By: Jean Kayitsinga

Photo credit: Joseph Sorrentino / Shutterstock.com
Photo credit: Joseph Sorrentino / Shutterstock.com

Introduction
The current novel coronavirus, SARS-CoV-2, which causes the coronavirus disease COVID-19 and gave rise to the pandemic in 2020, has affected the lives of millions in the United States (U.S.) and worldwide, including half a million deaths in the U.S. alone. The COVID-19 pandemic has exposed and exacerbated the already existing social, structural, and spatial inequalities, disrupted the routines of everyday life, and affected the well-being of individuals, families, and communities, with significant impacts on physical and mental health, education, jobs, food and housing security, and incomes. The COVID-19 pandemic has disproportionately affected racial and ethnic minority groups, with Latinos, African Americans, and Native Americans having rates at least double that of White Americans. Racial and ethnic minority groups are more likely to be poor, be employed as essential workers in low-paying service jobs that substantially increase their risk of contracting and dying from the virus, and experience poor health.
In education, children potentially experienced learning loss as a result of the pandemic, as the majority of elementary and secondary schools across the country were sent home in mid-March 2020. By April 2020, the vast majority of school districts transitioned to some form of distance learning, including virtual learning and, in some instances, supplemented with printed learning materials sent to students’ homes. In some school districts, classes were simply cancelled with no alternatives provided for learning. In order to help low-income students, some schools provided extra resources needed to support distance learning, such as laptops, tablet computers, internet access, and food. Some parents shifted to small group care and education arrangements in home-based settings.
The impacts of COVID-19 pandemic on the performance of K-12 students is still unknown. To assess such impacts would require comparing student performance prior to, during, and at the end of the pandemic. Kuhfeld and colleagues (2020) projected that students in grades 3 through 8 would start school in fall 2020 at 63 to 68% in reading and 37 to 50% in mathematics relative to the gains in a typical school year. It is expected that COVID-19 disruptions in schooling will result in setbacks for students in terms of performance. One would also expect that the impacts of COVID-19 will vary considerably depending on the quality of instruction the child was receiving while going to school compared to the quality of instruction the child received during the COVID-19 pandemic period. Further, the pandemic exposed the depth of structurally induced differences by race, gender, and class in society.
The impact of COVID-19 pandemic on education has been uneven. Minority and low-income children are more likely to experience learning losses as a result of class cancellation and the shift to distance learning formats. Minority and low-income children are affected more than others by school closures because they have fewer family resources and less access to online learning resources to offset the loss of face-to-face instruction time. The pandemic will likely widen achievement gaps along SES and race and ethnicity dimensions given varying family socioeconomic and online resources to compensate for lost school-learning time. Raudenbush and Eschmann (2015) reviewed studies comparing summer and academic-year learning and found that school attendance has significant effects on learning and that low-SES students benefit more from school than do high-SES students (Raudenbush and Eschmann, 2015). This and other studies suggest that in-person class cancellation would hurt more the academic achievement of low-SES than high-SES students, which would further exacerbate SES inequality in education.
As such, racial and ethnic minority families face significant challenges in facilitating learning environments that would compensate loss of in-person learning in school during the COVID-19 pandemic. Latino and African American students, in particular, are more likely to disproportionately experience learning loss, compounding the damaging effects of systemic racism that leave minority students with fewer and lower-quality resources, significant large class sizes, less qualified and experienced teachers, and less access to high-quality curricula.
This study examines educational disruptions caused by the COVID-19 pandemic, investigating three specific indicators: class cancellations, online learning only, and online learning plus sending printed materials home and some other ways. As the nation, states, and districts consider how to educate children during the pandemic, it is crucial to understand the effects of pandemic-induced disruptions on students’ loss of learning and those of online learning, particularly for racial/ethnic minority and low-SES students. This study answers the following research questions:
To what extent do educational disruptions caused by the COVID-19 pandemic vary by race/ethnicity?
To what extent do racial/ethnic disparities in educational disruptions vary by socioeconomic status during the COVID-19 pandemic?

