Reform and innovation of Civic Education combined with deep and intensive learning
In order to respond to the call for reform and innovation of Civic Education, this paper establishes a new teaching mode of Civic Education by combining a deep reinforcement learning model with a Civic Education platform. Firstly, the modules and functions of the platform are designed, in which the...
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| Format: | Article |
| Language: | English |
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Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns.2023.2.00472 |
| _version_ | 1797340764697526272 |
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| author | Kou Yilei Zhao Meng |
| author_facet | Kou Yilei Zhao Meng |
| author_sort | Kou Yilei |
| collection | DOAJ |
| description | In order to respond to the call for reform and innovation of Civic Education, this paper establishes a new teaching mode of Civic Education by combining a deep reinforcement learning model with a Civic Education platform. Firstly, the modules and functions of the platform are designed, in which the modules are divided into the pre-class module, in-class module, and after-class module, and the functions are divided into front and back office management system functions. Then the deep learning based on value function and strategy gradient combines the Civic Education platform with deep reinforcement learning and designs a deep reinforcement learning model for Civic Education, which meets the requirements of Civic Education reform and innovation. Finally, the teaching practice of Civic Education reform and innovation was carried out, and the average attendance rate of students was obtained, which was 92.7% in the first round and 95.3% in the second round. 79 students (72.5%) had an excellent attendance rate in the first round and 85.4% in the second round. At the beginning of the semester, 67.64% of the students’ thinking structure belonged to low-order thinking, only 7.65% of the students’ thinking reached the structure of the association and abstract expansion, at the end of the semester, 60.59% of the students’ thinking reached the structure of the association and abstract expansion. It is concluded that the reform and innovation of Civic Education can improve students’ attendance and improve their thinking ability. |
| first_indexed | 2024-03-08T10:08:03Z |
| format | Article |
| id | doaj.art-c0e5e22ca99549008f3bc0dbbb1e813c |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:08:03Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-c0e5e22ca99549008f3bc0dbbb1e813c2024-01-29T08:52:33ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.2.00472Reform and innovation of Civic Education combined with deep and intensive learningKou Yilei0Zhao Meng11College of Electrical Engineering, North China University of Science and Technology, Tangshan, Hebei, 063210, China.2Marxist College of Marxism, North China University of Science and Technology, Tangshan, Hebei, 063210, China.In order to respond to the call for reform and innovation of Civic Education, this paper establishes a new teaching mode of Civic Education by combining a deep reinforcement learning model with a Civic Education platform. Firstly, the modules and functions of the platform are designed, in which the modules are divided into the pre-class module, in-class module, and after-class module, and the functions are divided into front and back office management system functions. Then the deep learning based on value function and strategy gradient combines the Civic Education platform with deep reinforcement learning and designs a deep reinforcement learning model for Civic Education, which meets the requirements of Civic Education reform and innovation. Finally, the teaching practice of Civic Education reform and innovation was carried out, and the average attendance rate of students was obtained, which was 92.7% in the first round and 95.3% in the second round. 79 students (72.5%) had an excellent attendance rate in the first round and 85.4% in the second round. At the beginning of the semester, 67.64% of the students’ thinking structure belonged to low-order thinking, only 7.65% of the students’ thinking reached the structure of the association and abstract expansion, at the end of the semester, 60.59% of the students’ thinking reached the structure of the association and abstract expansion. It is concluded that the reform and innovation of Civic Education can improve students’ attendance and improve their thinking ability.https://doi.org/10.2478/amns.2023.2.00472civic educationdeep reinforcement learningcivic education platformvalue functionstrategy gradientthinking structure97b20 |
| spellingShingle | Kou Yilei Zhao Meng Reform and innovation of Civic Education combined with deep and intensive learning Applied Mathematics and Nonlinear Sciences civic education deep reinforcement learning civic education platform value function strategy gradient thinking structure 97b20 |
| title | Reform and innovation of Civic Education combined with deep and intensive learning |
| title_full | Reform and innovation of Civic Education combined with deep and intensive learning |
| title_fullStr | Reform and innovation of Civic Education combined with deep and intensive learning |
| title_full_unstemmed | Reform and innovation of Civic Education combined with deep and intensive learning |
| title_short | Reform and innovation of Civic Education combined with deep and intensive learning |
| title_sort | reform and innovation of civic education combined with deep and intensive learning |
| topic | civic education deep reinforcement learning civic education platform value function strategy gradient thinking structure 97b20 |
| url | https://doi.org/10.2478/amns.2023.2.00472 |
| work_keys_str_mv | AT kouyilei reformandinnovationofciviceducationcombinedwithdeepandintensivelearning AT zhaomeng reformandinnovationofciviceducationcombinedwithdeepandintensivelearning |