Approximation of Statistical Implicative Analysis to Learning Analytics: A systematic review

Fecha: 
02/11/2017
Fecha de finalización: 
04/11/2017

Learning Analytics was and continues to be an emerging technology, the amount of research papers in learning analytics are increasing every day. The integration of new tools, methods and theories is necessary. The aim of this paper is to study the approximation of Statistical Implicative Analysis theory (SIA) to Learning Analytics (LA). For this purpose, we created an approximation framework based in definition, data source, stages, types and methods used in LA. We used systematic review in the literature published in the last 66 months in electronic databases ACM, EBSCO, Google Scholar, IEEE, ProQuest, Scopus and WOS. We started with 319 papers of which 111 were in the educational area and finally 24 met all the criteria quality. This paper provides the topics whereby SIA approximates to LA, and identifies a series of future researches.

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