dc.creatorPicciano, Anthony G.
dc.date.accessioned2020-02-07T13:19:21Z
dc.date.accessioned2023-03-07T19:26:00Z
dc.date.available2020-02-07T13:19:21Z
dc.date.available2023-03-07T19:26:00Z
dc.date.created2020-02-07T13:19:21Z
dc.identifier1989-1660
dc.identifierhttps://reunir.unir.net/handle/123456789/9811
dc.identifierhttp://dx.doi.org/10.9781/ijimai.2014.275
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5904164
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.
dc.languageeng
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)
dc.relation;vol. 02, nº 07
dc.relationhttps://www.ijimai.org/journal/node/674
dc.rightsopenAccess
dc.subjectblended learning
dc.subjectdata-driven decision making
dc.subjectbig data
dc.subjectlearning analytics
dc.subjecthigher education
dc.subjectrational decision making
dc.subjectplanning
dc.subjectIJIMAI
dc.titleBig Data and Learning Analytics in Blended Learning Environments: Benefits and Concerns
dc.typearticle


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