sis 24(2):

Research Article

Application of Big Data Technology to Evaluate Gray Correlation Entropy in higher Education Sector

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  • @ARTICLE{10.4108/eetsis.4448,
        author={Limei Wang},
        title={Application of Big Data Technology to Evaluate Gray Correlation Entropy in higher Education Sector},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={11},
        number={2},
        publisher={EAI},
        journal_a={SIS},
        year={2023},
        month={11},
        keywords={ideological and political competence in colleges and universities, gray correlation entropy by AI, index system, ideological and political competence capacity},
        doi={10.4108/eetsis.4448}
    }
    
  • Limei Wang
    Year: 2023
    Application of Big Data Technology to Evaluate Gray Correlation Entropy in higher Education Sector
    SIS
    EAI
    DOI: 10.4108/eetsis.4448
Limei Wang1,*
  • 1: Shangqiu Institute of Technology
*Contact email: m15037058899@163.com

Abstract

INTRODUCTION: The quality of ideological and political competence in colleges and universities is crucial to cultivating socialist builders and successors with all-round development of morality, intelligence, physical fitness, and aesthetics. OBJECTIVES: To scientifically evaluate the capacity of ideological and political competence in colleges and universities, adopt the evaluation method based on gray correlation entropy in AI to construct a complete indicator system that comprehensively reflects multiple aspects of ideological and political competence in colleges and universities. METHODS: By quantitatively analyzing the indicators and comprehensively considering the weights and degree of correlation of the hands, the evaluation results of the ideological and political competence capacity of colleges and universities can be derived, and this method can objectively and scientifically assess the strengths and weaknesses of the ideological and political competence capacity of colleges and universities and provide colleges and universities with the basis for improving and optimizing ideological and political competence. RESULTS: The evaluation method based on gray correlation entropy in the context of AI helps to improve the quality and effect of ideological and political competence in colleges and universities and promotes the overall improvement of students' ideological and political quality, as seen through the analysis of examples. CONCLUSION: The evaluation method also provides new ideas and plans for the research of the ideological and political competence capacity of colleges and universities, which has strong feasibility and practicality and offers colleges and universities the basis for the scientific evaluation of ideological and political competence, which helps to improve the quality and level of ideological and political competence in colleges and universities.