Dirlene Ramalho da Silva, Simone de Lima Martins, Cristiano Maciel
{"title":"识别和系统化用于检测远程教育逃避的指标和数据挖掘技术","authors":"Dirlene Ramalho da Silva, Simone de Lima Martins, Cristiano Maciel","doi":"10.1109/LACLO.2017.8120892","DOIUrl":null,"url":null,"abstract":"This article presents a survey of the factors that indicate evasion in distance education, as well as the data mining techniques that are being used in the detection of evasion. As a methodology, we have used the systematic review, analyzing the works published in the last five years. The result indicated that there are multiple factors that influence evasion, which were systematized in four dimensions, being related to the students, the institution, the teachers and external factors.","PeriodicalId":278097,"journal":{"name":"2017 Twelfth Latin American Conference on Learning Technologies (LACLO)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Identification and systematization of indicatives and data mining techniques for detecting evasion in distance education\",\"authors\":\"Dirlene Ramalho da Silva, Simone de Lima Martins, Cristiano Maciel\",\"doi\":\"10.1109/LACLO.2017.8120892\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents a survey of the factors that indicate evasion in distance education, as well as the data mining techniques that are being used in the detection of evasion. As a methodology, we have used the systematic review, analyzing the works published in the last five years. The result indicated that there are multiple factors that influence evasion, which were systematized in four dimensions, being related to the students, the institution, the teachers and external factors.\",\"PeriodicalId\":278097,\"journal\":{\"name\":\"2017 Twelfth Latin American Conference on Learning Technologies (LACLO)\",\"volume\":\"86 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Twelfth Latin American Conference on Learning Technologies (LACLO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LACLO.2017.8120892\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Twelfth Latin American Conference on Learning Technologies (LACLO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LACLO.2017.8120892","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identification and systematization of indicatives and data mining techniques for detecting evasion in distance education
This article presents a survey of the factors that indicate evasion in distance education, as well as the data mining techniques that are being used in the detection of evasion. As a methodology, we have used the systematic review, analyzing the works published in the last five years. The result indicated that there are multiple factors that influence evasion, which were systematized in four dimensions, being related to the students, the institution, the teachers and external factors.