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# Pandemic School Closures May Increase Inequality in Test Scores

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Schools have been closed across the country and will remain closed until September in most provinces. The decision to reopen should take into account current inequalities in cognitive skills across the country and the impact of school interruptions on knowledge accumulation. In this article, we use information from a companion article to estimate the socioeconomic achievement gaps of 15-year-olds across Canada and assess the impact of the pandemic on inequalities in education. Using estimates from the literature on the impact of school closures, we find that the socioeconomic skills gap measured using Programme for International Student Assessment data could increase by more than 30 percent.
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publication by the Canadian Public Policy/Analyse de politiques. Due to
the importance of the subject matter, and the rapidly changing nature of
the topic, a pre-publication version has been released. A final,
copyedited and formatted version will be published at a later date.
Pandemic School Closures May Increase Inequality in Test Scores
Catherine Haeck and Pierre Lefebvre
Department of Economics
Université du Québec à Montréal
Montréal, Québec
June 23, 2020
https://utpjournals.press/doi/pdf/10.3138/cpp.2020-055 - Thursday, July 02, 2020 7:26:02 AM - IP Address:38.145.92.48
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publication by the Canadian Public Policy/Analyse de politiques. Due to
the importance of the subject matter, and the rapidly changing nature of
the topic, a pre-publication version has been released. A final,
copyedited and formatted version will be published at a later date.
Abstract
Schools have been closed across the country and will remain closed until September in most
provinces. The decision to reopen should take into account current inequalities in cognitive skills
across the country and the impact of school interruptions on knowledge accumulation. In this
article, we use information from a companion paper to estimate the socioeconomic achievement
gaps of 15-year-olds across Canada and assess the impact of the pandemic on inequalities in
education. Using estimates from the literature on the impact of school closures, we find that the
socioeconomic skills gap measured using PISA data could increase by more than 30 percent.
JEL: I20, I21, I28
Keywords: cognitive skills, socioeconomic inequalities, PISA, pandemic, Canadian provinces
Mots clés: habilités cognitives, inégalités socioéconomiques, PISA, pandémie, provinces
# This analysis is based on Statistics Canada’s surveys which produced PISA data sets for the
departments of education of the Canadian provinces and the OECD consortium. All computations
on these microdata were prepared by the authors who assume the responsibility for the use and
interpretation of these data. The authors would like to thank Marc Frenette, Gino Santarossa, the
Editor and Guest Editor of the CPP Special Edition on COVID-19.This research was funded by
two research grants from the Fonds de recherche du Québec Société et Culture (FRQSC),
Subvention Soutien aux équipes de recherche et Subvention Action concertée, Programme de
recherche sur la pauvreté et l'exclusion sociale, Phase 4
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publication by the Canadian Public Policy/Analyse de politiques. Due to
the importance of the subject matter, and the rapidly changing nature of
the topic, a pre-publication version has been released. A final,
copyedited and formatted version will be published at a later date.
1. Introduction
In the midst of the COVID-19 pandemic, primary and secondary schools across the country
have been closed, yet school interruptions are known to have short and long-term negative effects
on students’ academic outcomes and perseverance (e.g. Meyers and Thomasson (2017); Belot et
al. (2010)). These effects differ by socioeconomic status (SES) and therefore school interruptions
have the potential to exacerbate inequalities among students. As a result, the decision to reopen
schools across the country should take into account both health concerns related to the
propagation of the virus and the impact of school closures on inequalities in education across the
country. Using PISA data, combined with the approach used in a companion paper (Haeck and
Lefebvre, 2020) on the SES achievement gaps of 15-year-olds across Canada, we provide a back-
of-the-envelope calculation of the impact of the pandemic on SES inequalities in education.
2. School interruptions, a brief review
The literature shows that school interruptions can have a negative impact on students’
academic skills and perseverance (e.g. Cooper et al. (1996); Meyers and Thomasson (2017);
Belot et al. (2010)), and these impacts may differ by socioeconomic status. Several strategies
have been used to document the impact of school interruptions on academic achievement.
The literature that exploits summer learning losses finds mixed results on average, but seems
to suggest that mean declines or stagnation typically hide differences by socioeconomic status
(see Atteberry and McEachin (forthcoming) for a complete review). Many recent studies refer to
kindergarten children (e.g. Downey, Von Hippel, & Broh (2004), Von Hippel and Hamrock
(2019)), which is not our main focus here. Atteberry and McEachin (forthcoming) exploit data on
over 200 million test scores in 32,000 schools across the United States between 2008 and 2016.
