Understanding Learners Behavior in Massive Open Online Courses

2020 XLVI Latin American Computing Conference (CLEI) Pub Date : 2020-10-01 DOI:10.1109/CLEI52000.2020.00050

Jorge Maldonado-Mahauad, Mauricio Calle, Miguel Macías, Christian Moreira, Edwin Narvaez, David Valladarez

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Abstract

Massive Open Online Courses (MOOCs) are one of the most disruptive trends of recent years, attracting millions of students around the world. This has caught the attention of researchers who seek to understand the behavior of students in these courses. However, despite the efforts, approval rates remain below 5%, so more efforts are needed to understand why students end a MOOC or not. The goal of this work is to study learner's behavior in a MOOC. Specifically, it seeks to understand student interaction sequences with course resources and characterize their study sessions throughout MOOC weeks. For this, using Process Mining techniques, data from N = 38,838 learners enrolled in a MOOC in Coursera were analyzed. As a result of the analysis of learner's interactions with MOOCs, two groups of students were observed as comprehensive and strategic. In addition, differences in learning sequences were found among students from both groups who approved the MOOC. These results help advance current literature and open the debate about whether MOOCs remain open courses or a digital book.

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大规模在线开放课程中学习者行为的研究

大规模在线开放课程(MOOCs)是近年来最具颠覆性的趋势之一，吸引了全球数百万学生。这引起了研究人员的注意，他们试图了解学生在这些课程中的行为。然而，尽管做出了努力，但满意率仍低于5%，因此需要更多的努力来了解学生们为什么会结束MOOC课程。本研究的目的是研究MOOC中学习者的行为。具体来说，它试图了解学生与课程资源的互动顺序，并在MOOC周内描述他们的学习课程。为此，使用过程挖掘技术，分析了在Coursera上注册MOOC的N = 38,838名学习者的数据。通过对学习者与mooc互动的分析，我们观察到两组学生是全面的和战略性的。此外，两组认可MOOC的学生在学习顺序上也存在差异。这些结果有助于推进当前的文献，并开启了关于mooc是开放课程还是电子书的辩论。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2020 XLVI Latin American Computing Conference (CLEI)

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