Multi-Dimensional Analysis of Subjective and Objective Empowerment Methods in Online Civic Education
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To enhance the scientificity and effectiveness of online ideological and political education (Cyber Civics), this article aims to construct a multi-dimensional and quantifiable evaluation model. Methodologically, the article starts from the four dimensions of education subject, object, content, and medium, combines subjective empowerment (hierarchical analysis method AHP) and objective empowerment (entropy power method), and introduces an intelligent optimization algorithm - the long-nosed Cuckoo Optimization Algorithm (COA) to optimize the combination of weights, and constructs the COA-Mixed Cyber Ideology and Political Education Evaluation model. The results show that the model is better than the traditional model in terms of weight distribution, with the four-dimensional index weights of 0.358 for the educational subject, 0.245 for the educational object, 0.207 for the educational content, 0.189 for the educational medium, and the maximum composite score of the sample is 0.875, and the optimization coefficient of the model prediction error is α=0.35, which is significantly better than that of GWO-Mixed (α=0.33) and KOA-Mixed (α=0.33). Mixed (α=0.36). It is concluded that multi-dimensional analysis combined with subjective and objective empowerment and intelligent algorithm optimization can more objectively and accurately assess the effectiveness of online ideological and political education, which provides a feasible path and theoretical support for improving the quality of ideological and political education in colleges and universities.
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