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dc.contributor.authorPicciano, Anthony G.
dc.date2014-09
dc.date.accessioned2020-02-07T13:19:21Z
dc.date.available2020-02-07T13:19:21Z
dc.identifier.issn1989-1660
dc.identifier.urihttps://reunir.unir.net/handle/123456789/9811
dc.description.abstractThe purpose of this article is to examine big data and learning analytics in blended learning environments. It will examine the nature of these concepts, provide basic definitions, and identify the benefits and concerns that apply to their development and implementation. This article draws on concepts associated with data-driven decision making, which evolved in the 1980s and 1990s, and takes a sober look at big data and analytics. It does not present them as panaceas for all of the issues and decisions faced by higher education administrators, but sees them as part of solutions, although not without significant investments of time and money to achieve worthwhile benefits.es_ES
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;vol. 02, nº 07
dc.relation.urihttps://www.ijimai.org/journal/node/674es_ES
dc.rightsopenAccesses_ES
dc.subjectblended learninges_ES
dc.subjectdata-driven decision makinges_ES
dc.subjectbig dataes_ES
dc.subjectlearning analyticses_ES
dc.subjecthigher educationes_ES
dc.subjectrational decision makinges_ES
dc.subjectplanninges_ES
dc.subjectIJIMAIes_ES
dc.titleBig Data and Learning Analytics in Blended Learning Environments: Benefits and Concernses_ES
dc.typearticlees_ES
reunir.tag~IJIMAIes_ES
dc.identifier.doihttp://dx.doi.org/10.9781/ijimai.2014.275


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