Educational data mining and learning analytics: An updated survey

This survey is an updated and improved version of the previous one published in 2013 in this journal with the title “data mining in education”. It reviews in a comprehensible and very general way how Educational Data Mining and Learning Analytics have been applied over educational data. In the last...

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Veröffentlicht in:Wiley interdisciplinary reviews. Data mining and knowledge discovery Jg. 10; H. 3; S. e1355 - n/a
Hauptverfasser: Romero, Cristobal, Ventura, Sebastian
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Hoboken, USA Wiley Periodicals, Inc 01.05.2020
Wiley Subscription Services, Inc
Schlagworte:
Big Data in Education
Cultural organizations
Data analysis
Data mining
Data Mining on Education
Data science
Data‐Driven Decision‐Making in Education
Decision analysis
Education
Educational Data Mining
Educational Data Science
Learning
Mathematical analysis
State-of-the-art reviews
ISSN:1942-4787, 1942-4795
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:This survey is an updated and improved version of the previous one published in 2013 in this journal with the title “data mining in education”. It reviews in a comprehensible and very general way how Educational Data Mining and Learning Analytics have been applied over educational data. In the last decade, this research area has evolved enormously and a wide range of related terms are now used in the bibliography such as Academic Analytics, Institutional Analytics, Teaching Analytics, Data‐Driven Education, Data‐Driven Decision‐Making in Education, Big Data in Education, and Educational Data Science. This paper provides the current state of the art by reviewing the main publications, the key milestones, the knowledge discovery cycle, the main educational environments, the specific tools, the free available datasets, the most used methods, the main objectives, and the future trends in this research area. This article is categorized under: Application Areas > Education and Learning Educational Data Mining and Learning Analytics.
Bibliographie:Funding information
Ministerio de Ciencia e Innovación, Grant/Award Number: TIN2017‐83445‐P
ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1942-4787
1942-4795
DOI:10.1002/widm.1355