S. Crossley, M. Dascalu, D. McNamara, R. Baker, Stefan Trausan-Matu
{"title":"Predicting Success in Massive Open Online Courses (MOOCs) Using Cohesion Network Analysis","authors":"S. Crossley, M. Dascalu, D. McNamara, R. Baker, Stefan Trausan-Matu","doi":"10.22318/CSCL2017.17","DOIUrl":null,"url":null,"abstract":"This study uses Cohesion Network Analysis (CNA) indices to identify student patterns related to course completion in a massive open online course (MOOC). This analysis examines a subsample of 320 students who completed at least one graded assignment and produced at least 50 words in discussion forums in a MOOC on educational data mining. The findings indicate that CNA indices predict with substantial accuracy (76%) whether students complete the MOOC, helping us to better understand student retention in this MOOC and to develop more actionable automated signals of student success.","PeriodicalId":120843,"journal":{"name":"International Conference on Computer Supported Collaborative Learning","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Computer Supported Collaborative Learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22318/CSCL2017.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31
Abstract
This study uses Cohesion Network Analysis (CNA) indices to identify student patterns related to course completion in a massive open online course (MOOC). This analysis examines a subsample of 320 students who completed at least one graded assignment and produced at least 50 words in discussion forums in a MOOC on educational data mining. The findings indicate that CNA indices predict with substantial accuracy (76%) whether students complete the MOOC, helping us to better understand student retention in this MOOC and to develop more actionable automated signals of student success.