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<p>To enrich the content and form of college civic education, this paper constructs a civic education management innovation platform based on big data technology to explore the innovative development path of college civic education. Using the differentiated fusion algorithm, the information processing of college student management data is carried out, and the educational mining information of college students is identified through feature extraction. Bayesian network is introduced in the process of index weight calculation to improve the data mining efficiency to ensure the validity of obtaining the evaluation index of Civic Education. To verify the feasibility of the innovation platform of Civic Education Management based on big data technology, the application effect was tested. The analysis results show that the platform constructed in this paper can make students’ cognitive awareness of course contents reach 0.98, students’ concentration effect reach 0.89, and the overall effect of teaching feedback reach 90% in selecting teaching resources. The average test score of students in the experimental group was 8.5, and the average length range of the independent learning course was 2.78-4.629 hours. Thus, it can be seen that the platform constructed in this paper is conducive to promoting the high-quality development of Civics teaching and enhancing the effectiveness of Civics education in colleges and universities.</p>
</abstract>

To enrich the content and form of college civic education, this paper constructs a civic education management innovation platform based on big data technology to explore the innovative development path of college civic education. Using the differentiated fusion algorithm, the information processing of college student management data is carried out, and the educational mining information of college students is identified through feature extraction. Bayesian network is introduced in the process of index weight calculation to improve the data mining efficiency to ensure the validity of obtaining the evaluation index of Civic Education. To verify the feasibility of the innovation platform of Civic Education Management based on big data technology, the application effect was tested. The analysis results show that the platform constructed in this paper can make students’ cognitive awareness of course contents reach 0.98, students’ concentration effect reach 0.89, and the overall effect of teaching feedback reach 90% in selecting teaching resources. The average test score of students in the experimental group was 8.5, and the average length range of the independent learning course was 2.78-4.629 hours. Thus, it can be seen that the platform constructed in this paper is conducive to promoting the high-quality development of Civics teaching and enhancing the effectiveness of Civics education in colleges and universities.

Analysis of the innovative development path of university civic education based on the era of big data

Xinjiang Normal University Business School

Applied Mathematics and Nonlinear Sciences

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

To enrich the content and form of college civic education, this paper constructs a civic education management innovation platform based on big data technology...

Analysis of the innovative development path of university civic education based on the era of big data

Online veröffentlicht: 09. Juni 2023

Seitenbereich: -

Eingereicht: 08. Sept. 2022

Akzeptiert: 15. Dez. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00378

Schlüsselwörter
Big data technology, Differentiated fusion algorithm, Feature extraction, Bayesian network, Ideological education management innovation platform

© 2023 Xingang Chen et al., published by Sciendo

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

Analysis of the innovative development path of university civic education based on the era of big data

Online veröffentlicht: 09. Juni 2023

Seitenbereich: -

Eingereicht: 08. Sept. 2022

Akzeptiert: 15. Dez. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00378

SchlüsselwörterBig data technology, Differentiated fusion algorithm, Feature extraction, Bayesian network, Ideological education management innovation platform

© 2023 Xingang Chen et al., published by Sciendo

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

Schlüsselwörter
Big data technology, Differentiated fusion algorithm, Feature extraction, Bayesian network, Ideological education management innovation platform