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Cited by 2,251Online Learning and AnalyticsIntelligent Tutoring Systems and Adaptive LearningEducational Technology and Pedagogy

The DOI matches its Crossref record; 271 of the 279 references it cites were found in a registry or an index.

Educational Data Mining: A Review of the State of the Art

Romero, Cristóbal, Ventura, Sebastián·2010·IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)
DOI 10.1109/tsmcc.2010.2053532
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Abstract

Educational data mining (EDM) is an emerging interdisciplinary research area that deals with the development of methods to explore data originating in an educational context. EDM uses computational approaches to analyze educational data in order to study educational questions. This paper surveys the most relevant studies carried out in this field to date. First, it introduces EDM and describes the different groups of user, types of educational environments, and the data they provide. It then goes on to list the most typical/common tasks in the educational environment that have been resolved through data-mining techniques, and finally, some of the most promising future lines of research are discussed.

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8 of the 279 references couldn’t be matched to a known paper.

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Metadata

Authors
Romero, C., & Ventura, S.
Affiliations
University of Córdoba (ES)
ORCID
Venue
IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2010-11
Volume
40
Issue
6
Pages
601-618
ISSN
  • 1094-6977 (ISSN-L)
  • 1558-2442
DOI
10.1109/tsmcc.2010.2053532
OpenAlex
W2006444123
Cited by
2,251
References
279
Citations by year
2026: 204 · 2025: 141 · 2024: 117 · 2023: 118 · 2022: 142 · 2021: 144 · 2020: 204 · 2019: 196 · 2018: 185 · 2017: 167 · 2016: 155 · 2015: 145 · 2014: 140 · 2013: 90 · 2012: 70
FWCI
147.61
Type
journal article
Language
en
Open access
closed
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations
IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Social Sciences › Education › Educational Technology and Pedagogy
Keywords
educational data mining, educational data analysis, learning analytics, educational environment, future research directions

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