Mostrar el registro sencillo del ítem

dc.contributor.authorMartínez Navarro, Álvaro
dc.contributor.authorMoreno-Ger, Pablo
dc.date2018-09
dc.date.accessioned2022-01-27T09:45:52Z
dc.date.available2022-01-27T09:45:52Z
dc.identifier.issn1989-1660
dc.identifier.urihttps://reunir.unir.net/handle/123456789/12370
dc.description.abstractLearning Analytics is becoming a key tool for the analysis and improvement of digital education processes, and its potential benefit grows with the size of the student cohorts generating data. In the context of Open Education, the potentially massive student cohorts and the global audience represent a great opportunity for significant analyses and breakthroughs in the field of learning analytics. However, these potentially huge datasets require proper analysis techniques, and different algorithms, tools and approaches may perform better in this specific context. In this work, we compare different clustering algorithms using an educational dataset. We start by identifying the most relevant algorithms in Learning Analytics and benchmark them to determine, according to internal validation and stability measurements, which algorithms perform better. We analyzed seven algorithms, and determined that K-means and PAM were the best performers among partition algorithms, and DIANA was the best performer among hierarchical algorithms.es_ES
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;vol. 5, nº 2
dc.relation.urihttps://ijimai.org/journal/bibcite/reference/2653es_ES
dc.rightsopenAccesses_ES
dc.subjectclusteringes_ES
dc.subjectcomputer languageses_ES
dc.subjectdata analysises_ES
dc.subjectengineering studentses_ES
dc.subjectperformance evaluationes_ES
dc.subjectunsupervised learninges_ES
dc.subjectIJIMAIes_ES
dc.titleComparison of Clustering Algorithms for Learning Analytics with Educational Datasetses_ES
dc.typearticlees_ES
reunir.tag~IJIMAIes_ES
dc.identifier.doihttp://doi.org/10.9781/ijimai.2018.02.003


Ficheros en el ítem

Thumbnail

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem