EDUCATIONAL FUZZY DATA-SETS AND DATA MINING IN A LINEAR FUZZY REAL ENVIRONMENT

Frank Rogers
{"title":"EDUCATIONAL FUZZY DATA-SETS AND DATA MINING IN A LINEAR FUZZY REAL ENVIRONMENT","authors":"Frank Rogers","doi":"10.30862/JHM.V2I2.81","DOIUrl":null,"url":null,"abstract":"Educational data mining is the process of converting raw data from educational systems to useful information that can be used by educational software developers, students, teachers, parents, and other educational researchers. Fuzzy educational datasets are datasets consisting of uncertain values. The purpose of this study is to develop and test a classification model under uncertainty unique to the modern student. This is done by developing a model of the uncertain data that come from an educational setting with Linear Fuzzy Real data. Machine learning was then used to understand students and their optimal learning environment. The ability to predict student performance is important in a web or online environment. This is true in the brick and mortar classroom as well and is especially important in rural areas where academic achievement is lower than ideal.","PeriodicalId":33215,"journal":{"name":"Journal of Honai Math","volume":"56 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Honai Math","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30862/JHM.V2I2.81","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Educational data mining is the process of converting raw data from educational systems to useful information that can be used by educational software developers, students, teachers, parents, and other educational researchers. Fuzzy educational datasets are datasets consisting of uncertain values. The purpose of this study is to develop and test a classification model under uncertainty unique to the modern student. This is done by developing a model of the uncertain data that come from an educational setting with Linear Fuzzy Real data. Machine learning was then used to understand students and their optimal learning environment. The ability to predict student performance is important in a web or online environment. This is true in the brick and mortar classroom as well and is especially important in rural areas where academic achievement is lower than ideal.
线性模糊真实环境下的教育模糊数据集与数据挖掘
教育数据挖掘是将来自教育系统的原始数据转换为可供教育软件开发人员、学生、教师、家长和其他教育研究人员使用的有用信息的过程。模糊教育数据集是由不确定值组成的数据集。本研究的目的是开发和检验一个现代学生特有的不确定性分类模型。这是通过开发一个不确定数据模型来完成的,这些数据来自一个教育环境,具有线性模糊真实数据。然后使用机器学习来了解学生和他们的最佳学习环境。在网络或在线环境中,预测学生表现的能力很重要。这在实体教室里也是如此,在学习成绩低于理想水平的农村地区尤其重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
11
审稿时长
6 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信