Aprendizaje basado en juegos para la enseñanza de la probabilidad en la Administración pública
Bibliographic Data
| ID | 21436277 |
|---|---|
| Authors | Gabriel Villalobos Camargo (0000-0003-4582-265X, Escuela Superior de Administración Pública), Carlos Andrés Barco Rojas (0000-0002-6571-0172, Escuela Superior de Administración Pública), David Julián Molina Beltrán (0000-0003-0478-5311, Escuela Superior de Administración Pública) |
| Year | 2025 |
| Volume | 55 |
| Issue | 1 |
| Pages | e1110 |
| Publication date | 2025-06-20 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Administración & Desarrollo (JOURNAL) |
| Journal identifiers | ISSN: 0120-3754 • E-ISSN: 2500-5227 |
| Publisher | Escuela Superior de Administracion Publica (PUBLISHER) |
| DOI | 10.22431/25005227.1110 |
| OpenAlex | W4412202041 |
| Language | ES |
| References cited | 45 |
This reflection paper examines how Game-Based Learning can enhance the teaching of statistics in public administration, focusing specifically on the use of serious and simulation games as pedagogical tools. Board games can be used as an alternative pedagogical practice based on the holistic teaching style, which promotes learning motivation in the classroom. The methodology used for planning follows a five-stage process for the development of serious games: definition, conceptualization, formalization, production, presentation and evaluation. Additionally, this study presents the construction of a serious game whose pedagogical purpose is to identify the characteristics that differentiate discrete probability distributions. It is emphasized that Game-Based Learning should not replace traditional methods but complement them. Also, the evaluation through concept inventories provides a clear feedback of the pedagogical process, proposing an example of how it can be applied in the context of public administration. Finally, this methodology has the potential to significantly improve the training of future public administrators, especially in the understanding of discrete probability distributions
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| Highly cited | No |
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