Simulation Analysis of Standardized Management Measures for Private College Students Based on Data Mining

2021 ◽  
Author(s):  
Lijun Fan
Keyword(s):  
College Students ◽  
Data Mining ◽  
Simulation Analysis ◽  
Private College ◽  
Management Measures

The Relationship between Self-Reported Religiosity and Drug Use by College Students

1979 ◽  
Vol 9 (1) ◽  
pp. 67-78 ◽  
Author(s):  
Carol J. Turner ◽  
Robert J. Willis
Keyword(s):  
College Students ◽  
Drug Use ◽  
Private College ◽  
Drug Usage ◽  
College Counselors ◽  
Use Patterns ◽  
Current Drug ◽  
Drug Use Patterns ◽  
Drug Problems ◽  
The Relationship

As part of an extensive questionnaire on student drug use patterns at a small private college, this study was completed to determine the relationship between self-reported religiosity of college students and 1) the nature and incidence of current drug usage, 2) reasons for abstaining from drug use, 3) acceptable sources for referral in case of drug problems, and 4) persons with whom students would discuss their attitudes toward drugs. Statistically significant differences between religious and non-religious students at the 0.01 level were found in the current use of alcohol and marijuana, in reasons for abstaining from marijuana, amphetamines, barbiturates, and hallucinogens; in referral of drug problems to drug wise friends; and in discussing drug attitudes with parents and with college counselors.

scholarly journals Student perspective on plagiarism

2010 ◽  
Vol 3 (1) ◽  
Author(s):  
Torunn Skofsrud Boger ◽  
Anne-Lise Eng
Keyword(s):  
College Students ◽  
Great Britain ◽  
Master's Degree ◽  
National Interest ◽  
Colleges And Universities ◽  
Private College ◽  
Student Perspective ◽  
The Us ◽  
Master’S Degree

Autumn 2008, four employees at Østfold University College (HiØ), one with a Master's Degree in Sosiology, one with a Master's Degree in Nursing and two librarians, interviewed 33 Norwegian College students about the subjects cheating and plagiarism. This is the first such survey conducted in Norway. There are plenty of comparable reseach from countries such as the US, Great Britain, Canada and even Sweden, but the Norwegian focus on these issues has been missing until a few years ago. We started working with this subject about two years ago, about the same time as some incidents of cheating at a private College and a University Faculty got national interest, and HiØ started to review some of the effects of the reform Kvalitetsreformen. Our survey is part of this project named "Kvalitetsreformens vurderingsformer i høgskolen" (http://www.hiof.no/index.php?ID=14004=nor). Some of the topics treated in our survey are collaboration and collusion, consequenses of cheating, information given to students about plagiarism and the role of the libraries. We find that students, staff and teachers care about these subjects, but perhaps in slightly different ways and with different perspectives. Our aim is to let the students speak, and try to listen and understand, and hopefully find some ideas or starting points to start work with. Many colleges and universities are starting working with plans to deal with these issues, and we believe it is important to include the student perspective in this work. We are planning to release our research in a report in the HiØ's Report Series spring 2010.

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.

Deep Learning-based Mental Health Monitoring Scheme for College Students Using Convolutional Neural Network

2021 ◽  
Vol 30 (06n08) ◽  
Author(s):  
Chao Du ◽  
Chang Liu ◽  
P. Balamurugan ◽  
P. Selvaraj
Keyword(s):  
Neural Network ◽  
Mental Health ◽  
College Students ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Health Monitoring ◽  
Simulation Analysis ◽  
Personality Development ◽  
Monitoring Scheme ◽  
Depression Level

Artificial intelligence (AI) in healthcare has recently been promising using deep neural networks. It is indeed even been in clinical trials more and more, with positive outcomes. Deep learning is the process of using algorithms to train a neural network model using huge quantities of data to learn how to execute a given task and then make an accurate classification or prediction. Apart from physical health monitoring, such deep learning models can be used for the mental health evaluation of individuals. This study thus designs a deep learning-based mental health monitoring scheme (DL-MHMS) for college students. This model uses the most efficient convolutional neural network (CNN) to classify the mental health status as positive, negative, and normal using the EEG signals collected from college students. The simulation analysis achieves the highest classification accuracy and F1 scores of 97.54% and 98.35%, less sleeping disorder rate of 21.19%, low depression level of 18.11%, reduced suicide attention level of 28.14%, increasing personality development ratio of 97.52%, enhance self-esteem ratio of 98.42%, compared to existing models.

Study on the Application of Data Mining Based on Campus Card Platform

2013 ◽  
Vol 846-847 ◽  
pp. 977-980 ◽  
Author(s):  
Yuan Qian ◽  
Quan Shi
Keyword(s):  
College Students ◽  
Data Mining ◽  
Time Series ◽  
Statistical Methods ◽  
Business Intelligence ◽  
Sql Server ◽  
Policy Makers ◽  
University Policy ◽  
Development Tools ◽  
Intelligence Development

The thesis uses data in the database of campus card platform as the analysis object, combined with statistical methods and data mining technology to analyze the students consumption and the situation of the canteens. We use the Microsoft .NET and SQL Server 2008 business intelligence development tools to mine and analyze these data; know canteens consumption and learn about the business status and the popular shops of the canteen by using the K-means algorithm; analyze and predict students behavior and the situation of the canteen by using time series algorithm. It is convenient to manage the college students, and provide data support for university policy makers and shoppers to make plans.

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