ADHE: A Tool to Characterize Higher Education Dropout Phenomenon

Abstract

The field of academic analytics emerged in higher education institutions (HEI) because of developments in database technologies and the generalization of data-mining practices and business intelligence tools. We have designed and implemented a dashboard called ADHE (Academic Analytical Dashboard in Higher Education) for a Colombian higher education institution. The purpose of ADHE is to help administrators of academic programs in their decision-making process regarding the analysis of the phenomenon of student dropout. We used the pipeline methodology for processing large volumes of data was used, which is based on five phases: data acquisition, integration, cleaning, transformation, and visualization. All phases were carried out in the R programming language using academic information sources from the Faculty of Engineering of the Universidad de Antioquia and the Colombian Institute for the Evaluation of Education. The dashboard ADHE is open for free and can be consulted at:  https://fhernanb.shinyapps.io/AppPermanencia/. The main findings were that social stratum, gender, and type of high school are associated with the student dropout phenomenon. Furthermore, in social stratum 1, male students and public high schools tend to have a higher student dropout proportion. Additionally, we conclude that admission to engineering programs requires a balance of qualitative and quantitative abilities. The dashboard ADHE should be used to help students, parents, teachers, and administrators understand student dropout dynamics.