They find mean summer losses in grades 1 to 8 in both math and English, and the variance of
summer learning losses is large. This implies that some students lose a lot of ground, while others
gain some ground. Race and SES only explain a small fraction of the variance, but they certainly
do play a role. Cooper et al. (1996) review the literature on school interruptions during the
summer and find that students lose about one month of equivalent schooling over the summer.
Their meta-analysis also suggests that the impact is steeper in higher grades and losses are more
important in math than in reading. Finally, they document a differential impact in reading based
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publication by the Canadian Public Policy/Analyse de politiques. Due to
the importance of the subject matter, and the rapidly changing nature of
the topic, a pre-publication version has been released. A final,
copyedited and formatted version will be published at a later date.
on the SES of the students. More specifically, they find that students from low-income families
experience a decline in their reading skills (-1.5 months) while students from middle- to high-
income families experience an improvement in their reading skills over the summer (+2.3
months). Studies used in Cooper et al. (1996) are dated, most were conducted in the 1980s. Their
findings may not apply in the current context. On one hand, given that the labour force
participation of mothers has increased over the last 30 years, mothers may not be as available
during the summer months to supervise their children and, therefore the learning loss may be
higher now than before. At the same time, families with dual-income parents have more income
resources than ever before and they may therefore be able to provide an enriched environment
during the summer months. Finally, in the specific context of the pandemic, more educated
parents are more likely to have flexible jobs, access to internet-enabled personal computers or
laptops, which are more conducive than mobile devices to producing information (Frenette et al.
2020) and resources to help their children. In this sense, the impact may in fact be even stronger
than suggested in Cooper et al. (1996) as parents may get more involved than they normally
would during the summer. In addition to Cooper et al. (1996), Davies and Aurini (2013) study
learning inequalities over the summer in Ontario. They also find evidence suggesting that
socioeconomic disparities in literacy tend to increase over the summer.
Instead of using summer learning losses, Frenette (2008) uses a different identification
strategy, but comes to a similar conclusion. He exploits regulations around school entry age to
document the impact of instructional time. He finds that one less year of schooling is associated
with a score that is 6 percent lower in reading, 5.9 percent lower in math, and 4 percent lower in
science.
Educational attainment may also be impacted by school closures. Meyers and Thomasson
(2017) study the impact of school closures during the 1916 polio pandemic. School closures
occurred at the beginning of the school year and lasted only a few weeks, yet it had devastating
effects on school perseverance. They find that school closures reduced educational attainment of
children aged 14 to 17 during the pandemic, but not that of younger children. They find that a one
standard-deviation increase in the number of polio cases caused one in every fourteen students to
achieve one less year of schooling. This is an important lesson for high schools come September.
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publication by the Canadian Public Policy/Analyse de politiques. Due to
the importance of the subject matter, and the rapidly changing nature of
the topic, a pre-publication version has been released. A final,
copyedited and formatted version will be published at a later date.
Finally, Belot et al. (2010) study teachers’ strikes in Belgium in 1990 and also reach a similar
conclusion : school interruptions affect educational attainment in a permanent way. Baker (2013)
and Johnson (2011) also exploit teachers’ strikes using school-level data on Grade 3 and 6
students in Ontario. Baker (2013) documents that long strikes of ten days or more have large
negative impacts on test score growth. Johnson (2011) finds that school interruptions caused by
teachers’ strikes negatively affect the pass-rate on provincial exams and that those effects are
concentrated among students in disadvantaged schools.
3. Pandemic and educational inequalities
In our companion paper (Haeck and Lefebvre, 2020), we document the evolution of the
achievement gap over time between low and high SES students using microdata from the
Programme for International Student Assessment (PISA). PISA is a triennial survey of the skills
of 15-year-olds in three domains: reading, math and science. Here, we present the average
achievement gap by SES. To do so, we estimate the following equation for Canada and also for
each province separately:
, =+,++
5
=2 (1).
