s):  
College Students ◽  
Data Mining ◽  
Evaluation System ◽  
Rapid Development ◽  
Value Orientation ◽  
The Body ◽  
Ideological And Political Education ◽  
Political Education ◽  
Political Evaluation ◽  
The Times

In the whole educational system of our country, ideological and political education is an important component, and contains very rich content. With the development of the times, a variety of new information technology methods have been actively applied to the ideological and political practical teaching. At present, the group of college students is growing up with the rapid development of Internet. The “95 after generation” network “indigenous people” has undergone great changes in the evaluation body of Ideological and political education. Evaluation of Ideological and political education of the traditional value orientation gradually deconstructed, a new multi value orientation to penetrate into the body of all aspects of the behavior, must be established in accordance with the characteristics of the times subject evaluation system, the evaluation of “down to earth” and easy to be operated, rather than a mere formality. Based on the actual situation, this paper analyzes the close relationship between data mining technology and the evaluation of College Students’ Ideological and political education, and then focuses on the related problems of College Students’ Ideological and political evaluation model based on data

scholarly journals Application of Association Rule Data Mining in Statistical Analysis of College Students' Mental Health

CONVERTER ◽  
2021 ◽  
pp. 716-724
Author(s):  
Hongrui Zhang
Keyword(s):  
Mental Health ◽  
College Students ◽  
Data Mining ◽  
Big Data ◽  
Data Analysis ◽  
Statistical Analysis ◽  
Statistical Data ◽  
Knowledge Map ◽  
Statistical Indicators ◽  
Big Data Technology

Strengthening the application of big data technology in data analysis can effectively improve the service capability and level of relevant statistics, and provide comprehensive and reliable information support for macro decision-making and trend analysis. This paper comprehensively reviews the research status of big data technology in the field of college students' mental health at home and abroad. Combining with the characteristics of college students' mental health statistical data and the weaknesses in statistical analysis, the feasibility of using knowledge mapping technology is demonstrated. On this basis, the blood relationship graph and influence analysis among the statistical indicators of college students' mental health were constructed through the knowledge map. The application of the knowledge map of college students' mental health statistical indicators in statistical data analysis, statistical indicator identification and statistical data quality management is proposed. Specifically, based on the concept of big data, we can establish a decision analysis platform for college students' mental health. Based on the big data technology, the data mining and analysis ability can be enhanced. In addition, it can change the traditional thinking of college students' mental health statistics and strengthen the construction of statistical team.

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