Learning loss due to school closures during the COVID-19 pandemic

Per Engzell (), Arun Frey and Mark D. Verhagen
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Per Engzell: Leverhulme Centre for Demographic Science, University of Oxford, Oxford OX1 1JD, United Kingdom; Nuffield College, University of Oxford, Oxford OX1 1NF, United Kingdom; Swedish Institute for Social Research, Stockholm University, 106 91 Stockholm, Sweden
Arun Frey: Leverhulme Centre for Demographic Science, University of Oxford, Oxford OX1 1JD, United Kingdom; Department of Sociology, University of Oxford, Oxford OX1 1JD, United Kingdom
Mark D. Verhagen: Leverhulme Centre for Demographic Science, University of Oxford, Oxford OX1 1JD, United Kingdom; Nuffield College, University of Oxford, Oxford OX1 1NF, United Kingdom

Proceedings of the National Academy of Sciences, 2021, vol. 118, issue 17, e2022376118

Abstract: Suspension of face-to-face instruction in schools during the COVID-19 pandemic has led to concerns about consequences for students’ learning. So far, data to study this question have been limited. Here we evaluate the effect of school closures on primary school performance using exceptionally rich data from The Netherlands ( n ≈ 350,000). We use the fact that national examinations took place before and after lockdown and compare progress during this period to the same period in the 3 previous years. The Netherlands underwent only a relatively short lockdown (8 wk) and features an equitable system of school funding and the world’s highest rate of broadband access. Still, our results reveal a learning loss of about 3 percentile points or 0.08 standard deviations. The effect is equivalent to one-fifth of a school year, the same period that schools remained closed. Losses are up to 60% larger among students from less-educated homes, confirming worries about the uneven toll of the pandemic on children and families. Investigating mechanisms, we find that most of the effect reflects the cumulative impact of knowledge learned rather than transitory influences on the day of testing. Results remain robust when balancing on the estimated propensity of treatment and using maximum-entropy weights or with fixed-effects specifications that compare students within the same school and family. The findings imply that students made little or no progress while learning from home and suggest losses even larger in countries with weaker infrastructure or longer school closures.

Keywords: COVID-19; learning loss; school closures; social inequality; digital divide (search for similar items in EconPapers)
Date: 2021
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