文章基本信息

标题：Internationalizing Professional Development: Using Educational Data Mining to Analyze Learners’ Performance and Dropouts in a French MOOC
其他标题：Internationalizing Professional Development: Using Educational Data Mining to Analyze Learners’ Performance and Dropouts in a French MOOC
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作者：Rawad Chaker ; Rémi Bachelet
期刊名称：The International Review of Research in Open and Distributed Learning
印刷版ISSN：1492-3831
出版年度：2020
卷号：21
期号：4
页码：199-221
DOI：10.19173/irrodl.v21i4.4787
出版社：AU Press
摘要：This paper uses data mining from a French project management MOOC to study learners’ performance (i.e., grades and persistence) based on a series of variables: age, educational background, socio-professional status, geographical area, gender, self- versus mandatory-enrollment, and learning intentions. Unlike most studies in this area, we focus on learners from the French-speaking world: France and French-speaking European countries, the Caribbean, North Africa, and Central and West Africa. Results show that the largest gaps in MOOC achievements occur between 1) learners from partner institutions versus self-enrolled learners 2) learners from European countries versus low- and middle-income countries, and 3) learners who are professionally active versus inactive learners (i.e., with available time). Finally, we used the CHAID data-mining method to analyze the main characteristics and discriminant factors of MOOC learner performance and dropout.
关键词：MOOCs;learner grades;learner dropout;learner performance;academic cohorts;educational data mining;CHAID;low- and middle-income countries;developing countries