School closure policies and student reading achievement: evidence across countries

Abstract

The COVID-19 pandemic disrupted education worldwide as educational systems made the decision to close schools to contain the spread of the virus. The duration of school closures varied greatly internationally. In this study, we use international variation in school closure policies to examine the effects of school closures on student achievement. Specifically, we use representative trend data from more than 300,000 students in 29 countries to examine whether the length of school closures is related to changes in student achievement before and after the outbreak of COVID-19. We observe a significant and substantial negative effect of school closures on student reading achievement. This school closure effect remains even after controlling for measures of pandemic severity such as infection rates, vaccination policies, and a measure of lockdown stringency. The estimated effect implies that a year of school closures corresponds roughly to the loss of a little more than half a school year of learning. This effect is even more pronounced for socioeconomically disadvantaged students and those without home computer access.

Covid-19 and the European Education Performance Decline: A Focus on Primary School Children's Reading Achievement between 2016 and 2021

“…It is also widely agreed that countries opting for longer school closure paid the price of higher learning loss (De Witte and Francois 2022, Patrinos 2022 estimating that 1 week of additional school closure increases the learning loss by 0.01 standard deviations). The latter has also been shown by a study examining PIRLS reading outcomes and school closure length for 29 countries (Kennedy and Strietholt 2023). Furthermore, remote learning appeared to be more effective in later lockdown phases compared to spring 2020 (König and Frey 2022).…”

Challenges for the Design of International Assessments: Sampling, Measurement, and Causality

“…There are further examples of how data from cross-sectional international assessment studies can be combined or supplemented with external data to strengthen designs that make causal inference more credible, such as difference-in-differences designs, instrument variable regression, regression discontinuity analyses, and matching approaches (e.g., Cordero et al, 2018;Hogrebe & Strietholt, 2016;Kennedy & Strietholt, 2023;Schlotter et al, 2011;Steinmann & Olsen, 2022;Strello et al, 2021) Beyond creatively utilising and combining existing cross-sectional data, there are ongoing initiatives aimed at altering the designs of these studies themselves. For instance, amidst the COVID-19 pandemic, adaptations were made to the teacher survey component of ICILS, resulting in the same teachers being surveyed in 2020 as they were in 2018 (Strietholt et al, 2021).…”