Model for discovering knowledge about academic and administrative aspects for students at driving schools in San Juan De Pasto
DOI:
https://doi.org/10.56294/dm2025842Keywords:
Educational data mining, Learning analytics, K-means, K-prototype, Driving schools, Knowledge discovery in databases (KDD)gAbstract
This paper proposes a comprehensive methodology for knowledge discovery in databases (KDD) applied
to driving schools. The usefulness of clustering algorithms such as K-means and K-prototype to identify
patterns in administrative and academic procedures was explored. During the study, three main stages were
developed: process characterization, experimental design based on machine learning, and evaluation of
the generated models. The results showed that K-prototype is particularly effective in handling mixed data,
providing key recommendations to optimize both training processes and internal management. In addition,
an application was designed to implement the model, highlighting the impact of educational data mining on
dynamic analysis and informed decision making.
References
[1] Romero, C., & Ventura, S. (2020). "Educational Data Mining: A Review of the State of the Art." IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(6), 601–618.
[2] Baker, R. S., & Inventado, P. S. (2021). "Educational Data Mining and Learning Analytics: Second Edition." Springer.
[3] Peña-Ayala, A. (2021). "Learning Analytics: Fundaments, Applications, and Trends." Springer. Este libro proporciona una visión integral de la analítica de aprendizaje, abordando fundamentos, aplicaciones y tendencias actuales en el campo.
[4] Zhang, Y., & Rangwala, H. (2023). "Deep Learning Techniques for Educational Data Mining." ACM Computing Surveys, 55(1), 1–37.
[5] Kumar, V., & Chadha, A. (2022). "An Improved K-Prototypes Clustering Algorithm for Mixed - Numerical and Categorical Data." Expert Systems with Applications, 185, 115612. Este estudio presenta mejoras al algoritmo K-Prototypes, relevante para el análisis de datos mixtos en contextos educativos.
[6] Hidalgo Cajo, B. G. (2018). "Minería de datos en los Sistemas de gestión de Aprendizaje en la Educación Universitaria." Campus Virtuales, 7(2), 115–128.
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Copyright (c) 2025 John Jairo Rivera Minayo, Javier Alejandro Jiménez Toledo, Deixy Ximena Ramos Rivadeneira, Jorge Albeiro Rivera Rosero (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
