{"title":"基于信息熵的学科建设学生满意度优化评价","authors":"Limei Liu, Xiuling Li, Xiao-Sheng Cai","doi":"10.1109/ICVRIS.2019.00037","DOIUrl":null,"url":null,"abstract":"Aiming at evaluating the student satisfaction in discipline construction scientifically and effectively, an optimization evaluation method of student satisfaction in discipline construction based on information entropy and principal component analysis is proposed. The influencing factors of student satisfaction are obtained by using literature method and multivariate statistical analysis. These influence factors take into account both generality and individuality in different disciplines. Due to the number of influence factors is too large, the calculation burdens in evaluation need to be considered. Therefore, comprehensive determinants of students' satisfaction in discipline construction are defined in this paper. Comprehensive determinants of students' satisfaction in discipline construction are defined to be teachers' conditions, teaching conditions and practical conditions by principal component analysis method. Weights of comprehensive determinants in optimization evaluation are computed by entropy weight method. The experimental results verify the validity and feasibility of the optimization evaluation method of student satisfaction in discipline construction proposed in this paper.","PeriodicalId":294342,"journal":{"name":"2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization Evaluation of Student Satisfaction in Discipline Construction Based on Information Entropy\",\"authors\":\"Limei Liu, Xiuling Li, Xiao-Sheng Cai\",\"doi\":\"10.1109/ICVRIS.2019.00037\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at evaluating the student satisfaction in discipline construction scientifically and effectively, an optimization evaluation method of student satisfaction in discipline construction based on information entropy and principal component analysis is proposed. The influencing factors of student satisfaction are obtained by using literature method and multivariate statistical analysis. These influence factors take into account both generality and individuality in different disciplines. Due to the number of influence factors is too large, the calculation burdens in evaluation need to be considered. Therefore, comprehensive determinants of students' satisfaction in discipline construction are defined in this paper. Comprehensive determinants of students' satisfaction in discipline construction are defined to be teachers' conditions, teaching conditions and practical conditions by principal component analysis method. Weights of comprehensive determinants in optimization evaluation are computed by entropy weight method. The experimental results verify the validity and feasibility of the optimization evaluation method of student satisfaction in discipline construction proposed in this paper.\",\"PeriodicalId\":294342,\"journal\":{\"name\":\"2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICVRIS.2019.00037\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVRIS.2019.00037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization Evaluation of Student Satisfaction in Discipline Construction Based on Information Entropy
Aiming at evaluating the student satisfaction in discipline construction scientifically and effectively, an optimization evaluation method of student satisfaction in discipline construction based on information entropy and principal component analysis is proposed. The influencing factors of student satisfaction are obtained by using literature method and multivariate statistical analysis. These influence factors take into account both generality and individuality in different disciplines. Due to the number of influence factors is too large, the calculation burdens in evaluation need to be considered. Therefore, comprehensive determinants of students' satisfaction in discipline construction are defined in this paper. Comprehensive determinants of students' satisfaction in discipline construction are defined to be teachers' conditions, teaching conditions and practical conditions by principal component analysis method. Weights of comprehensive determinants in optimization evaluation are computed by entropy weight method. The experimental results verify the validity and feasibility of the optimization evaluation method of student satisfaction in discipline construction proposed in this paper.