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

<p>Political identity directly affects the implementation of the nurturing function of politics and the enhancement of the teaching effect, this paper proposes a path to enhance students’ political identity in the teaching of Daofa based on the multimodal fusion model. The TF-IDF method is utilized to identify political emotions contained in students’ classroom expressions, and LBP is used to extract students’ facial expression features. Based on the above-extracted results, a multimodal feature learner emotion data model is designed, which is also combined with a deep RNN model to identify and analyze students’ learning behaviors in the actual Daofa classroom. Evaluating students’ political identity from five dimensions, the results show that all students have significant differences in the five dimensions, P&lt;0.05, and their political identity is above 60, of which the highest political identity in the fourth year of college reaches 78.586. Among the states of political identity, the state of maturity type has the highest frequency of occurrence, which is 132 times. The results of the study provide data support for improving students’ political identity.</p>
</abstract>

Political identity directly affects the implementation of the nurturing function of politics and the enhancement of the teaching effect, this paper proposes a path to enhance students’ political identity in the teaching of Daofa based on the multimodal fusion model. The TF-IDF method is utilized to identify political emotions contained in students’ classroom expressions, and LBP is used to extract students’ facial expression features. Based on the above-extracted results, a multimodal feature learner emotion data model is designed, which is also combined with a deep RNN model to identify and analyze students’ learning behaviors in the actual Daofa classroom. Evaluating students’ political identity from five dimensions, the results show that all students have significant differences in the five dimensions, P<0.05, and their political identity is above 60, of which the highest political identity in the fourth year of college reaches 78.586. Among the states of political identity, the state of maturity type has the highest frequency of occurrence, which is 132 times. The results of the study provide data support for improving students’ political identity.

Research on the Path of Enhancing Students’ Political Identity in Teaching Ethics and Rule of Law in the Information Age

Applied Mathematics and Nonlinear Sciences

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

Political identity directly affects the implementation of the nurturing function of politics and the enhancement of the teaching effect, this paper proposes a...

Research on the Path of Enhancing Students’ Political Identity in Teaching Ethics and Rule of Law in the Information Age

Publié en ligne: 31 janv. 2024

Pages: -

Reçu: 20 déc. 2023

Accepté: 29 déc. 2023

DOI: https://doi.org/10.2478/amns-2024-0218

Mots clés
Multimodal fusion, TF-IDF method, LBP facial features, deep RNN, Political identity

© 2024 Jia Zhang et al., published by Sciendo

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

Research on the Path of Enhancing Students’ Political Identity in Teaching Ethics and Rule of Law in the Information Age

Publié en ligne: 31 janv. 2024

Pages: -

Reçu: 20 déc. 2023

Accepté: 29 déc. 2023

DOI: https://doi.org/10.2478/amns-2024-0218

Mots clésMultimodal fusion, TF-IDF method, LBP facial features, deep RNN, Political identity

© 2024 Jia Zhang et al., published by Sciendo

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

Mots clés
Multimodal fusion, TF-IDF method, LBP facial features, deep RNN, Political identity