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Vol. 14 No. 2 (2024)
Julio-Diciembre

Articles

Time series model for the characterization and prediction of the graduation rate at the University of Cartagena

https://doi.org/10.19053/uptc.20278306.v14.n2.2024.17921

Published 2024-07-15

  • Ana María Prieto-Romero
    • ,
  • Gabriel Elías Chanchí-Golondrino
    • ,
  • Manuel Alejandro Ospina-Alarcón

Ana María Prieto-Romero
University of Cartagena, Cartagena, Colombia image/svg+xml

Gabriel Elías Chanchí-Golondrino
University of Cartagena, Cartagena, Colombia image/svg+xml

Manuel Alejandro Ospina-Alarcón
University of Cartagena, Cartagena, Colombia image/svg+xml

Abstract

For universities, characterizing graduation rates is a key indicator reflecting academic quality and the institution's ability to guide students towards successful entry into the workforce. This paper proposes a time series model for characterizing and predicting graduation rates at the University of Cartagena. Methodologically, the CRISP-DM methodology was adapted into four phases: P1. Business and data understanding, P2. Data preparation, P3. Model construction and evaluation, and P4. Deployment. As a result, various ARIMA models were implemented and evaluated to determine the best fitting model. This model serves as a reference for developing tools to support decision-making by university administrators regarding the number of graduating professionals, in line with educational quality standards.

Keywords

Graduates, graduation rate, predictive model, time series, ARIMA

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Author Biography

Ana María Prieto-Romero

Ingeniera de Sistemas

Gabriel Elías Chanchí-Golondrino

Ingeniero en Electrónica y Telecomunicaciones , Doctor en Ingeniería Telemática.

Manuel Alejandro Ospina-Alarcón

Ingeniero de Control, Doctor en Ingeniería - Ciencia y Tecnología de Materiales.

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