Definición de un modelo predictivo para la deserción estudiantil en educación virtual y a distancia

University desertion is one of the most relevant and important concerns evaluated by Higher Education Institutions in Colombia. For this reason, the purpose of this document is to describe a proposed model that allows for the understanding and identification of institutional requirements regarding s...

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Autores:
Acosta Contreras, Iván Acosta
Puentes, Giovanny Alberto
Tipo de recurso:
Fecha de publicación:
2019
Institución:
Escuela Colombiana de Ingeniería Julio Garavito
Repositorio:
Repositorio Institucional ECI
Idioma:
spa
OAI Identifier:
oai:repositorio.escuelaing.edu.co:001/1054
Acceso en línea:
https://catalogo.escuelaing.edu.co/cgi-bin/koha/opac-detail.pl?biblionumber=22252
https://repositorio.escuelaing.edu.co/handle/001/1054
Palabra clave:
Deserción estudiantil- Educación Superior- Colombia
Educación Virtual
Educación a distancia
Análisis de datos- Educación Superior
Student drop-out - Higher Education- Colombia
Virtual education
Long distance education
Data Analysis - Higher Education
Rights
openAccess
License
Derechos Reservados - Escuela Colombiana de Ingeniería Julio Garavito
Description
Summary:University desertion is one of the most relevant and important concerns evaluated by Higher Education Institutions in Colombia. For this reason, the purpose of this document is to describe a proposed model that allows for the understanding and identification of institutional requirements regarding student dropout and also pathway all the changes that will be required of the institution in order to achieve the expected benefits and results. It also illustrates how, through digital technologies and data analysis methodologies, it is possible to identify more reliable levels of precision in order to predict possible students who may fall into student absenteeism and/or dropout. With this context, a practical approach of the proposed methodology has been carried out in a real-life scenario and in the company of a university in Colombia that has been a pioneer in the virtual education modality, where the strategic and operative understanding of the business areas that participate in the processes of information analysis for student dropout was carried out and together with this algorithms and techniques of data analysis were applied to the students allowing to obtain experimental results that achieved reliable levels of precision to identify predictions of student absenteeism and dropout. The final result is presented for discussion with the institution so that the university can define initiatives to reduce the dropout rate by identifying possible causes of student dropout.