Exploring students’ learning behaviour in MOOCs using process mining techniques

P. Mukala, J.C.A.M. Buijs, W.M.P. Aalst, van der

Research output: Book/ReportReportAcademic

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Massive Open Online Courses (MOOCs) provide increasing opportunities for skills acquisition. Their widespread use can be justified by a number of critical motivating factors such as the possibility of free courses, the flexibility of the learning process as well as the reputation of some of the world most prestigious universities offering these courses. This level of popularity has created the need for a deep understanding of learning in MOOCs. This has been so far achieved through Learning Analytics (LA) using data mining techniques. Nevetheless, it is difficult to perform a sytematic analysis of learning processes based on students’ behaviour using these techniques alone. Therefore, we propose to apply process mining since it provides important techniques for understanding learning processes based on students’activities trails from MOOC platforms logs. In this paper, we analyze a Coursera MOOC dataset using several process mining techniques and provide some indications in terms of useful insights and guidance that could inspire intervention measures to improve both the quality and delivery of MOOCs. Keywords: Learning Analytics, Mooc, Coursera, Educational Data Mining, Process Mining,Online Learning
Original languageEnglish
PublisherBPMcenter. org
Number of pages26
Publication statusPublished - 2015

Publication series

NameBPM reports


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