Advanced Hybrid Information Processing. First International Conference, ADHIP 2017, Harbin, China, July 17–18, 2017, Proceedings

Research Article

The Comprehensive Quality Evaluation of Minority Students in Colleges and Universities Based on Principle of Information Entropy

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  • @INPROCEEDINGS{10.1007/978-3-319-73317-3_37,
        author={Wu Wang and Lina Shan and Yunjie Gu},
        title={The Comprehensive Quality Evaluation of Minority Students in Colleges and Universities Based on Principle of Information Entropy},
        proceedings={Advanced Hybrid Information Processing. First International Conference, ADHIP 2017, Harbin, China, July 17--18, 2017, Proceedings},
        proceedings_a={ADHIP},
        year={2018},
        month={2},
        keywords={Minority students Evaluation index Principle of information entropy Comprehensive quality},
        doi={10.1007/978-3-319-73317-3_37}
    }
    
  • Wu Wang
    Lina Shan
    Yunjie Gu
    Year: 2018
    The Comprehensive Quality Evaluation of Minority Students in Colleges and Universities Based on Principle of Information Entropy
    ADHIP
    Springer
    DOI: 10.1007/978-3-319-73317-3_37
Wu Wang1, Lina Shan2,*, Yunjie Gu2
  • 1: Youth League Committee of Inner Mongolia University of Technology
  • 2: Harbin University of Science and Technology
*Contact email: linashan@126.com

Abstract

The paper does the analysis to the quality character of minority students in Colleges and Universities and there are four evaluation indexes which are suitable for the students: language and communication skills, academic performance and professional skills, personality accomplishment and psychological quality and democratic spirit and patriotism. Based on principle of information entropy, it analyzes the random sample of Inner Mongolia University of Technology graduate and makes use of the entropy to confirm the weight of each evaluation index to the influence of the comprehensive quality. It builds the linear evaluation model to get the comprehensive evaluation index and compares the result calculated by model and the student graduation test to prove the feasible of model with Pearson correlation coefficient.