Scalable Early Warning Systems for School Dropout prevention: Evidence from a 4.000-School Randomized Controlled Trial

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Across many low- and middle-income countries, a sizable share of young people drop out of school before completing a full course of basic education. Early warning systems that accurately identify students at risk of dropout and support them with targeted interventions have shown results and are in w...

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Detalles Bibliográficos
Autores principales: Vazquez, Emmanuel José, Haimovich, Francisco, Adelman, Melissa
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2021
Materias:
Ciencias Económicas
Dropout prevention
Early Warning
Impact Evaluation
School Management
Guatemala
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/170146
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-170146
record_format dspace
spelling I19-R120-10915-1701462024-09-14T04:08:09Z http://sedici.unlp.edu.ar/handle/10915/170146 Scalable Early Warning Systems for School Dropout prevention: Evidence from a 4.000-School Randomized Controlled Trial Vazquez, Emmanuel José Haimovich, Francisco Adelman, Melissa 2021-11 2021 2024-09-13T15:21:27Z en Ciencias Económicas Dropout prevention Early Warning Impact Evaluation School Management Guatemala Across many low- and middle-income countries, a sizable share of young people drop out of school before completing a full course of basic education. Early warning systems that accurately identify students at risk of dropout and support them with targeted interventions have shown results and are in widespread use in high-income contexts. This paper presents impact evaluation results from an early warning system pilot program in Guatemala, a middle-income country where nearly 40 percent of sixth graders drop out before completing ninth grade. The pilot program, which was implemented in 17 percent of Guatemala’s primary schools and largely leveraging existing government resources, reduced the dropout rate in the transition from primary to lower secondary school by 4 percent (1.3 percentage points) among schools assigned to the program, and by 9 percent (3 percentage points) among program compliers. Although the effect size is relatively modest, the low cost of the program (estimated at less than US$3 per student) and successful implementation at scale make this a promising and cost-effective approach for reducing dropout in resource-constrained contexts like Guatemala. AEA RCT ID: AEARCTR-0004091. Facultad de Ciencias Económicas Objeto de conferencia Objeto de conferencia http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Económicas
Dropout prevention
Early Warning
Impact Evaluation
School Management
Guatemala
spellingShingle Ciencias Económicas
Dropout prevention
Early Warning
Impact Evaluation
School Management
Guatemala
Vazquez, Emmanuel José
Haimovich, Francisco
Adelman, Melissa
Scalable Early Warning Systems for School Dropout prevention: Evidence from a 4.000-School Randomized Controlled Trial
topic_facet Ciencias Económicas
Dropout prevention
Early Warning
Impact Evaluation
School Management
Guatemala
description Across many low- and middle-income countries, a sizable share of young people drop out of school before completing a full course of basic education. Early warning systems that accurately identify students at risk of dropout and support them with targeted interventions have shown results and are in widespread use in high-income contexts. This paper presents impact evaluation results from an early warning system pilot program in Guatemala, a middle-income country where nearly 40 percent of sixth graders drop out before completing ninth grade. The pilot program, which was implemented in 17 percent of Guatemala’s primary schools and largely leveraging existing government resources, reduced the dropout rate in the transition from primary to lower secondary school by 4 percent (1.3 percentage points) among schools assigned to the program, and by 9 percent (3 percentage points) among program compliers. Although the effect size is relatively modest, the low cost of the program (estimated at less than US$3 per student) and successful implementation at scale make this a promising and cost-effective approach for reducing dropout in resource-constrained contexts like Guatemala. AEA RCT ID: AEARCTR-0004091.
format Objeto de conferencia
Objeto de conferencia
author Vazquez, Emmanuel José
Haimovich, Francisco
Adelman, Melissa
author_facet Vazquez, Emmanuel José
Haimovich, Francisco
Adelman, Melissa
author_sort Vazquez, Emmanuel José
title Scalable Early Warning Systems for School Dropout prevention: Evidence from a 4.000-School Randomized Controlled Trial
title_short Scalable Early Warning Systems for School Dropout prevention: Evidence from a 4.000-School Randomized Controlled Trial
title_full Scalable Early Warning Systems for School Dropout prevention: Evidence from a 4.000-School Randomized Controlled Trial
title_fullStr Scalable Early Warning Systems for School Dropout prevention: Evidence from a 4.000-School Randomized Controlled Trial
title_full_unstemmed Scalable Early Warning Systems for School Dropout prevention: Evidence from a 4.000-School Randomized Controlled Trial
title_sort scalable early warning systems for school dropout prevention: evidence from a 4.000-school randomized controlled trial
publishDate 2021
url http://sedici.unlp.edu.ar/handle/10915/170146
work_keys_str_mv AT vazquezemmanueljose scalableearlywarningsystemsforschooldropoutpreventionevidencefroma4000schoolrandomizedcontrolledtrial
AT haimovichfrancisco scalableearlywarningsystemsforschooldropoutpreventionevidencefroma4000schoolrandomizedcontrolledtrial
AT adelmanmelissa scalableearlywarningsystemsforschooldropoutpreventionevidencefroma4000schoolrandomizedcontrolledtrial
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