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Accounting for repetition and dropout in contemporaneous cross-section learning profiles

Evidence from Rwanda

Bibliographic Data

ID12071741
AuthorsLee Crawfurd (0000-0003-1513-934X, corresponding author)
Year2021
Volume85
Pages102443-102443
Publication date2021-06-10
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Educational Development (JOURNAL)
Journal identifiersISSN: 0738-0593 • E-ISSN: 1873-4871
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.ijedudev.2021.102443
PMID34483466
OpenAlexW3168598884
LanguageEN
Citations received5
References cited19

How much do children learn in a year of school? Longitudinal data that tracks children over time is scarce in developing countries, and so recent studies estimate learning profiles by comparing the ability of people with different amounts of schooling, at a single point in time. Such estimates of the effect of schooling on learning may be biased upwards by not controlling for repetition and dropout. In this paper I estimate contemporaneous cross-section learning profiles for Rwanda, using data from a nationally representative survey of 3053 children aged six to eighteen. I show how adjusting this learning profile for the total number of years enrolled in school (accounting for repetition and dropout), using detailed schooling histories, reduces the average amount learnt per year by over 60 percent. The learning profile for Rwanda is not just too flat, but flatter than previous estimates suggest

Dropout (neural networks · Geography · Machine learning · Point (geometry · Repetition (rhetorical device · Section (typography · Child Nutrition and Water Access · Computer Science · Mathematics · Poverty, Education, and Child Welfare · Psychology · School Choice and Performance

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Unique citing works5
Citations per year1
Citation span2021 - 2026 (6)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 5

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