, is the PISA test score of student i in province p, it can be in math, reading or science in year
y. The equation is estimated for each survey year, but also by pooling all survey-years and adding
year fixed effects. The SES index is measured by the Highest International Socio-economic Index
of Occupational Status (HISEI) and transposed in quintiles1. As a result, the term ,
represents four dummy variables, one for each of the top four quintiles of the HISEI index. The
reference group is therefore the bottom quintile of the index, which represents students whose
parents have the lowest occupational status. Following our companion paper, the quintiles are
measured at the provincial level, but measuring them at the national level provides extremely
similar results. The vector includes student gender, age in months, expected grade, along with
a dummy for immigration status, and two dummies indicating the language spoken at home
(French, English, and others as the reference). Survey weights, plausible values and bootstrapped
weights derived by the OECD are used in the estimation procedure (refer to PISA Technical
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publication by the Canadian Public Policy/Analyse de politiques. Due to
the importance of the subject matter, and the rapidly changing nature of
the topic, a pre-publication version has been released. A final,
copyedited and formatted version will be published at a later date.
survey-years (top panel), and also for 2018 only (bottom panel).
Math
Science
SES
Coef.
SE
Coef.
SE
Coef.
All years
Q2
19.18
1.28
21.33
1.17
18.15
Q3
31.44
1.23
35.05
1.24
35.48
Q4
43.47
1.20
48.55
1.20
47.32
Q5
58.79
1.36
63.12
1.42
59.97
2018
Q2
19.03
2.90
20.38
3.15
18.15
Q3
35.50
3.55
38.05
3.45
35.48
Q4
48.17
3.02
50.39
3.26
47.32
Q5
62.17
3.42
62.66
3.56
59.97
Notes : This table only presents the estimated coefficient on the SES quintile dummies. The top panel
pools all survey-years together. The bottom panel is based on PISA 2018 data only. The reference group
for the SES quintiles is Q1 (the bottom quintile including students whose parents have the lowest
occupational status). Year fixed effects are included when all years are pooled together (top panel). All
models include the following control variables : student gender, age in months, expected grade, a dummy
for immigration status, and two dummies indicating the language spoken at home (French, English, and
others as the reference).
Source : Author's calculations
Results from Table 1 suggest that, in reading, students with parents in the second quintile (Q2) of
the SES index obtain an average score that is 21.3 points higher relative to students of Q1
parents. At the top end of the distribution, students of parents in the highest quintile (Q5)
generally obtain 63.1 points more on average. The PISA Technical report (OECD 2010) states
that a 40 point difference in test scores is approximately equivalent to one additional year of
schooling. In this sense, the SES gap we identify represents more than a year of schooling. In
math, the SES gradient is not as steep, from 19.2 points for Q2 relative to Q1, to 58.8 points for
Q5 relative to Q1. Finally, in science we find a SES gradient starting at 18.1 in Q2 to 60.0 in Q5.
Similar gradients are also observed in all ten provinces, with some variation across domains (see
Figures 1 to 3). Using only data from PISA 2018, we find similar gradients, slightly higher in
magnitude but not statistically different.
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publication by the Canadian Public Policy/Analyse de politiques. Due to
the importance of the subject matter, and the rapidly changing nature of
the topic, a pre-publication version has been released. A final,
copyedited and formatted version will be published at a later date.
Figure 1: Q5 versus Q1 SES gradient across Canada – Math score
Notes : Estimated SES Q5 coefficients. See note Table 1 for list of control variables.
Source : Author's calculations
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publication by the Canadian Public Policy/Analyse de politiques. Due to
the importance of the subject matter, and the rapidly changing nature of
the topic, a pre-publication version has been released. A final,
copyedited and formatted version will be published at a later date.
Notes : Estimated SES Q5 coefficients. See note Table 1 for list of control variables.
Source : Author's calculations
Notes : Estimated SES Q5 coefficients. See note Table 1 for list of control variables.
Source : Author's calculations
Since school interruptions across the country due to the pandemic will be of at least 3.2
months (5.5 months in total minus a summer period of 2.3 months2), using Cooper et al.’s
months,3 which would represent about 6 points on average in PISA. As mentioned above, Cooper
et al. (1996) is somewhat dated. To validate these findings, we use the estimates produced by
Frenette (2008). Since one less year of schooling is associated with a decrease of 6 percent in
reading, 5.9 percent in math, and 4 percent in science, and that the average PISA 2018 score in
Canada was 520 in reading, 512 in math and 518 in science, we estimate that an interruption of
3.2 months would represent a drop of 10 points in reading, 10 points in math and 7 points in
science. Both studies lead to similar estimates.
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publication by the Canadian Public Policy/Analyse de politiques. Due to
the importance of the subject matter, and the rapidly changing nature of
the topic, a pre-publication version has been released. A final,
copyedited and formatted version will be published at a later date.
