Failures in school progression
The objectives of this paper are two-fold. Firstly, to analyse the state of the education system in Argentina, combining data from different sources, as each of them have their own strengths and weaknesses. For instance, school census data have the advantage of being direct reports from state educat...
Guardado en:
| Autor principal: | |
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| Formato: | Articulo Documento de trabajo |
| Lenguaje: | Inglés |
| Publicado: |
2007
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/3609 http://cedlas.econo.unlp.edu.ar/download.php?file=archivos_upload/doc_cedlas50.pdf |
| Aporte de: |
| id |
I19-R120-10915-3609 |
|---|---|
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dspace |
| institution |
Universidad Nacional de La Plata |
| institution_str |
I-19 |
| repository_str |
R-120 |
| collection |
SEDICI (UNLP) |
| language |
Inglés |
| topic |
Economía rendimiento de la educación educación |
| spellingShingle |
Economía rendimiento de la educación educación Giovagnoli, Paula Inés Failures in school progression |
| topic_facet |
Economía rendimiento de la educación educación |
| description |
The objectives of this paper are two-fold. Firstly, to analyse the state of the education system in Argentina, combining data from different sources, as each of them have their own strengths and weaknesses. For instance, school census data have the advantage of being direct reports from state education agencies but do not provide wide socio-economic information on students, and do not give an estimation of how many people are out of the system. Using the population Census data it is possible to fill in the gap, as non-attendance rates by age and gender are easily calculated. This information, however, is available every 10 years. There are also many contextual variables (such as household income) that are not collected during the interviews. Using the household survey it is possible to get that information on a current basis. Although it covers only main urban areas, it is a good approximation to the urban census data. With these data, it was also possible to construct a measure to identify children who are below the modal grade for their age. Secondly, to closely explore the interrelations between quantitative educational outcomes and individual characteristics as well as school factors, exploiting the EEJ database. The research intends to uncover correlations among variables and in this sense, it is purely a descriptive paper to highlight associations rather than causal relations. The next section will provide the readers with the general context of the education sector, and its origins. Section II.B describes the main stylised facts observed during recent decades using data from different sources, with special focus on identifying risk schooling zones for teenagers. Section III explores the new data set that allows us to characterise dissimilar paths in youth education. The second part of this section will present a multivariate analysis to identify the groups that are most likely to having access secondary school and complete it. Findings are discussed by constructing different student profiles. The last section summarises the findings. |
| format |
Articulo Documento de trabajo |
| author |
Giovagnoli, Paula Inés |
| author_facet |
Giovagnoli, Paula Inés |
| author_sort |
Giovagnoli, Paula Inés |
| title |
Failures in school progression |
| title_short |
Failures in school progression |
| title_full |
Failures in school progression |
| title_fullStr |
Failures in school progression |
| title_full_unstemmed |
Failures in school progression |
| title_sort |
failures in school progression |
| publishDate |
2007 |
| url |
http://sedici.unlp.edu.ar/handle/10915/3609 http://cedlas.econo.unlp.edu.ar/download.php?file=archivos_upload/doc_cedlas50.pdf |
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AT giovagnolipaulaines failuresinschoolprogression |
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Repositorios |
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1764820472404377600 |