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<p>This paper takes the synergy between ideological work and student management in colleges and universities as an entry point, analyzes the intrinsic mechanism between the two, and gives the synergistic effect of parenting after the integration of the two. The synergistic mechanism between student management and ideological work is explored by mining students’ daily behavioral data, and after analyzing students’ daily behavioral data based on density-optimized clustering algorithm, risk warning detection of students’ academic situation is carried out by combining the improved LSTM model. The GCN network model is utilized to detect students’ psychological disorders. In order to verify the effectiveness of the method given in this paper for exploring the synergistic cultivation of ideological work and student management, quantitative analysis was carried out through the data of college students’ one-card. The results show that the movement data of college students are divided into 4 classes, of which the largest proportion of students is class cluster 4 is 44.59%, the risk prediction accuracy of the improved LSTM academic warning model is 0.731, and the GCN network model has a model loss value of about 0.25% after about 50 iterations when the threshold value is 0. Colleges and universities under the binary structure can narrow the value differences between students through data mining technology, and can help students remove psychological barriers, prompting the generation of a collaborative parenting mechanism between ideological work and student management in colleges and universities.</p>
</abstract>

This paper takes the synergy between ideological work and student management in colleges and universities as an entry point, analyzes the intrinsic mechanism between the two, and gives the synergistic effect of parenting after the integration of the two. The synergistic mechanism between student management and ideological work is explored by mining students’ daily behavioral data, and after analyzing students’ daily behavioral data based on density-optimized clustering algorithm, risk warning detection of students’ academic situation is carried out by combining the improved LSTM model. The GCN network model is utilized to detect students’ psychological disorders. In order to verify the effectiveness of the method given in this paper for exploring the synergistic cultivation of ideological work and student management, quantitative analysis was carried out through the data of college students’ one-card. The results show that the movement data of college students are divided into 4 classes, of which the largest proportion of students is class cluster 4 is 44.59%, the risk prediction accuracy of the improved LSTM academic warning model is 0.731, and the GCN network model has a model loss value of about 0.25% after about 50 iterations when the threshold value is 0. Colleges and universities under the binary structure can narrow the value differences between students through data mining technology, and can help students remove psychological barriers, prompting the generation of a collaborative parenting mechanism between ideological work and student management in colleges and universities.

Research on the synergistic nurturing mechanism of ideological work and student management in colleges and universities under the binary structure

Applied Mathematics and Nonlinear Sciences

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

This paper takes the synergy between ideological work and student management in colleges and universities as an entry point, analyzes the intrinsic mechanism...

Research on the synergistic nurturing mechanism of ideological work and student management in colleges and universities under the binary structure

Online veröffentlicht: 16. Dez. 2023

Seitenbereich: -

Eingereicht: 26. Jan. 2023

Akzeptiert: 26. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01485

Schlüsselwörter
Density optimization, K-means clustering, LSTM model, GCN model, Collaborative parenting

© 2023 Zhenhua Du, published by Sciendo

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

Research on the synergistic nurturing mechanism of ideological work and student management in colleges and universities under the binary structure

Online veröffentlicht: 16. Dez. 2023

Seitenbereich: -

Eingereicht: 26. Jan. 2023

Akzeptiert: 26. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01485

SchlüsselwörterDensity optimization, K-means clustering, LSTM model, GCN model, Collaborative parenting

© 2023 Zhenhua Du, published by Sciendo

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

Schlüsselwörter
Density optimization, K-means clustering, LSTM model, GCN model, Collaborative parenting