These average impacts may mask important differences by SES. Using SES estimates of
Cooper et al. (1996) we find that students from low-income families may see their overall reading
score decline by an additional 2 months (or -8 points), while other children may gain 3.2 months
(or +12.8 points). This would increase the score gap between Q1 and Q5 students by 20.8 points,
an increase of more than 30 percent relative to the actual SES gap in Canada. Since online
teaching has taken place in some provinces, students have not been left completely idle. A drop
of 30 percent may therefore be a worst-case scenario. At the same time, given the differential
access to technology and parental support by SES, it may also be a fairly realistic estimate.
More recently, Davies and Aurini (2013) study learning inequalities over the summer in
Ontario. They also find evidence suggesting that socioeconomic disparities in literacy tend to
increase over the summer. They find that children in affluent families gain literacy skills over the
summer while those from the bottom SES quartile lose skills. According to their results, 25
percent of the observed skills gap by SES at the beginning of the school year is explained by
differential summer learning by SES. Their results are in line with our above estimate for the
pandemic.
On school perseverance, we can also expect a large negative impact. This is particularly
worrisome in general, but even more so in provinces where the high school dropout rate is higher.
On time completion rate is lowest in Québec.4 Our companion paper (Haeck and Lefebvre, 2020)
also shows that this is also the province in which a larger fraction of 15-year-olds are behind their
expected trajectories in the PISA data. Major human and financial resources will be needed in the
fall to help students persevere and succeed across the country, but it may be more severe in some
provinces.
As a final note, we would like to point interested readers to Escueta et al. (forthcoming), a
brilliant review of 126 studies on education technologies using controlled trials. The authors
point out that the effectiveness of online learning is highest if combined with incentives to learn
and interact. Teachers need to learn how to use technology to provide online teaching and they
need to provide retroaction to keep the students engaged. Teachers’ responses will determine the
depth of the impacts on the SES gap across the country. PISA 2021 survey data will be a valuable
source to evaluate our successes and our failures.
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publication by the Canadian Public Policy/Analyse de politiques. Due to
the importance of the subject matter, and the rapidly changing nature of
the topic, a pre-publication version has been released. A final,
copyedited and formatted version will be published at a later date.
3. Concluding remarks
Canada is one of the strongest performing OECD countries in the PISA results. However,
these results mask important differences by SES. The pandemic brings important challenges to
our provincial education systems. Our back-of-the-envelope calculation revealed that the SES
score gap could increase by as much as 30 percent. School interruption is likely to impact
perseverance in high school. A recent study on the polio pandemic showed that a few weeks of
interruption at the beginning of the school year caused a significant reduction in school
attainment among high school students. Clearly, incentives to graduate from high school have
evolved since 1916, but the duration of school interruptions is dramatically larger in this
pandemic than it was back then.
Inequalities in skills is not a contemporaneous problem that will be easily reabsorbed. Skills
acquired early in life beget skills over the life cycle, such that skills inequalities generally
translate into income inequalities (e.g. Chetty et al. 2011; Carneiro et Heckman, 2003). On a
macroeconomic scale, Hanushek and Woessmann (2015a and b) have also shown that skills
measured using PISA data are associated with our ability to generate economic growth.
Our lack of knowledge on the epidemiology of the virus among children, teenagers and
teachers at the start of the pandemic have appropriately led to our collective decision to close
schools across the country. As our knowledge evolves on the transmission and severity of the
virus such that our decisions are being reassessed, it would be important to factor in the impact of
school closures on academic inequalities and their long-term consequences.
While rising inequalities resulting from the pandemic should be our primary concern, we also
need to remember that inequalities in academic achievement observed throughout the PISA
surveys highlight a lingering issue that we will still need to address post-pandemic. Innovative
actions across our education system will need to be taken to mitigate the potential rise in
achievement gaps by SES during the pandemic, but also beyond the pandemic.
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publication by the Canadian Public Policy/Analyse de politiques. Due to
the importance of the subject matter, and the rapidly changing nature of
the topic, a pre-publication version has been released. A final,
copyedited and formatted version will be published at a later date.
References
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Belot, M. and D. Webbink. 2010. "Do Teacher Strikes Harm Educational Attainment of
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publication by the Canadian Public Policy/Analyse de politiques. Due to
the importance of the subject matter, and the rapidly changing nature of
the topic, a pre-publication version has been released. A final,
copyedited and formatted version will be published at a later date.
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Endnotes
1 This choice is explained in detail in Haeck and Lefebvre (2020).
2 We do not include the summer months because these happen every year and are embedded in
the observed gap.
3 Negative impact of one month over 2.3 months of summer multiplied by an additional 3.2
months of school closure due to the pandemic.