Methods
Data and Sample
This study uses data from the 2020 Household Pulse Survey (HPS). To understand the effects of the COVID-19 pandemic on U.S. households, the U.S. Census Bureau conducted the HPS in collaboration with the Bureau of Labor Statistics, the National Center for Health Statistics, the United States Department of Agriculture’s Economic Research Service, the National Center for Education Statistics, and the Department of Housing and Urban Development. The Census Bureau selected large national, state, and large metropolitan statistical areas representative samples to provide timely data on the social and economic impacts of COVID-19.
Data collection of the HPS began on April 23, 2020 and was conducted online on a weekly basis using Qualtrics. The questionnaire covers many household areas, including employment status, spending and economic impact payments (stimulus), food sufficiency and food security, housing security, physical and mental health, access to health care, education disruptions, and demographic and socioeconomic characteristics. For the analysis here, data from Week 1 (April 23-May 5, 2020 through Week 21 (December 9-December 21, 2020) are used. Each week, new participants were added to maintain appropriate sample size and to minimize participants’ burden. Most participants (80%) only completed one week survey, but some participants were enrolled for two (15%) or three (5%) weeks. Because so few participants completed more than one weekly survey, only the first observation from any participants with repeated observations is used. The analytic sample includes households with school-age children enrolled in public and private schools and with no missing values on the education disruption outcomes (n = 381,098).

Measures
Dependent variables
For households with school-age children enrolled in public or private schools in the 2020-2021 school year, the HPS included a question that asks how the coronavirus pandemic affected how children received their education. Responses to that question were: 1) classes normally taught in person at the school were canceled, 2) classes normally taught in person moved to a distance-learning format using online resources, either self-paced or in real time, 3) classes normally taught in person moved to a distance-learning format using paper materials sent home to children, 4) classes normally taught in person changed in some other way. These response categories overlap because respondents could select more than one category. The dependent variables in this study are distance learning (online only), distance learning (online and paper materials sent home) plus some other way of learning, and 3) class cancellation during the COVID-19 pandemic. Each dummy variable is coded 1 for yes and 0 otherwise.

Race/Ethnicity
Race/ethnicity is the main independent variable. The HPS included questions on respondent’s race and ethnicity. A categorical variable of race/ethnicity included five categories: 1) non-Hispanic White, 2) non-Hispanic Black or African American, 3) Hispanic or Latino, 4) non-Hispanic Asian, and 5) Other racial/ethnic groups. Four dummy variables (1 = yes, 0 = no) were created for multivariate analysis. Non-Hispanic White was used as the reference group in the analyses.
 
Socioeconomic characteristics
Educational Attainment.
The HPS asked respondents the highest degree or level of school they have completed. Values for respondent’s education range from 1 = less than high school to 7 = graduate degree (e.g., master’s, professional, doctorate).

Household Income.
Household income is measured as the midpoint of each income category. Categories of income ranged from 1 = less than $25,000 to 8 = $200,000 or more. The midpoint estimate of the highest income category was obtained via a modified Pareto formula (Hout, 2004). Missing income values (5.3%) were coded to the median midpoint income of $87,500.

Covariates.
Models account for sociodemographic and other covariates that are associated with race/ethnicity and education outcomes. Covariates include age (in years), gender (1 = female), marital status (married (reference), widowed, divorced/separated, never married), and household size (total number of people in the household). Models also control for loss of employment income since March 13, 2020 (1 = yes, 0 = no), food insecurity before March 13,2020 [whether or not people in the household did not have enough food to eat, 1 = sometimes or often not enough to eat, 0 = enough of the kinds of food to eat (reference)], health insurance (1 = yes, 0 = no), large metropolitan area (1 = yes, 0 = no), and the three week periods of the survey to account for changes in distance learning during data collection (April-December, 2020). Descriptive statistics of select variables are displayed in Table 1.

Analytical Strategy
To examine variations in distance learning (online only), distance learning (online and paper materials sent home) and some other way of learning, and class cancellations during COVID-19 pandemic by race/ethnicity, estimated logistic regression models are used to predict outcomes by race/ethnicity (Models 1 & 2), race/ethnicity and education (Model 3), race/ethnicity and household income (Model 4), and race/ethnicity, education, and household income (Model 5). Because of the HPS complex sampling design, personal weight is applied to the descriptive results in Table 1 and the multivariate analyses in Tables 2 through 4. All analyses were conducted using Stata 15.1.

