Rafael Isaac Estrada-Danell, Roman Alberto Zamarripa-Franco, Pilar Giselle Zúñiga-Garay, Isaías Martínez-Trejo
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引用次数: 6
Abstract
This article aims to analyze how data mining (DM) optimizes the enrollment process, with the intention of designing a predictive model to manage private enrollment for higher education institutions of Mexico. It analyzes the current status of the higher education institutions in relation to its enrollment process and the application of the DM. With a correlational method, a dataset (DS) was used to model an entropy decision tree with the help of Rapid Miner software. The results show that it is possible to build and test a predictive model management of private enrollment for higher education institutions of Mexico as the ZAM&EST model proposed by the authors.
期刊介绍:
Educare Electronic Journal is edited and published by the Center for Research and Teaching in Education (Centro de Investigación y Docencia en Educación) from the Universidad Nacional (National University, Costa Rica). It is an international, quarterly, academic publication. Educare’s aim is to disseminate academic production in the area of Education, both nationally and internationally, allowing authors to communicate their findings, and readers, the possibility to discover the extensive work related to the discipline and its impact and relationship with other fields of knowledge. In search of the construction of interdisciplinary pedagogical thought, the Journal seeks academic reflection; the discussion and analysis of the published knowledge; the incorporation of new perspectives; the reference to innovation and the presentation of successful methodological applications. Aware of the wide range of expressions in this discipline, from theoretical conceptualizations to practical exercises, Educare offers a space for exchange, dissemination and promotion of Education.