Proceedings of the 3rd International Conference on New Media Development and Modernized Education, NMDME 2023, October 13–15, 2023, Xi’an, China

Research Article

Evolutionary Algorithm in the Evaluation Index System of Students' Comprehensive Moral Education Ability

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  • @INPROCEEDINGS{10.4108/eai.13-10-2023.2341314,
        author={Pan  Luo},
        title={Evolutionary Algorithm in the Evaluation Index System of Students' Comprehensive Moral Education Ability},
        proceedings={Proceedings of the 3rd International Conference on New Media Development and Modernized Education, NMDME 2023, October 13--15, 2023, Xi’an, China},
        publisher={EAI},
        proceedings_a={NMDME},
        year={2024},
        month={1},
        keywords={evolutionary algorithm; comprehensive evaluation of moral education; evaluating indicator},
        doi={10.4108/eai.13-10-2023.2341314}
    }
    
  • Pan Luo
    Year: 2024
    Evolutionary Algorithm in the Evaluation Index System of Students' Comprehensive Moral Education Ability
    NMDME
    EAI
    DOI: 10.4108/eai.13-10-2023.2341314
Pan Luo1,*
  • 1: Sichuan Technology Business College
*Contact email: 15208289477@163.com

Abstract

In order to understand the application of evolutionary algorithms in the comprehensive evaluation of student moral education, an application research based on evolutionary algorithms in the comprehensive evaluation of student moral education has been proposed. Firstly, we conducted an in-depth analysis of various factors that need to be considered in the comprehensive evaluation system for college students, including moral quality, intellectual level, physical health, aesthetic taste, labor skills, etc. These factors are crucial in evaluating a student's overall quality. Next, we specifically considered the unique situation of students at China University of Geosciences and conducted a comprehensive evaluation of their qualities from different dimensions. These dimensions include moral and ethical qualities. This multidimensional evaluation can provide a more comprehensive understanding of students' qualities and potential. Finally, in order to determine the weights of various evaluation indicators more objectively, we adopted evolutionary algorithms to determine the dimensions of each quality and the weights of each indicator, in order to better reflect the overall quality of students. This not only improves the objectivity of evaluation index weights, but also provides strong support for developing more reasonable evaluation standards.