Results
Descriptive Analysis Results
The COVID-19 pandemic dramatically shifted the way children were being educated. Figure 1 displays learning alternatives provided to school-age children during the pandemic. Nearly 76% of households with school-age children during the study period (April 23—December 21, 2020) reported that their children engaged in some form of “distance learning” from home, including online learning (70%) and paper resources sent home (5%) whereas 7% of households reported that their children learned in some other way. About 11% of households indicated that classes that were normally taught in person at their child’s school were cancelled while 6% of households reported that school did not close (Figure 1).
Figure 1. Learning Alternatives Provided to School-Age Children during the COVID-19 Pandemic (April 23 – December 21, 2020)

Learning alternatives during COVID-19 pandemic varied by race/ethnicity. About 76% of Latino children, 73% of African American, 84% of Asian, and 77% of Other racial/ethnic children were engaged in some form of distance learning compared to 75% of non-Hispanic White children. About 4% of Latino, 6% of African American, 4% of Asian, and 7% of Other racial/ethnic children were engaged in “some other way of learning” compared to 8% of non-Hispanic White children. About 15% of Latino children, 17% of African American, 9% of Asian, and 12% of Other racial/ethnic childrens’ classes were cancelled compared to 9% of non-Hispanic White children’s classes. School did not close during the pandemic for about 4% of Latino, 4% of African American, 3% of Asian, and 5% of Other racial/ethnic children compared to 8% of non-Hispanic White children (Figure 2).

Figure 2. Learning Alternatives Provided to School-Age Children during the COVID-19 Pandemic (April 23 – December 21, 2020) by Race/Ethnicity

Multivariate Analysis Results
Distance Learning – Online Only.
Race/Ethnicity and Distance Learning.
Model 1 (Table 2) shows the effect of race/ethnicity on online learning with no other covariates while model 2 shows the effect of race/ethnicity, net of the effects of selected covariates. The results in model 1 show that the odds of online learning for Latino children are not significantly different from those of non-Hispanic White children. The odds of online learning for Asian children are 70% higher than those of non-Hispanic White children. For African American children, the odds of online learning are 16% lower than those of non-Hispanic White children. The odds of online learning for Other racial/ethnic group children are not significantly different from those of non-Hispanic White children (Model 1).

Table 2. Logistic Regression Analyses Predicting Online Learning during COVID-19 Pandemic (Odds ratios with robust standard errors in parentheses)

After controlling for selected covariates, the results in model 2 show that the odds of online learning for Latino children remain not statistically significantly different from those of non-Hispanic White children. The odds of online learning for Asian children are 43% higher than those of non-Hispanic White children. African American children have 14% lower odds of online learning than non-Hispanic White children. Other racial/ethnic group children’s odds of online learning are 14% higher than those of non-Hispanic White children (Model 2).

Race/Ethnicity, Education, and Online Learning.
The results in model 3 (Table 2) show that higher education is associated with greater online learning, net of sociodemographic and other covariates in the model. By adding education in model 3, the odds of online learning during the COVID-19 pandemic are 18% higher for Latino children, 36% higher for Asian children, and 14% higher for Other racial/ethnic group children as compared to those of non-Hispanic White children. Respondents’ education becomes increasingly important in explaining the effect of race/ethnicity on online learning as evidenced by significant and positive interactions between Latino and education and between African American and education. The odds of online learning increase further for Latino and African American children whose parents have higher education (Table 2).

Race/Ethnicity, Household Income, and Online Learning.
The results in model 4 (Table 2) show that higher household income is associated with higher online learning, net of sociodemographic and other covariates in the model. By adding household income in model 4, the odds of online learning during the COVID-19 pandemic are 12% higher for Latino children, 42% higher for Asian, and 14% higher for Other racial/ethnic group children as compared to non-Hispanic White children. Similar to education, household income becomes increasingly important in explaining the effect of race/ethnicity on online learning as evidenced by significant and positive interactions between Latino and household income and between African American and household income. The odds of online learning increase further for Latino and African American children as household income increases (Table 2).

Race/Ethnicity, Education, Household Income,and Online Learning.
Finally, model 5 adds both respondent’s education and household income and the interaction of race/ethnicity and education. Results from this final model show that the odds of online learning during the COVID-19 pandemic are 21% higher for Latino children, 7% higher for African American, 36% higher for Asian, and 15% higher for Other racial and ethnic group children as compared to those in non-Hispanic White children, net of the effects of education, household income, other sociodemographic and other covariates in the model. Both education and household income remain significantly and positively associated with online learning during the COVID-19 pandemic and the odds of online learning further increase as respondent’s education increases for Latino and African American children (Table 2).
Figure 3 displays predicted probabilities online-learning by race/ethnicity and education to ease interpretation of the results in model 5 and provide a visual assessment of the gap in online learning by race and ethnicity and education (Figure 3). The probability of online learning is significantly higher among respondents with a graduate degree than it is among those with less than a high school education. The probability of online learning is significantly higher among Asian, Latino, African American, and Other racial and ethnic group children than it is among non-Hispanic White children at each level of respondent’s education (Figure 3).

