Educational Data Mining
Educational data mining (EDM) is the field that develops and applies data-mining and machine-learning methods to data generated by educational settings — clickstreams from online courses, intelligent tutoring system logs, assessment records, and student information systems. Its goal is to discover patterns that explain and predict learning: who is at risk of failing, how students work through material, which content sequences help, and what hidden skill structures underlie performance. EDM treats fine-grained learner data as a source of actionable scientific and practical insight.
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Fuentes
- Baker, R. S. J. d., & Yacef, K. (2009). The state of educational data mining in 2009: A review and future visions. Journal of Educational Data Mining, 1(1), 3–17. link ↗
- Romero, C., & Ventura, S. (2010). Educational data mining: A review of the state of the art. IEEE Transactions on Systems, Man, and Cybernetics, Part C, 40(6), 601–618. DOI: 10.1109/TSMCC.2010.2053532 ↗
Cómo citar esta página
ScholarGate. (2026, June 22). Educational Data Mining for Discovering Patterns in Learning Data. ScholarGate. https://scholargate.app/es/education/educational-data-mining
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- Bayesian Knowledge TracingEducation↔ comparar
- Árbol de DecisiónAprendizaje automático↔ comparar
- Agrupamiento K-MeansAprendizaje automático↔ comparar
- Learning Analytics MethodEducation↔ comparar
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