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<p>Multicultural integration brings opportunities and challenges to the field of education, and the innovation of Civics education in higher vocational colleges and universities becomes increasingly essential. In this paper, the reinforcement learning algorithm is used to construct a Civics teaching mode with precise teaching intervention, which quantifies students’ learning ability and learning status by combining the Civics learning ability level parameter. The difficulty coefficient of Civics exercises determines the students’ mastery of Civics content. Based on the students’ Civics learning ability and learning status, a precise teaching intervention strategy was formulated, and the teaching intervention was used in practice to explore the effectiveness of the accurate intervention Civics teaching model in terms of the change of students’ ability and performance. The results show that under the Precision Intervention Civics Teaching Model, students with low collaborative learning and high problem-solving ability changed from unidirectional PR→RS to bidirectional PA↔PR, indicating that the Precision Intervention Teaching Model can improve students’ learning ability. The passing rate of students under this model were maintained at 70%, the average score was above 70, and the students’ performance in Civics was significantly improved compared with the traditional teaching model.</p>
</abstract>

Multicultural integration brings opportunities and challenges to the field of education, and the innovation of Civics education in higher vocational colleges and universities becomes increasingly essential. In this paper, the reinforcement learning algorithm is used to construct a Civics teaching mode with precise teaching intervention, which quantifies students’ learning ability and learning status by combining the Civics learning ability level parameter. The difficulty coefficient of Civics exercises determines the students’ mastery of Civics content. Based on the students’ Civics learning ability and learning status, a precise teaching intervention strategy was formulated, and the teaching intervention was used in practice to explore the effectiveness of the accurate intervention Civics teaching model in terms of the change of students’ ability and performance. The results show that under the Precision Intervention Civics Teaching Model, students with low collaborative learning and high problem-solving ability changed from unidirectional PR→RS to bidirectional PA↔PR, indicating that the Precision Intervention Teaching Model can improve students’ learning ability. The passing rate of students under this model were maintained at 70%, the average score was above 70, and the students’ performance in Civics was significantly improved compared with the traditional teaching model.

Innovative Development of Civic and Political Education in Higher Vocational Colleges and Universities in the Context of Multiculturalism

Applied Mathematics and Nonlinear Sciences

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

Multicultural integration brings opportunities and challenges to the field of education, and the innovation of Civics education in higher vocational colleges...

Innovative Development of Civic and Political Education in Higher Vocational Colleges and Universities in the Context of Multiculturalism

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 10. Jan. 2024

Akzeptiert: 16. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0481

Schlüsselwörter
Competence level parameter, Reinforcement learning algorithm, Quantification of learning status, Civics education

© 2024 Dan Li, published by Sciendo

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

Innovative Development of Civic and Political Education in Higher Vocational Colleges and Universities in the Context of Multiculturalism

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 10. Jan. 2024

Akzeptiert: 16. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0481

SchlüsselwörterCompetence level parameter, Reinforcement learning algorithm, Quantification of learning status, Civics education

© 2024 Dan Li, published by Sciendo

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

Schlüsselwörter
Competence level parameter, Reinforcement learning algorithm, Quantification of learning status, Civics education