Figure 3. Average Marginal Effect of Race and Ethnicity by Respondent’s Education on Predicted Probability of Online Learning


Distance Learning (online and materials sent home) and Other Way of Learning.
Race/Ethnicity and Distance/Other Way Learning.
The results in model 1 (Table 3) show that the odds of distance/other way learning are 16% lower for Latino children and 24% lower for African American children than those of non-Hispanic White children.  The odds of distance/other way learning for Asian children are 51% higher than those of non-Hispanic White children (Model 1).
After controlling for selected covariates in model 2, the results show that the odds of distance/other way learning are 13% lower for Latino children and 20% lower for African American children than those of non-Hispanic White children. The odds of distance/other way of learning for Asian children are 32% higher than those of non-Hispanic White children. The odds of distance/other way learning for Other racial/ethnic group children are 13% higher than those of non-Hispanic White children (Model 2).

Table 3. Logistic Regression Analyses Predicting Online and Other Way of Learning during the COVID-19 Pandemic (Odds ratios with robust standard errors in parentheses)

Race/Ethnicity, Education, and Distance/Other
Way Learning.
Model 3 (Table 3) adds education and the interaction of race/ethnicity and education. The results show that higher education is associated with greater odds of distance/other way learning, net of sociodemographic and other covariates in the model. By adding education in model 3, the odds of distance/other way learning during the COVID-19 pandemic for Latino children are not significantly and statistically different from those of non-Hispanic White children. The odds of distance/other way learning are 23% higher for Asian children, and 16% higher for Other racial/ethnic group children as compared to those of non-Hispanic White children. The odds of distance/other way learning for African American children are 12% lower than those of non-Hispanic White children. Respondent’s education becomes increasingly important in explaining the effect on African American children of distance/other way learning as evidenced by a significant and positive interaction between African American and education. The odds of distance/other way learning increase further for African American children and become significantly higher than those of non-Hispanic White children as levels of respondent’s education increase (Table 3).

Race/Ethnicity, Household Income, and Distance/Other Way Learning.
Model 4 (Table 3) adds household income. The results show that higher household income is associated with higher distance/other way learning, net of sociodemographic and other covariates in the model. By adding household income in model 4, the odds of distance/other way learning during the COVID-19 pandemic for Latino and African American children are not significant and statistically different from those of non-Hispanic White children. The odds of distance/other way learning are 31% higher for Asian and 16% higher for Other racial/ethnic group children as compared to those of non-Hispanic White children. Similar to respondent’s education, household income becomes increasingly important in explaining the effect of race/ethnicity on distance/other way learning as evidenced by significant and positive interactions between Latino and household income and between African American and household income. The odds of distance/other way learning increase further for Latino and African American children and become significantly higher than those of non-Hispanic White children as household income increases (Table 3).

Race/Ethnicity, Education, Household Income, and Distance/Other Way Learning.
Finally, model 5 adds both education and household income and the interaction of race/ethnicity and education. The interaction terms between race/ethnicity and household income were not significant and were dropped from the model. Results from this final model show that the odds of distance/other way learning during the COVID-19 pandemic for Latino children are not significantly and statistically different from those of non-Hispanic White children. The odds of distance/other way learning during the COVID-19 pandemic are 23% higher for Asian children, 7% higher for African American children, 36% higher for Asian children and 17% higher for Other racial and ethnic group children as compared to those in non-Hispanic White children, net of the effects of education, household income, sociodemographic and other covariates in the model. The odds of distance/other learning for African American children are 7% lower than those of non-Hispanic White children. Both education and household income remain significantly and positively associated with distance/other way learning during the COVID-19 pandemic and the odds of distance/other way learning further increase as respondent’s education increases for Latino and African American children (Table 3).
Figure 4 displays predicted probabilities by race/ethnicity and parental education to ease interpretation of the results in model 5 and provide a visual assessment of the gaps in distance/other way learning by race and ethnicity and respondent’s education (Figure 4). The plot highlights distance/other way learning disparities by race/ethnicity and education. The probability of distance/other way learning is significantly higher among those with a graduate degree than it is among those with less than a high school education. The probability of distance/other way learning is higher among Asian, Other racial and ethnic group, and Latino children than it is among non-Hispanic White children at each level of education. The probability of distance/other way learning is significantly lower among African American children than it is among non-Hispanic White children at each level of education. (Figure 4).

