Sraidi Soukaina, Smaili El Miloud, Salma Azzouzi, M. E. H. Charaf
{"title":"Quality Approach to Analyze the Causes of Failures in MOOC","authors":"Sraidi Soukaina, Smaili El Miloud, Salma Azzouzi, M. E. H. Charaf","doi":"10.1109/CloudTech49835.2020.9365904","DOIUrl":null,"url":null,"abstract":"Massive Open Online Courses (MOOC) have become popular around the world as a free way of online learning. However, one of the crucial problems associated with MOOC is their low completion rate. The analysis of data obtained from the forums and the social media groups associated with MOOCS provides a helpful mean to understand the behavior of the learners. The idea is to examine the correlation between the sentiment level reported on the basis of the forum messages and the rate of students dropping out of the courses. Moreover, a good number of quality tools are used on the domain of Education. Therefore, we propose in this paper to combine the Sentiment Analysis (Machine learning approach) of the forum posts and the ISHIKAWA method (Quality approach) to handle these issues. The aim is to predict the main causes of MOOCs’ failures","PeriodicalId":272860,"journal":{"name":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CloudTech49835.2020.9365904","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Massive Open Online Courses (MOOC) have become popular around the world as a free way of online learning. However, one of the crucial problems associated with MOOC is their low completion rate. The analysis of data obtained from the forums and the social media groups associated with MOOCS provides a helpful mean to understand the behavior of the learners. The idea is to examine the correlation between the sentiment level reported on the basis of the forum messages and the rate of students dropping out of the courses. Moreover, a good number of quality tools are used on the domain of Education. Therefore, we propose in this paper to combine the Sentiment Analysis (Machine learning approach) of the forum posts and the ISHIKAWA method (Quality approach) to handle these issues. The aim is to predict the main causes of MOOCs’ failures