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

<p>In the era of big data, the implementation of red ideological and political education has a positive and practical guide to the daily behavior habits of college students, and plays a positive guiding role. The lack of red ideological and political education is one of the main reasons for the abnormal behavior of college students. In this paper, the daily behavioral habits of college students are modeled, and according to the different distribution characteristics of individuals on campus activities, abnormal class determination and cluster analysis are carried out. The abnormality detection operator is used to detect the strange behavior of college students. In the study of abnormal behaviors of college students, the proportion of medium and low intensity of deviant behavior college students in sports behavior is as high as 73%, the proportion of high intensity in dietary behavior is 53%, and the proportion of high intensity in consumption behavior is also more than 50%. The psychological attention characteristic value of abnormal behavior college students is lower than that of average behavior college students, and the fluctuation is slightly more significant than that of intermediate behavior college students. Except for the forgiveness and modesty factors, the other 13 positive psychological quality factors of abnormal behavior college students are lower than those of average behavior college students, and the evaluation of the quality of political thinking is more inadequate than 80 points, which is in the range of poor and general assessment. Given the abnormal behavior of college students, the optimization direction of red Civics teaching method is proposed.</p>
</abstract>

In the era of big data, the implementation of red ideological and political education has a positive and practical guide to the daily behavior habits of college students, and plays a positive guiding role. The lack of red ideological and political education is one of the main reasons for the abnormal behavior of college students. In this paper, the daily behavioral habits of college students are modeled, and according to the different distribution characteristics of individuals on campus activities, abnormal class determination and cluster analysis are carried out. The abnormality detection operator is used to detect the strange behavior of college students. In the study of abnormal behaviors of college students, the proportion of medium and low intensity of deviant behavior college students in sports behavior is as high as 73%, the proportion of high intensity in dietary behavior is 53%, and the proportion of high intensity in consumption behavior is also more than 50%. The psychological attention characteristic value of abnormal behavior college students is lower than that of average behavior college students, and the fluctuation is slightly more significant than that of intermediate behavior college students. Except for the forgiveness and modesty factors, the other 13 positive psychological quality factors of abnormal behavior college students are lower than those of average behavior college students, and the evaluation of the quality of political thinking is more inadequate than 80 points, which is in the range of poor and general assessment. Given the abnormal behavior of college students, the optimization direction of red Civics teaching method is proposed.

Characterization of Red Civic Education in Colleges and Universities under Big Data Platform and Optimization of Teaching Methods

Applied Mathematics and Nonlinear Sciences

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

In the era of big data, the implementation of red ideological and political education has a positive and practical guide to the daily behavior habits of...

Characterization of Red Civic Education in Colleges and Universities under Big Data Platform and Optimization of Teaching Methods

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 15. Jan. 2024

Akzeptiert: 22. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0622

Schlüsselwörter
Red civic education, Cluster analysis, Anomaly detection operator, Anomaly class

© 2023 Rong Pan, published by Sciendo

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

Characterization of Red Civic Education in Colleges and Universities under Big Data Platform and Optimization of Teaching Methods

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 15. Jan. 2024

Akzeptiert: 22. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0622

SchlüsselwörterRed civic education, Cluster analysis, Anomaly detection operator, Anomaly class

© 2023 Rong Pan, published by Sciendo

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

Schlüsselwörter
Red civic education, Cluster analysis, Anomaly detection operator, Anomaly class