H. Hayati, Jihane Sophia Tahiri, Mohammed Khalidi, S. Bennani
{"title":"Classification system of learners engagement within Massive Open Online Courses","authors":"H. Hayati, Jihane Sophia Tahiri, Mohammed Khalidi, S. Bennani","doi":"10.1109/CIST.2016.7805105","DOIUrl":null,"url":null,"abstract":"Engagement is one of the important key of success in academic process, the present article aims to model the classification system of learners in Massive Open Online Course (MOOC) based on their engagement levels. In this scope, our mission is to define the notion of engagement as well as establish its different levels. This will enable us to present an approach based on indicators measurement with the application of the k-means clustering classification algorithm, in order to group the learners depending on their engagement level, which will help tutors and developers to take good decisions and minimize the dropout rate.","PeriodicalId":196827,"journal":{"name":"2016 4th IEEE International Colloquium on Information Science and Technology (CiSt)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 4th IEEE International Colloquium on Information Science and Technology (CiSt)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIST.2016.7805105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Engagement is one of the important key of success in academic process, the present article aims to model the classification system of learners in Massive Open Online Course (MOOC) based on their engagement levels. In this scope, our mission is to define the notion of engagement as well as establish its different levels. This will enable us to present an approach based on indicators measurement with the application of the k-means clustering classification algorithm, in order to group the learners depending on their engagement level, which will help tutors and developers to take good decisions and minimize the dropout rate.
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