Andrew Bacher-Hicks – Education Next https://www.educationnext.org A Journal of Opinion and Research About Education Policy Wed, 21 Dec 2022 14:18:00 +0000 en-US hourly 1 https://wordpress.org/?v=5.4.2 https://i2.wp.com/www.educationnext.org/wp-content/uploads/2020/06/e-logo-1.png?fit=32%2C32&ssl=1 Andrew Bacher-Hicks – Education Next https://www.educationnext.org 32 32 181792879 Proving the School-to-Prison Pipeline https://www.educationnext.org/proving-school-to-prison-pipeline-stricter-middle-schools-raise-risk-of-adult-arrests/ Tue, 27 Jul 2021 09:00:25 +0000 https://www.educationnext.org/?p=49713736 Stricter middle schools raise the risk of adult arrests

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This spring, the Biden administration announced it would seek public comment on student race and school climate, which was roundly viewed as a precursor to restoring an Obama-era directive to reduce racial disparities in discipline practices. Those guidelines, which were rescinded by former Secretary Betsy DeVos, have been variously described as a critical means of protecting students’ civil rights and a dangerous overreach by the federal government that prevented schools from keeping students safe.

At issue is the school-to-prison pipeline—a term often used to describe the connection between exclusionary punishments like suspensions and expulsions and involvement in the criminal justice system. Black and Hispanic students are far more likely than white students to be suspended or expelled, and Black and Hispanic Americans are disproportionately represented in the nation’s prisons.

Is there a causal link between experiencing strict school discipline as a student and being arrested or incarcerated as an adult? Research shows that completing more years of school reduces subsequent criminal activity, as does enrolling in a higher-quality school and graduating from high school. Yet there is little evidence on the mechanisms by which a school can have a long-run influence on criminal activity.

To address this, we examine middle-school suspension rates in Charlotte-Mecklenburg Schools, where a large and sudden change in school-enrollment boundary lines resulted in half of all students changing schools in a single year. We estimate a school’s disciplinary strictness based on its suspension rates before the change and use this natural experiment to identify how attending a stricter school influences criminal activity in adulthood.

Our analysis shows that young adolescents who attend schools with high suspension rates are substantially more likely to be arrested and jailed as adults. These long-term, negative impacts in adulthood apply across a school’s population, not just to students who are suspended during their school years.

Students assigned to middle schools that are one standard deviation stricter—equivalent to being at the 84th percentile of strictness versus the mean—are 3.2 percentage points more likely to have ever been arrested and 2.5 percentage points more likely to have ever been incarcerated as adults. They also are 1.7 percentage points more likely to drop out of high school and 2.4 percentage points less likely to attend a 4-year college. These impacts are much larger for Black and Hispanic male students.

We also find that principals, who have considerable discretion in meting out school discipline, are the major driver of differences in the number of suspensions from one school to the next. In tracking the movements of principals across schools, we see that principals’ effects on suspensions in one school predicts their effects on suspensions at another.

Our findings show that early censure of school misbehavior causes increases in adult crime—that there is, in fact, a school-to-prison pipeline. Further, we find that the negative impacts from strict disciplinary environments are largest for minorities and males, suggesting that suspension policies expand preexisting gaps in educational attainment and incarceration. We do see some limited evidence of positive effects on the academic achievement of white male students, which highlights the potential to increase the achievement of some subgroups by removing disruptive peers. However, any effort to maintain safe and orderly school climates must take into account the clear and negative consequences of exclusionary discipline practices for young students, and especially young students of color, which last well into adulthood.

Desegregation in Charlotte-Mecklenburg

For decades, school enrollment and bus routes in the Charlotte-Mecklenburg school district were designed to achieve racial integration. The busing plan was ordered by a state judge and upheld by a unanimous U.S. Supreme Court decision in 1971, after the Swann family, who were Black, sued to reassign their 6-year-old son from an all-Black school to an integrated school closer to their home. The landmark Swann v. Charlotte-Mecklenburg Board of Education decision required the district to reassign students to new schools to balance their racial composition and influenced similar busing programs nationwide.

