Modelo de aprendizaje automático para la predicción del abandono escolar mediante encuestas de hogares
The persistent issue of student dropout negatively impacts the educational sector and society at large. This study presents a machine learning model that leverages data from the National Household Survey to predict student dropout in Peru, integrating a wide range of socio-demographic variables. The...
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | Artículo |
| Lenguaje: | español |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | Enlace permanente (DOI o Handle) Descargar el archivo Ver en el sistema de origen |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1881700528877993984 |
|---|---|
| author | Johnny P. Jacha Rojas Walter Yataco Cañari Johann Alexis Ospina Galindez |
| author_browse | Johann Alexis Ospina Galindez Johnny P. Jacha Rojas Walter Yataco Cañari |
| author_facet | Johnny P. Jacha Rojas Walter Yataco Cañari Johann Alexis Ospina Galindez |
| author_sort | Johnny P. Jacha Rojas |
| collection | Producción científica |
| description | The persistent issue of student dropout negatively impacts the educational sector and society at large. This study presents a machine learning model that leverages data from the National Household Survey to predict student dropout in Peru, integrating a wide range of socio-demographic variables. The research fills a gap in existing literature by providing a model that incorporates socio-demographic variables, an area not fully explored in previous studies. The predictive model aims to identify factors associated with student dropout, aiding educational stakeholders in implementing effective interventions. The findings underscore the model's potential to enhance educational outcomes by enabling early identification of at-risk students, thereby facilitating targeted support. This work contributes to refining predictive models of university dropout rates and sug- gests the use of ensemble methods to improve the accu- racy of single-model predictions. Future research could further explore computational methodologies like deep learning and hybrid models to predict dropout rates and their comparison with this study's outcomes, considering additional influential factors not covered in this research. |
| format | Article |
| id | openalex:W7220706030 |
| institution | UPeU |
| language | Spanish |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| record_format | dspace |
| spelling | openalex:W7220706030Modelo de aprendizaje automático para la predicción del abandono escolar mediante encuestas de hogaresJohnny P. Jacha RojasWalter Yataco CañariJohann Alexis Ospina Galindezstudent dropout predictionschool dropoutsocio-demographic variableshousehold survey dataat-risk studentsuniversity dropoutensemble methodseducational interventionPeruOnline Learning and AnalyticsEvasion and Academic Success FactorsEducational Outcomes and InfluencesThe persistent issue of student dropout negatively impacts the educational sector and society at large. This study presents a machine learning model that leverages data from the National Household Survey to predict student dropout in Peru, integrating a wide range of socio-demographic variables. The research fills a gap in existing literature by providing a model that incorporates socio-demographic variables, an area not fully explored in previous studies. The predictive model aims to identify factors associated with student dropout, aiding educational stakeholders in implementing effective interventions. The findings underscore the model's potential to enhance educational outcomes by enabling early identification of at-risk students, thereby facilitating targeted support. This work contributes to refining predictive models of university dropout rates and sug- gests the use of ensemble methods to improve the accu- racy of single-model predictions. Future research could further explore computational methodologies like deep learning and hybrid models to predict dropout rates and their comparison with this study's outcomes, considering additional influential factors not covered in this research.Articlehttps://doi.org/10.46276/rifce.v10i2.2308https://revistas.unheval.edu.pe/rifce/article/download/2308/2031https://revistas.unheval.edu.pe/index.php/rifce/article/view/2308W7220706030esRevista Identidad2306-40722707-54192024-11-30 |
| spellingShingle | student dropout prediction school dropout socio-demographic variables household survey data at-risk students university dropout ensemble methods educational intervention Peru Online Learning and Analytics Evasion and Academic Success Factors Educational Outcomes and Influences Johnny P. Jacha Rojas Walter Yataco Cañari Johann Alexis Ospina Galindez Modelo de aprendizaje automático para la predicción del abandono escolar mediante encuestas de hogares |
| title | Modelo de aprendizaje automático para la predicción del abandono escolar mediante encuestas de hogares |
| title_full | Modelo de aprendizaje automático para la predicción del abandono escolar mediante encuestas de hogares |
| title_fullStr | Modelo de aprendizaje automático para la predicción del abandono escolar mediante encuestas de hogares |
| title_full_unstemmed | Modelo de aprendizaje automático para la predicción del abandono escolar mediante encuestas de hogares |
| title_short | Modelo de aprendizaje automático para la predicción del abandono escolar mediante encuestas de hogares |
| title_sort | modelo de aprendizaje automatico para la prediccion del abandono escolar mediante encuestas de hogares |
| topic | student dropout prediction school dropout socio-demographic variables household survey data at-risk students university dropout ensemble methods educational intervention Peru Online Learning and Analytics Evasion and Academic Success Factors Educational Outcomes and Influences |
| topic_facet | student dropout prediction school dropout socio-demographic variables household survey data at-risk students university dropout ensemble methods educational intervention Peru Online Learning and Analytics Evasion and Academic Success Factors Educational Outcomes and Influences |
| url | https://doi.org/10.46276/rifce.v10i2.2308 https://revistas.unheval.edu.pe/rifce/article/download/2308/2031 https://revistas.unheval.edu.pe/index.php/rifce/article/view/2308 |
| work_keys_str_mv | AT johnnypjacharojas modelodeaprendizajeautomaticoparalapredicciondelabandonoescolarmedianteencuestasdehogares AT walteryatacocanari modelodeaprendizajeautomaticoparalapredicciondelabandonoescolarmedianteencuestasdehogares AT johannalexisospinagalindez modelodeaprendizajeautomaticoparalapredicciondelabandonoescolarmedianteencuestasdehogares |