Prevention and Mitigation of Rural Higher Education Dropout in Colombia: A Dynamic Performance Management Approach

Background: Dropout in higher education is a socio-educational phenomenon that has the scope to limit the benefits of education as well as to widen social disparities. For this reason, governments have implemented various public policies for its prevention and mitigation. However, in rural populatio...

Full description

Autores:
Tipo de recurso:
Article of journal
Fecha de publicación:
2024
Institución:
Universidad de Bogotá Jorge Tadeo Lozano
Repositorio:
Expeditio: repositorio UTadeo
Idioma:
OAI Identifier:
oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/34684
Acceso en línea:
https://f1000research.com/articles/12-497
https://f1000research.com/articles/12-497/v2/pdf?article_uuid=4020293a-6e88-40d4-822f-10492d64d178
http://hdl.handle.net/20.500.12010/34684
Palabra clave:
Simulation models
Higher education
Rural areas
Dynamic Performance Management
Dropping out
Rights
License
Abierto (Texto Completo)
Description
Summary:Background: Dropout in higher education is a socio-educational phenomenon that has the scope to limit the benefits of education as well as to widen social disparities. For this reason, governments have implemented various public policies for its prevention and mitigation. However, in rural populations, such policies have proven to be ineffective. The aim of this paper is to simulate public policy scenarios for the treatment of school dropout in rural higher education in Colombia from a Dynamic Performance Management approach. Methodology: To achieve the aim, a parameterised simulation model was designed with data from Colombian state entities in rural higher education. Five simulations were carried out. The analysis of the results was carried out using descriptive statistics and comparison of means using the Wilcoxon Sign Rank statistic. Results: The adoption of such an approach based on simulations suggests that policies to expand the coverage of educational credits and financial support, as well as the addition of a family income subsidy, allow for a reduction in the number of dropouts. Conclusions: A dynamic, data-driven approach can be effective in preventing and mitigating dropout in these areas. It also highlights the importance of identifying the key factors contributing to dropout. The results also suggest that government policies can have a significant impact on school retention in rural areas.