Application of Statistical Analysis and Association Data Mining in College Students' Mental Health Intelligent Evaluation System

Author(s):  
Qiong Wang
CONVERTER ◽  
2021 ◽  
pp. 716-724
Author(s):  
Hongrui Zhang

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.


2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Hexia Yao ◽  
Mohd. Dahlan Hj. A. Malek

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.


2020 ◽  
pp. 1-12
Author(s):  
Zheng Rong ◽  
Zheng Gang

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.


2021 ◽  
Author(s):  
Loveilia Geovani ◽  
Yonathan Aditya

Several studies have found that religion linked to perfectionism can harm mental health. Conversely, most research found that religion resulted in positive effects on mental health. Therefore, the current study was conducted to better understand this phenomenon by examining religious orientation's influence on maladaptive perfectionism among 82 college students with high levels of perfectionism as indicated by the designated instrument. The data was subject to parametric statistical analysis using Pearson Product-Moment correlation and multiple linear regression. The results showed that intrinsic religious orientation negatively influences maladaptive perfectionism, while extrinsic religious orientation positively influences maladaptive perfectionism. The study highlights the importance for college students to develop an intrinsic religious orientation to achieve an adaptive perfectionism.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yichen Chu ◽  
Xiaojian Yin

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.


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