Educational data mining: a 10-year review

dc.contributor.authorKalita, Emi
dc.contributor.authorOyelere, Solomon Sunday
dc.contributor.authorGaftandzhieva, Silvia
dc.contributor.authorRajesh, Kandala N. V. P. S.
dc.contributor.authorJagatheesaperumal, Senthil Kumar
dc.contributor.authorMohamed, Asmaa
dc.contributor.authorElbarawy, Yomna M.
dc.date.accessioned2025-07-03T21:26:52Z
dc.date.issued2025
dc.departmentBalıkesir Üniversitesi
dc.description.abstractThis systematic review comprehensively examines the application and impacts of Educational Data Mining (EDM) over the past decade. It explores the use of various data mining tools and techniques, statistics, and machine learning algorithms in education. The review discusses how EDM helps understand and improve the learning experience, educational strategies, and institutional efficiency. It highlights the iterative process of EDM, its applications, and the benefits it offers to different stakeholders, including students, teachers, and educational institutions. The paper also discusses the challenges related to data ethics, privacy, and security in EDM. Key sections include a methodology for conducting the systematic review, exploring different data mining techniques and learning styles, and using Artificial Intelligence in EDM. The review concludes with a discussion of findings, future research directions, and a summary of the study's contributions and limitations.
dc.description.sponsorshipLulea University of Technology
dc.description.sponsorshipThe authors are thankful to all the individuals who helped directly or indirectly to complete this study. For open access, the author has applied a 'Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version.
dc.identifier.doi10.1007/s10791-025-09589-z
dc.identifier.issn2948-2984
dc.identifier.issn2948-2992
dc.identifier.issue1
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1007/s10791-025-09589-z
dc.identifier.urihttps://hdl.handle.net/20.500.12462/21909
dc.identifier.volume28
dc.identifier.wosWOS:001490873500003
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofDiscover Computing
dc.relation.publicationcategoryDiğer
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250703
dc.subjectEducation data mining
dc.subjectMultimodal learning analytics
dc.subjectArtificial intelligence in education
dc.subjectExplainability in education
dc.titleEducational data mining: a 10-year review
dc.typeReview Article

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