{"title":"闽台合作大学学生成绩的k -均值聚类分析","authors":"Weixia Liu, Ying Chen","doi":"10.1109/ICEKIM52309.2021.00112","DOIUrl":null,"url":null,"abstract":"This study introduces the idea and basic workflow of the K-means clustering algorithm, which is then used to conduct a cluster analysis of the scores of financial-major students taking basic courses at Fujian Taiwan Cooperative University. Through a cluster analysis, the distribution of students' scores in each course is determined. It provides a basis on which teachers can formulate personalized guidance strategies and students can adjust their learning time and energy.","PeriodicalId":337654,"journal":{"name":"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"K-means cluster analysis of student performance at a Fujian Taiwan Cooperative University\",\"authors\":\"Weixia Liu, Ying Chen\",\"doi\":\"10.1109/ICEKIM52309.2021.00112\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study introduces the idea and basic workflow of the K-means clustering algorithm, which is then used to conduct a cluster analysis of the scores of financial-major students taking basic courses at Fujian Taiwan Cooperative University. Through a cluster analysis, the distribution of students' scores in each course is determined. It provides a basis on which teachers can formulate personalized guidance strategies and students can adjust their learning time and energy.\",\"PeriodicalId\":337654,\"journal\":{\"name\":\"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)\",\"volume\":\"129 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEKIM52309.2021.00112\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEKIM52309.2021.00112","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
K-means cluster analysis of student performance at a Fujian Taiwan Cooperative University
This study introduces the idea and basic workflow of the K-means clustering algorithm, which is then used to conduct a cluster analysis of the scores of financial-major students taking basic courses at Fujian Taiwan Cooperative University. Through a cluster analysis, the distribution of students' scores in each course is determined. It provides a basis on which teachers can formulate personalized guidance strategies and students can adjust their learning time and energy.