{"title":"K-12教育的数据科学","authors":"Julie L. Harvey, S. Kumar","doi":"10.1109/SSCI44817.2019.9002940","DOIUrl":null,"url":null,"abstract":"Data science is a field that can be used in a variety of settings. Education is one of the fields that is expanding its use of data science to improve the quality of education. The United States denotes primary and secondary school as grades kindergarten (K) through 12th grade. This is representative of education prior to college/university level. Data science in K-12 education is evaluated and important to the field of education because educators, administrators, and stakeholders are always looking for ways to close the achievement gap and increase performance of all students. Student performance evaluation using data science is crucial to closing this gap. Data mining is used in the evaluation and analysis of student performance, educational programs and educational instruction. It is also used to create prediction models for future student success. A K-12 education dataset will be used to evaluate student performance. This paper will explore and display student performance based on a variety of factors and data. Data science in K-12 education and its impact on student performance and educator use of this data is discussed. We have also performed review of existing work in the data analytics for K-12 education along with their limitations.","PeriodicalId":6729,"journal":{"name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"7 1","pages":"2482-2488"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Data Science for K-12 Education\",\"authors\":\"Julie L. Harvey, S. Kumar\",\"doi\":\"10.1109/SSCI44817.2019.9002940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data science is a field that can be used in a variety of settings. Education is one of the fields that is expanding its use of data science to improve the quality of education. The United States denotes primary and secondary school as grades kindergarten (K) through 12th grade. This is representative of education prior to college/university level. Data science in K-12 education is evaluated and important to the field of education because educators, administrators, and stakeholders are always looking for ways to close the achievement gap and increase performance of all students. Student performance evaluation using data science is crucial to closing this gap. Data mining is used in the evaluation and analysis of student performance, educational programs and educational instruction. It is also used to create prediction models for future student success. A K-12 education dataset will be used to evaluate student performance. This paper will explore and display student performance based on a variety of factors and data. Data science in K-12 education and its impact on student performance and educator use of this data is discussed. We have also performed review of existing work in the data analytics for K-12 education along with their limitations.\",\"PeriodicalId\":6729,\"journal\":{\"name\":\"2019 IEEE Symposium Series on Computational Intelligence (SSCI)\",\"volume\":\"7 1\",\"pages\":\"2482-2488\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Symposium Series on Computational Intelligence (SSCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSCI44817.2019.9002940\",\"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 IEEE Symposium Series on Computational Intelligence (SSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSCI44817.2019.9002940","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data science is a field that can be used in a variety of settings. Education is one of the fields that is expanding its use of data science to improve the quality of education. The United States denotes primary and secondary school as grades kindergarten (K) through 12th grade. This is representative of education prior to college/university level. Data science in K-12 education is evaluated and important to the field of education because educators, administrators, and stakeholders are always looking for ways to close the achievement gap and increase performance of all students. Student performance evaluation using data science is crucial to closing this gap. Data mining is used in the evaluation and analysis of student performance, educational programs and educational instruction. It is also used to create prediction models for future student success. A K-12 education dataset will be used to evaluate student performance. This paper will explore and display student performance based on a variety of factors and data. Data science in K-12 education and its impact on student performance and educator use of this data is discussed. We have also performed review of existing work in the data analytics for K-12 education along with their limitations.