Analysing Structured Learning Behaviour in Massive Open Online Courses (MOOCs): An Approach Based on Process Mining and Clustering

The increasing use of digital systems to support learning leads to a growth in data regarding both learning processes and related contexts. Learning Analytics offers critical insights from these data, through an innovative combination of tools and techniques. In this paper, we explore students’ acti...

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Autores principales:	Antoine van den Beemt, Joos Buijs, Wil van der Aalst
Formato:	article
Lenguaje:	EN
Publicado:	Athabasca University Press 2018
Materias:	social learning analytics constructivism learning analytics learning behavior educational data mining process mining Special aspects of education LC8-6691
Acceso en línea:	https://doaj.org/article/f0d3432b34dd453db8db561f5b1e31a5
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spelling	oai:doaj.org-article:f0d3432b34dd453db8db561f5b1e31a52021-12-02T18:02:59ZAnalysing Structured Learning Behaviour in Massive Open Online Courses (MOOCs): An Approach Based on Process Mining and Clustering10.19173/irrodl.v19i5.37481492-3831https://doaj.org/article/f0d3432b34dd453db8db561f5b1e31a52018-11-01T00:00:00Zhttp://www.irrodl.org/index.php/irrodl/article/view/3748https://doaj.org/toc/1492-3831The increasing use of digital systems to support learning leads to a growth in data regarding both learning processes and related contexts. Learning Analytics offers critical insights from these data, through an innovative combination of tools and techniques. In this paper, we explore students’ activities in a MOOC from the perspective of personal constructivism, which we operationalized as a combination of learning behaviour and learning progress. This study considers students’ data analyzed as per the MOOC Process Mining: Data Science in Action. We explore the relation between learning behaviour and learning progress in MOOCs, with the purpose to gain insight into how passing and failing students distribute their activities differently along the course weeks, rather than predict students' grades from their activities. Commonly-studied aggregated counts of activities, specific course item counts, and order of activities were examined with cluster analyses, means analyses, and process mining techniques. We found four meaningful clusters of students, each representing specific behaviour ranging from only starting to fully completing the course. Process mining techniques show that successful students exhibit a more steady learning behaviour. However, this behaviour is much more related to actually watching videos than to the timing of activities. The results offer guidance for teachers. Antoine van den BeemtJoos BuijsWil van der AalstAthabasca University Pressarticlesocial learning analyticsconstructivismlearning analyticslearning behavioreducational data miningprocess miningSpecial aspects of educationLC8-6691ENInternational Review of Research in Open and Distributed Learning, Vol 19, Iss 5 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	social learning analytics constructivism learning analytics learning behavior educational data mining process mining Special aspects of education LC8-6691
spellingShingle	social learning analytics constructivism learning analytics learning behavior educational data mining process mining Special aspects of education LC8-6691 Antoine van den Beemt Joos Buijs Wil van der Aalst Analysing Structured Learning Behaviour in Massive Open Online Courses (MOOCs): An Approach Based on Process Mining and Clustering
description	The increasing use of digital systems to support learning leads to a growth in data regarding both learning processes and related contexts. Learning Analytics offers critical insights from these data, through an innovative combination of tools and techniques. In this paper, we explore students’ activities in a MOOC from the perspective of personal constructivism, which we operationalized as a combination of learning behaviour and learning progress. This study considers students’ data analyzed as per the MOOC Process Mining: Data Science in Action. We explore the relation between learning behaviour and learning progress in MOOCs, with the purpose to gain insight into how passing and failing students distribute their activities differently along the course weeks, rather than predict students' grades from their activities. Commonly-studied aggregated counts of activities, specific course item counts, and order of activities were examined with cluster analyses, means analyses, and process mining techniques. We found four meaningful clusters of students, each representing specific behaviour ranging from only starting to fully completing the course. Process mining techniques show that successful students exhibit a more steady learning behaviour. However, this behaviour is much more related to actually watching videos than to the timing of activities. The results offer guidance for teachers.
format	article
author	Antoine van den Beemt Joos Buijs Wil van der Aalst
author_facet	Antoine van den Beemt Joos Buijs Wil van der Aalst
author_sort	Antoine van den Beemt
title	Analysing Structured Learning Behaviour in Massive Open Online Courses (MOOCs): An Approach Based on Process Mining and Clustering
title_short	Analysing Structured Learning Behaviour in Massive Open Online Courses (MOOCs): An Approach Based on Process Mining and Clustering
title_full	Analysing Structured Learning Behaviour in Massive Open Online Courses (MOOCs): An Approach Based on Process Mining and Clustering
title_fullStr	Analysing Structured Learning Behaviour in Massive Open Online Courses (MOOCs): An Approach Based on Process Mining and Clustering
title_full_unstemmed	Analysing Structured Learning Behaviour in Massive Open Online Courses (MOOCs): An Approach Based on Process Mining and Clustering
title_sort	analysing structured learning behaviour in massive open online courses (moocs): an approach based on process mining and clustering
publisher	Athabasca University Press
publishDate	2018
url	https://doaj.org/article/f0d3432b34dd453db8db561f5b1e31a5
work_keys_str_mv	AT antoinevandenbeemt analysingstructuredlearningbehaviourinmassiveopenonlinecoursesmoocsanapproachbasedonprocessminingandclustering AT joosbuijs analysingstructuredlearningbehaviourinmassiveopenonlinecoursesmoocsanapproachbasedonprocessminingandclustering AT wilvanderaalst analysingstructuredlearningbehaviourinmassiveopenonlinecoursesmoocsanapproachbasedonprocessminingandclustering
_version_	1718378843810562048

Analysing Structured Learning Behaviour in Massive Open Online Courses (MOOCs): An Approach Based on Process Mining and Clustering

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