Content area
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.
Details
Course Selection (Students);
Innovation;
Ideology;
Natural Language Processing;
Knowledge Level;
Artificial Intelligence;
Language Processing;
Educational Environment;
Algorithms;
Moral Issues;
Educational Resources;
Influence of Technology;
Distance Education;
Addition;
Equal Education;
Educational Technology;
Periodicals;
Creative Teaching;
Ethics;
Data Analysis;
Preferences;
Opportunities;
Higher Education;
Individual Needs
Collaborative learning;
Moral education;
Algorithms;
Deep learning;
Computer assisted instruction--CAI;
Distance learning;
Politics;
Technology;
Machine learning;
Artificial intelligence;
Education;
Neural networks;
Ideology;
Learning;
Customization;
Recursion;
Cooperative learning;
Colleges & universities;
Variants;
Pandemics
