Education system institutions and educational inequalities in Uruguay

Bogliaccini, Juan Ariel; Rodríguez, Federico

doi:10.18356/7ff65165-en

Cited by 2 publications

(3 citation statements)

References 23 publications

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“…One of the sources of quality differences within the public system is the mechanism of allocating teachers to schools: the administration makes an ordered list of teachers based on their curriculum and the best teachers get first choice in their school of preference. Bogliaccini and Rodríguez (2015) find that in both primary and secondary education, more experienced teachers are concentrated in advantaged socio-economic areas. In a study of primary level education, Luschei and Carnoy (2010) reinforce the importance of this finding, concluding that teacher experience is strongly related to student outcomes.…”

Section: Effect Of In-kind Transfersmentioning

confidence: 85%

“…This affects populations with fewer economic resources, although students may choose the school. However, the opportunities for choice are limited: Bogliaccini and Rodríguez (2015) indicate that most of the students attend an establishment near their home because of transportation costs.…”

Section: Effect Of In-kind Transfersmentioning

confidence: 99%

“…A share of these inputs is funded by associations of students' parents, which has a direct effect on these resources. In addition, Bogliaccini and Rodríguez (2015) argue that management abilities of school principals are better in high than in low socio-economic areas, a fact which allows them to capture more resources from the central administration.…”

Section: Effect Of In-kind Transfersmentioning

confidence: 99%

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Inequality and fiscal policies in Uruguay by race

2018

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The aim of this study is to analyze the effect of fiscal policy by race, disaggregating to consider Uruguayans with primarily European, African and indigenous ancestry. We perform an incidence analysis, an estimation of the effect of fiscal policy on the poverty exit rate and an assessment of the impact on the average ethno-racial gaps. The findings support the idea that fiscal policy reduces (but does not eliminate) ethnic gaps. This result is led by health care and educational transfers, and to a lesser degree by direct transfers. We do not consider quality issues with public services, which may affect the estimated narrowing of gaps. Finally, we find that Afro-descendants and indigenous individuals do not capture the full potential of education transfers because of their high drop-out rate.

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Section: Effect Of In-kind Transfersmentioning

confidence: 85%

Section: Effect Of In-kind Transfersmentioning

confidence: 99%

Section: Effect Of In-kind Transfersmentioning

confidence: 99%

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Inequality and fiscal policies in Uruguay by race

2018

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Early Prediction of At-Risk Students in Secondary Education: A Countrywide K-12 Learning Analytics Initiative in Uruguay

et al. 2022

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This paper describes a nationwide learning analytics initiative in Uruguay focused on the future implementation of governmental policies to mitigate student retention and dropouts in secondary education. For this, data from a total of 258,440 students were used to generate automated models to predict students at risk of failure or dropping out. Data were collected from primary and secondary education from different sources and for the period between 2015 and 2020. Such data contains demographic information about the students and their trajectories from the first grade of primary school to the second grade of secondary school (e.g., student assessments in different subjects over the years, the amount of absences, participation in social welfare programs, and the zone of the school, among other factors). Predictive models using the random forest algorithm were trained, and their performances were evaluated with F1-Macro and AUROC measures. The models were planned to be applied in different periods of the school year for the regular secondary school and for the technical secondary school ((before the beginning of the school year and after the first evaluation meeting for each grade). A total of eight predictive models were developed considering this temporal approach, and after an analysis of bias considering three protected attributes (gender, school zone, and social welfare program participation), seven of them were approved to be used for prediction. The models achieved outstanding performances according to the literature, with an AUROC higher than 0.90 and F1-Macro higher than 0.88. This paper describes in depth the characteristics of the data gathered, the specifics of data preprocessing, and the methodology followed for model generation and bias analysis, together with the architecture developed for the deployment of the predictive models. Among other findings, the results of the paper corroborate the importance given in the literature of using the previous performances of the students in order to predict their future performances.

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Education system institutions and educational inequalities in Uruguay

Cited by 2 publications

References 23 publications

Inequality and fiscal policies in Uruguay by race

Inequality and fiscal policies in Uruguay by race

Early Prediction of At-Risk Students in Secondary Education: A Countrywide K-12 Learning Analytics Initiative in Uruguay

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