4 Education Indicators in Canada: An International Perspective, 2018 (81-604-X).
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... The interruption they documented lasted eight weeks, while in Canada, schools were closed for over 16 weeks in most of the country. Haeck and Lefebvre (2020) show that academic inequalities by socioeconomic status are large and comparable across Canadian provinces, and that they may have increased by as much as 30 percent as a result of school closures during the pandemic. ...
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... Spring 2020 was dominated by the first COVID-19-related school closures, confronting students, teachers, schools, and parents with a sudden switch from in-person learning to more or less systematic measures of remote learning. Numerous researchers warned that this sudden switch might have negative effects on student achievement in general and is likely to contribute to increasing achievement inequalities (Haeck & Lefebvre, 2020;Woessmann, 2020). Early projectionsbased on educational production functions, research on student absenteeism and summer learning loss, and national educational databases-aimed at providing first estimations of the potential learning loss due to the COVID-19-related school closures (Kaffenberger, 2021;Kuhfeld, Soland et al., 2020). ...
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COVID‐19 led to school closures and the necessity to use remote learning in 2020 and 2021 around the globe. This article provides results for a three‐level random‐effects meta‐analysis examining the average effect of the COVID‐19‐related school closures with respect to several moderator variables. The results showed a robust average effect of d=−0.175(SE=0.063$d = - 0.175( SE = 0.063$, p=0.013,95%CI[−0.308,−0.041])$p = 0.013,95\% {\rm{CI}}[ { - 0.308, - 0.041} ] )$. The moderator analysis was largely insignificant; however, the results tentatively point out that younger students in schools were more negatively affected compared to older students, and that the negative effect reduced with subsequent lockdowns in autumn and winter 2020/2021. The results are discussed with respect to potential explanations.
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The present research aimed to reveal how the COVID-19 pandemic influenced the mathematical reasoning of primary school students through mediation analysis. It was designed as ex post facto research. The research sample consisted of two cohorts. Cohort 1 included 415 primary school children who received face-to-face instruction by attending school for six months until COVID-19 emerged. Cohort 2 included 964 children who were taught curricular skills through distance education due to COVID-19 and school closures. In total, 1,379 primary school children were recruited into the research sample. Data were collected through a mathematical reasoning test by sending items from the instrument via Google Docs. The data were analysed with mediation analysis. Results demonstrated that the school closures due to the COVID-19 pandemic negatively influenced mathematical reasoning skills. Findings are discussed in the light of human interaction and Cattell's intelligence theory.
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The objective of the present study was to reflect on psychosocial intervention programs for the development of digital skills aimed at kids between the seventh and tenth grade of schooling in situations of post-pandemic vulnerability. The research methodology was non-experimental, documentary, descriptive, and reflective. The information was collected from multinational organisms and scientific articles from indexed magazines and web platforms. Obtained results indicate that the COVID-19 pandemic aggravated the vulnerability conditions in children living in multidimensional poverty conditions. For this reason, international organisms—UN, World Bank, ILO—have proposed the creation of programs that promote resilience among the vulnerable population, based on the use of virtual platforms. In this context, this investigation proposes the implementation of psychosocial intervention programs for the development of digital skills aimed at kids in situations of post-pandemic vulnerability.
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This Economic Insights article discusses the potential impact of recent school closures on learning and academic performance of school children. To benefit from online resources, students require access to internet-enabled devices that are suitable for learning. The article estimates the percentage of households with children under the age of 18 with access to these learning tools by level of household income, and also discusses the potential impact of receiving no instruction on academic performance based on an earlier Statistics Canada study.
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Do test score gaps between advantaged and disadvantaged children originate inside or outside schools? One approach to this classic question is to ask (1) How large are gaps when children enter school? (2) How much do gaps grow later on? (3) Do gaps grow faster during school or during summer? Confusingly, past research has given discrepant answers to these basic questions. We show that many results about gap growth have been distorted by measurement artifacts. One artifact relates to scaling: Gaps appear to grow faster if measurement scales spread with age. Another artifact relates to changes in test form: Summer gap growth is hard to estimate if children take different tests in spring than in fall. Net of artifacts, the most replicable finding is that gaps form mainly in early childhood, before schooling begins. After school begins, most gaps grow little, and some gaps shrink. Evidence is inconsistent regarding whether gaps grow faster during school or during summer. We substantiate these conclusions using new data from the Growth Research Database and two data sets used in previous studies of gap growth: the Beginning School Study and the Early Childhood Longitudinal Study, Kindergarten Cohort of 1998-1999.
