摘要：Data analytics is a new field that has permeated higher education through the foray into mathematical tools, statistics, data mining, and machine learning. Initially, a theoretical foundation related to applied analytics in education, academic analytics and their approaches is presented. Subsequently, a methodology is proposed whose purpose is the referential review of the last five years regarding the field of analytics in education and especially in what concerns academic analytics, in order to identify aspects related to the growth of this approach and its fields application, focused on higher education. The results show that researchers have been concerned in recent years to work on the development of models that allow understanding aspects of the academic life of the student, teachers and institutions (academic performance, dropout rate and graduation rate in their respective order) that allow the development and making of correct decisions.
其他摘要：Data analytics is a new field that has permeated higher education through the foray into mathematical tools, statistics, data mining, and machine learning. Initially, a theoretical foundation related to applied analytics in education, academic analytics and their approaches is presented. Subsequently, a methodology is proposed whose purpose is the referential review of the last five years regarding the field of analytics in education and especially in what concerns academic analytics, in order to identify aspects related to the growth of this approach and its fields application, focused on higher education. The results show that researchers have been concerned in recent years to work on the development of models that allow understanding aspects of the academic life of the student, teachers and institutions (academic performance, dropout rate and graduation rate in their respective order) that allow the development and making of correct decisions.
关键词：Analítica;analítica académica;aprendizaje automático;educación en ingeniería
