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Construction and Implementation of Ideological and Political Education Platforms Based on Artificial Intelligence Technology

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Bibliographic Details
Title: Construction and Implementation of Ideological and Political Education Platforms Based on Artificial Intelligence Technology
Language: English
Authors: Ni Li
Source: International Journal of Web-Based Learning and Teaching Technologies. 2025 20(1).
Availability: IGI Global. 701 East Chocolate Avenue, Hershey, PA 17033. Tel: 866-342-6657; Tel: 717-533-8845; Fax: 717-533-8661; Fax: 717-533-7115; e-mail: journals@igi-global.com; Web site: https://www.igi-global.com/journals/
Peer Reviewed: Y
Page Count: 23
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Algorithms, Online Courses, Learning Management Systems, Political Attitudes, Ideology, Moral Development, Efficiency, Individualized Instruction, Behavior Patterns, Accuracy, Course Content, Global Approach, Political Science, Comparative Education, Pandemics, COVID-19, Foreign Countries, Best Practices, Learning Analytics, Higher Education
Geographic Terms: United States, Europe, Latin America, Asia, Africa
DOI: 10.4018/ijwltt.372072
ISSN: 1548-1093
1548-1107
Abstract: In depth exploration of how the pandemic has reshaped the education ecosystem over the past three years, especially in the context of the surge in demand for online education courses and learning platforms, this article focuses on the field of student ideological and political education, and innovatively constructs a moral and political education platform that integrates efficiency, interactivity, and personalization. Through in-depth analysis of existing online education platforms in the market, we found that although these platforms have the potential for remote teaching in terms of technology. By introducing advanced artificial intelligence technologies, especially recursive neural networks (RNNs) and their variants in deep learning, traditional collaborative recommendation algorithms are revolutionized. This improvement not only enhances the algorithm's understanding of user behavior patterns, but also more accurately captures users' potential points of interest and changes in needs, thereby achieving more personalized content recommendations.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1470435
Database: ERIC
Description
Abstract:In depth exploration of how the pandemic has reshaped the education ecosystem over the past three years, especially in the context of the surge in demand for online education courses and learning platforms, this article focuses on the field of student ideological and political education, and innovatively constructs a moral and political education platform that integrates efficiency, interactivity, and personalization. Through in-depth analysis of existing online education platforms in the market, we found that although these platforms have the potential for remote teaching in terms of technology. By introducing advanced artificial intelligence technologies, especially recursive neural networks (RNNs) and their variants in deep learning, traditional collaborative recommendation algorithms are revolutionized. This improvement not only enhances the algorithm's understanding of user behavior patterns, but also more accurately captures users' potential points of interest and changes in needs, thereby achieving more personalized content recommendations.
ISSN:1548-1093
1548-1107
DOI:10.4018/ijwltt.372072