Figure 4. Average Marginal Effect of Race and Ethnicity by Respondent’s Education on Predicted Probability of Distance/Other Way Learning
 

Class Cancellation.
Race/Ethnicity and Class Cancellation.
The results in model 1 (Table 4) show that Latino children have about 87%, African American children (136%), and Other racial and ethnic group children (33%) greater odds of class cancellation than non-Hispanic White children, respectively (Model 1). After controlling for selected covariates in the model 2, the results show that Latino children have about 60% and African American (73%) greater odds of class cancellation than non-Hispanic White children (Model 2).

Race/Ethnicity, Respondent’s Education, and Class Cancellation.
Model 3 (Table 4) adds respondent’s education and its interaction with race/ethnicity. The results show that education reduces the odds of class cancellation, net of sociodemographic and other covariates in the model. By adding education in model 3, the odds of class cancellation during the COVID-19 pandemic are 36% higher for Latino children, 70% higher for African American children, and 16% higher for Asian children as compared to those in non-Hispanic White children.

Race/Ethnicity, Household Income, and Class Cancellation.
Model 4 (Table 4) adds household income and its interaction with race/ethnicity. The results show that household income reduces the odds of class cancellation, net of sociodemographic and other covariates in the model (Table 4). By adding household income in model 4, the odds of class cancellation during the COVID-19 pandemic are 45% higher for Latino children and 57% higher for African American children as compared to those of non-Hispanic White children.

Race/Ethnicity, Respondent’s Education, Household Income, and Class Cancellation.
Results in the final model (Table 4) show that the odds of class cancellation during the COVID-19 pandemic are 31% higher for Latino, 61% higher for African American, and 15% higher for Asian children as compared to those in non-Hispanic White children, net of the effects of selected covariates in the model. Both education and household income remain significantly and negatively associated with class cancellation.

Table 4. Logistic Regression Analyses Predicting Classes Cancellation during COVID-19 Pandemic (Odds ratios with robust standard errors in parentheses)

Figure 5 displays predicted probabilities of class cancellation by race/ethnicity and respondent’s education (Figure 5). The plot highlights class cancellation disparities by race and ethnicity and by respondent’s education. The probability of class cancellation significantly declines as education increases. The probability of class cancellation is significantly higher among Latino and African American children than it is among non-Hispanic White children at each level of education (Figure 5).

Figure 5. Average Marginal Effect of Race/Ethnicity by Parental Education on Predicted Probability of Class Cancellation

