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Educational Data Mining: A Review of the State of the Art
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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“This personalized approach helps optimize learning outcomes by focusing on areas where learners need more support and practice [87].”
From Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review (2023) · cites this paper as [87]
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Metadata
- Authors
- Romero, C., & Ventura, S.
- Affiliations
- University of Córdoba (ES)
- Venue
- IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)
- Published
- 2010-11
- Volume
- 40
- Issue
- 6
- Pages
- 601-618
- ISSN
- 1094-6977 (ISSN-L)
- 1558-2442
- 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
- 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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