EconPapers    
Economics at your fingertips  
 

Model for discovering knowledge about academic and administrative aspects for students at driving schools in San Juan De Pasto

John Jairo Rivera Minayo, Javier Alejandro Jiménez Toledo, Deixy Ximena Ramos Rivadeneira and Jorge Albeiro Rivera Rosero

Data and Metadata, 2025, vol. 4, 842

Abstract: 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.

Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:dbk:datame:v:4:y:2025:i::p:842:id:1056294dm2025842

DOI: 10.56294/dm2025842

Access Statistics for this article

More articles in Data and Metadata from AG Editor
Bibliographic data for series maintained by Javier Gonzalez-Argote ().

 
Page updated 2025-09-21
Handle: RePEc:dbk:datame:v:4:y:2025:i::p:842:id:1056294dm2025842