Discussion and Conclusions
This study examines racial/ethnic differences in learning alternatives during the COVID-19 pandemic (April 23 - December 21, 2020). More than three-fourths of households with school-age children in the United States transitioned to some form of distance learning, including using online resources and paper materials sent home to children. About 12% of households reported that in-person classes at the school were cancelled, changed in some other way (7%), or that there was no change because schools did not close (6%). These learning alternatives during the COVID-19 pandemic varied by race/ethnicity. The odds of online learning are significantly higher for Latino, Asian, African American, and Other racial/ethnic children than for non-Hispanic White children. The odds of distance/other way learning are not significantly different from those of non-Hispanic White children. The odds of distance/other way learning are significantly higher for Asian and Other racial/ethnic children, but lower for African American children than they are for non-Hispanic White children. The odds for class cancellation were significantly higher for Latino, African American, and Asian children than there were for non-Hispanic White children.
The odds of online learning or distance/other way learning increase significantly by education and household income, whereas the odds of class cancellation decrease by respondent’s education and household income. With regard to socioeconomic position, differences in levels of education and household income partially explain the racial/ethnic gaps in online learning and distance/other way learning. Racial/ethnic differences in education and household income account for an additional 18% of the Latino/White, 25% of the African American/White, and 2% of the Other racial and ethnic group/White differences in online learning and a 5% decrease in the Asian/White differences in online learning (calculated by comparing odds ratio in model 2 and model 5, Table 2). Racial/ethnic differences in education and household income account for an additional 24% of the Latino/White, 17% of the African American/White, and 3% of the Other racial and ethnic group/White differences in distance/other way learning and a 7% decrease in the Asian/White differences in distance/other way learning (calculated by comparing odds ratio in model 2 and model 5, Table 3). Asian American students have the highest probability of any other racial/ethnic groups to rely on distance learning during COVID-19 pandemic.
Both respondent’s education and household income partially contribute to racial/ethnic differences in class cancellation. Racial/ethnic differences in education and household income account for 18% decrease in the Latino/White and 7% in the African American/White differences in class cancellation, and a 9% increase in the Asian/White differences in class cancellation (calculated by comparing odds ratio in model 2 and model 5, Table 4). Latino, African American, and Asian students have higher predicted probability of class cancellation than their non-Hispanic White counterparts. The predicted probability of class cancellation significantly declines as parental education increases for Latino, African American, and Asian students as compared to their non-Hispanic White counterparts.
This study explores education disruptions caused by the COVID-19 pandemic and assesses the effects of race/ethnicity and socioeconomic status; however, limitations should be noted. First, the Household Pulse Survey asks how the COVID-19 pandemic affected how children in the household receive education during the 2020-2021 school year, but the survey does not tell which child in the household is affected, nor does it tell how many children are affected by education disruptions during the COVID-19 pandemic. More importantly, there is no way of knowing how education disruptions during the COVID-19 pandemic affected the educational performance of children. Second, the Household Pulse Survey’s weekly samples are only representative of the nation, states, and large metropolitan areas. It would be useful to be able to link the HPS data to school districts or census geographies. There were greater variations in education disruptions within and between states. It would be important to know, for example, how different schools in specific school districts coped with COVID-19 pandemic education disruptions. Third, the Household Pulse Survey does not collect detailed data on race/ethnicity, so it was not possible to assess how different Latino and Asian subgroups based on the country of origin (e.g., Mexican, Puerto Rican, Cuban, Chinese, Indian, Japanese, Vietnamese etc.) dealt with education disruptions of their children. This masks substantial diversity that exists within Latino and Asian populations. Finally, the Household Pulse Survey is an internet-based survey, which excludes people who do not have internet because they cannot afford it or those who choose not to use the internet. This omits some of the most vulnerable populations such as minority and lower-SES children and families without internet connection.
Findings in this study illuminate future research suggestions. First, future education researchers can design a study that assesses the impact of COVID-19 pandemic on student performance. That would require determining the quality of education the child was receiving while going to school prior to the COVID-19 pandemic and comparing it to the quality of education the child received at home during the COVID-19 pandemic period. Further, such a study would reveal if the racial/ethnic and SES gaps in educational performance have widened as a result of the COVID-19 pandemic. Second, future education researchers can propose research on the impact of the COVID-19 pandemic on the education of the most vulnerable populations, such as racial and ethnic minority, immigrant, low-SES children and families. Such a study would take into consideration the substantial diversity of different racial/ethnic minorities and detailed social processes and family dynamics of racial/ethnic minority and low-SES families. Finally, future education research can investigate whether distance learning and existing technologies can enhance students’ skills in comparison to in-person learning.  Such a study would inform legislators, school officials, and parents whether distance learning is a good alternative to in-person learning during future infectious diseases’ pandemics.
The current COVID-19 pandemic has affected daily lives in unprecedented ways. It resulted not only in half a million deaths in the United States, but it has also caused suffering and hardships due to economic crisis with levels of unemployment unseen since the Great Depression. It has also engendered food insecurity for many households, housing crises, and school closures, resulting in education disruptions for many children. The majority of elementary and secondary schools across the country sent students home in mid-March 2020 and thereafter transitioned to some form of distance learning or to a combination of distance learning and other ways of learning. Some schools adopted a hybrid format, providing both in-person learning as well as distance learning depending on the level of community rate of COVID-19 infection. This study provides one of the first assessments of education disruptions by race/ethnicity in the U.S. during the period of the COVID-19 pandemic from April 23 – December 21, 2020 using the HPS, one of the few surveys that provides national-level data on the social and economic impacts of the COVID-19 pandemic.
To ensure that children receive education that is equal to or better to that they received prior to the COVID-19 pandemic, federal, state, and local school officials should accelerate efforts to safely reopen schools to improve the skills of children through in-person learning in classroom. At the same time, concerted efforts are needed to ensure education equality across all racial/ethnic and income groups. Minority and low-SES students benefit more than White and high-SES counterparts when they attend school than when they are not in school. Legislators could consider providing all needed resources to safely reopen all schools. For schools still in high-risk areas for COVID-19 pandemic and with poor in-school controls where it is still considered unsafe to reopen, providing income support for households that are disadvantaged and have less access to computer and internet availability should be taken into consideration to prevent further learning losses among racial/ethnic minority and low-SES children. Without such action, the current COVID-19 pandemic could become a social crisis that will have long-term consequences for all children and families and will further exacerbate the already existing inequalities in education. Finally, once schools reopen, it is important that pedagogical approaches be modified to accelerate learning among all students and reduce existing social inequalities in education
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