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Education policy should be informed by research that distinguishes school-based learning from learning that occurs during non-school time. American studies find that socio-economic disparities in learning tend to widen over the summer months, the longest continuous stretch of non-school time. This paper analyzes the first large-scale Canadian study of summer learning. We collected data on literacy growth for a non-random sample of 1,376 Ontario children in Grades 1-3 during the summers of 2010 and 2011. Summer learning was widely dispersed with a mean of zero, and equal proportions of children had substantial learning gains and losses. There were strong disparities by family socio-economic status (SES), as affluent children gained literacy while those from poorer families lost literacy. We attributed 25 percent of the gap between the top and bottom SES quartiles at the start of the school year to the previous summer. We discuss implications for Canadian education policy and future research.
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How does schooling affect inequality in cognitive skills? Reproductionist theorists have argued that schooling plays an important role in reproducing and even exacerbating existing disparities. But seasonal comparison research has shown that gaps in reading and math skills grow primarily during summer vacation, suggesting that non-school factors (e.g., family and neighborhood) are the main source of inequality. Using the Early Childhood Longitudinal Study-Kindergarten Cohort of 1998-99, this article improves upon past seasonal estimates of school and non-school effects on cognitive skill gains. Like past research, this study considers how socioeconomic and racial/ethnic gaps in skills change when school is in session versus when it is not. This study goes beyond past research, however, by examining the considerable inequality in learning that is not associated with socioeconomic status and race. This "unexplained" inequality is more than 90 percent of the total inequality in learning rates, and it is much smaller during school than during summer. The results suggest, therefore, that schools serve as important equalizers: nearly every gap grows faster during summer than during school. The black/white gap, however represents a conspicuous exception.
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In recent years, there has been widespread interest around the potential for technology to transform learning. As investment in education technology continues to grow, students, parents, and teachers face a seemingly endless array of education technologies from which to choose—from digital personalized learning platforms to online courses to text message reminders to submit financial aid forms. Amid the excitement, it is important to step back and understand how technology can help—or in some cases hinder—learning. This review article synthesizes and discusses rigorous evidence on the effectiveness of technology-based approaches to education in developed countries and outlines areas for future inquiry. In particular, we examine randomized controlled trials and regression discontinuity studies across the following categories of education technology: (i) access to technology, (ii) computer-assisted learning, (iii) technology-enabled behavioral interventions in education, and (iv) online learning. We hope this synthesis will advance academic understanding of how technology can improve education, outline key areas for new experimental research, and help drive improvements to the policies, programs, and structures that contribute to successful teaching and learning. (JEL H52, H75, I20, O33)
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In Project STAR, 11,571 students in Tennessee and their teachers were randomly assigned to classrooms within their schools from kindergarten to third grade. This article evaluates the long-term impacts of STAR by linking the experimental data to administrative records. We first demonstrate that kindergarten test scores are highly correlated with outcomes such as earnings at age 27, college attendance, home ownership, and retirement savings. We then document four sets of experimental impacts. First, students in small classes are significantly more likely to attend college and exhibit improvements on other outcomes. Class size does not have a significant effect on earnings at age 27, but this effect is imprecisely estimated. Second, students who had a more experienced teacher in kindergarten have higher earnings. Third, an analysis of variance reveals significant classroom effects on earnings. Students who were randomly assigned to higher quality classrooms in grades K-3-as measured by classmates' end-of-class test scores-have higher earnings, college attendance rates, and other outcomes. Finally, the effects of class quality fade out on test scores in later grades, but gains in noncognitive measures persist.
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A review of 39 studies indicated that achievement test scores decline over summer vacation. The results of the 13 most recent studies were combined using meta-analytic procedures. The meta-analysis indicated that the summer loss equaled about one month on a grade-level equivalent scale, or one tenth of a standard deviation relative to spring test scores. The effect of summer break was more detrimental for math than for reading and most detrimental for math computation and spelling. Also, middle-class students appeared to gain on grade-level equivalent reading recognition tests over summer while lower-class students lost on them. There were no moderating effects for student gender or race, but the negative effect of summer did increase with increases in students’ grade levels. Suggested explanations for the findings include the differential availability of opportunities to practice different academic material over summer (with reading practice more available than math practice) and differences in the material’s susceptibility to memory decay (with fact- and procedure-based knowledge more easily forgotten than conceptual knowledge). The income differences also may be related to differences in opportunities to practice and learn. The results are examined for implications concerning summer school programs and proposals concerning school calendar changes