Theories and Methods of Online Ideological and Political Education for College Students in the Context of Deep Learning
This paper designs a teaching mode for online ideological and political education under deep learning, designing teaching content in a structured, contextualized and activity-based way to enhance teaching effectiveness and learning experience. By mining the learning needs embedded in users’ learning...
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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.2023.2.01442 |
| _version_ | 1797340581987352576 |
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| author | Yang Hongling |
| author_facet | Yang Hongling |
| author_sort | Yang Hongling |
| collection | DOAJ |
| description | This paper designs a teaching mode for online ideological and political education under deep learning, designing teaching content in a structured, contextualized and activity-based way to enhance teaching effectiveness and learning experience. By mining the learning needs embedded in users’ learning behaviors, customized learning resources are provided for each student to meet the personalized learning needs of different students. It also uses knowledge-forgetting matrix decomposition technology to identify and recommend key knowledge points in teaching content, helping students master important knowledge more effectively. The teaching mode proposed in this paper performs well in resource recommendation, with an average server response time of 15.147ms, while the students’ preference time is above 0.940s, which effectively improves the educational and teaching effect of the theory and method of online ideological and political education for college students. |
| first_indexed | 2024-03-08T10:05:13Z |
| format | Article |
| id | doaj.art-dc3d5ec581ce47f38cbee0905bf522b8 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:05:13Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-dc3d5ec581ce47f38cbee0905bf522b82024-01-29T08:52:43ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.2.01442Theories and Methods of Online Ideological and Political Education for College Students in the Context of Deep LearningYang Hongling01School of Management, Guangdong Industry Polytechnic, Guangzhou, Guangdong, 510300, China.This paper designs a teaching mode for online ideological and political education under deep learning, designing teaching content in a structured, contextualized and activity-based way to enhance teaching effectiveness and learning experience. By mining the learning needs embedded in users’ learning behaviors, customized learning resources are provided for each student to meet the personalized learning needs of different students. It also uses knowledge-forgetting matrix decomposition technology to identify and recommend key knowledge points in teaching content, helping students master important knowledge more effectively. The teaching mode proposed in this paper performs well in resource recommendation, with an average server response time of 15.147ms, while the students’ preference time is above 0.940s, which effectively improves the educational and teaching effect of the theory and method of online ideological and political education for college students.https://doi.org/10.2478/amns.2023.2.01442deep learningmatrix decompositiononline ideological and politicalresource recommendationresponse time00a35 |
| spellingShingle | Yang Hongling Theories and Methods of Online Ideological and Political Education for College Students in the Context of Deep Learning Applied Mathematics and Nonlinear Sciences deep learning matrix decomposition online ideological and political resource recommendation response time 00a35 |
| title | Theories and Methods of Online Ideological and Political Education for College Students in the Context of Deep Learning |
| title_full | Theories and Methods of Online Ideological and Political Education for College Students in the Context of Deep Learning |
| title_fullStr | Theories and Methods of Online Ideological and Political Education for College Students in the Context of Deep Learning |
| title_full_unstemmed | Theories and Methods of Online Ideological and Political Education for College Students in the Context of Deep Learning |
| title_short | Theories and Methods of Online Ideological and Political Education for College Students in the Context of Deep Learning |
| title_sort | theories and methods of online ideological and political education for college students in the context of deep learning |
| topic | deep learning matrix decomposition online ideological and political resource recommendation response time 00a35 |
| url | https://doi.org/10.2478/amns.2023.2.01442 |
| work_keys_str_mv | AT yanghongling theoriesandmethodsofonlineideologicalandpoliticaleducationforcollegestudentsinthecontextofdeeplearning |