It was another parent lawsuit that ultimately ended mandatory busing and redrew school-zone boundaries in Charlotte-Mecklenburg again. In 1997, a white parent named William Capacchione sued the district because he believed his child was denied entrance to a magnet program based on race. This case led to a series of court battles that ended with a 2001 ruling by the Fourth Circuit Court of Appeals, which upheld an earlier state court order to stop using race in school assignments. The district had “eliminated, to the extent practicable, the vestiges of past discrimination in the traditional areas of school operations,” the court ruled.

As a result, over the summer of 2002, Charlotte-Mecklenburg Schools redrew school-attendance boundaries based only on classroom capacity and the geographical concentration of students around a building. This mechanical redistricting process rarely took advantage of environmental features such as streams and major roads, and was controversial because it often bisected existing neighborhoods. About half of all students changed schools between 2001–02 and 2002–03.

For some students, that meant going from a school where suspensions were relatively rare to a school with a different approach to discipline (see Figure 1 for an example). While all schools are held to the district’s code of conduct and guidance by the North Carolina Department of Education, different schools have higher or lower rates of suspensions and expulsions.

Many discussions about the school-to-prison pipeline center on the possibility that students experiencing suspension differ from other students in ways that could explain their higher levels of involvement in the criminal justice system later in life. The sudden reassignment of half of all Charlotte-Mecklenburg Schools students in the summer of 2002 meant that students who live in the same neighborhoods and previously attended the same school could be assigned to attend very different schools in the fall. This creates a natural experiment to identify the impact of a school’s approach to discipline, which we use to identify a school’s influence on a range of outcomes in adulthood, including educational attainment and criminal activity.

Figure 1: Redrawing School Boundaries in Charlotte-Mecklenburg Schools

A Natural Experiment

Our analysis focuses on 26,246 middle-school students who experienced the boundary change because they were enrolled in a Charlotte-Mecklenburg school in both the 2001–02 and 2002–03 school years. We use district administrative records that track students from 1998–99 through 2010–11. The data include information on student demographics, test scores for grades 3 through 8 in math and reading, and annual counts of days suspended. Overall, 48 percent of students are Black, 39 percent are white, and 8 percent are Hispanic. On average, 23 percent of students are suspended at least once per school year, and the average suspension duration is 2.3 days.

District records also include each student’s home address in every year, which we use to determine individual school assignments under the busing and post-busing regimes. To define residential neighborhood, we use the 371 block groups from the 2000 Census that include at least one Charlotte-Mecklenburg student. We use address records to assign students to these neighborhoods and to middle-school zones for both the pre- and post-2002 boundaries.

To look at long-term outcomes, we first match district records to Mecklenburg County administrative data for all adult arrests and incarcerations from 1998 through 2013. Sixth graders in 2002–03 who progress through school as expected would enter 12th grade in the 2008–09 school year. Because our data on crime extends through 2013, we use two main measures of criminal activity: whether the individual was arrested between the ages of 16 and 21 and whether the individual was incarcerated between the ages of 16 and 21. This allows us to observe crime outcomes for all students who were in grades 6 through 8 in 2002–03.

We also track college-going data from the National Student Clearinghouse. That includes records for every student of college age who had ever attended a Charlotte-Mecklenburg school, including students who transfer to other districts or private schools or who drop out of school altogether. Because our data end in the summer of 2009, we cannot examine longer-run measures of educational attainment such as degree completion. Thus we focus on 7th- and 8th-grade students and measure whether they attended college within 12 months of the fall after their expected high-school graduation date.

Approximately 12 percent of our sample eventually drops out of high school, while 23 percent attend a 4-year college within 12 months of their expected graduation date. Between the ages of 16 and 21 years old, 19 percent are arrested at least once and 13 percent are incarcerated at least once. While well above the national averages in terms of suspensions and crime, Charlotte-Mecklenburg Schools is fairly representative of large, urban school districts in the Southern United States.

The Impacts of a Strict School

To quantify each school’s strictness, we use the same basic method commonly used to estimate individual teachers’ value-added to student test scores. We examine the number of days students are suspended both in and out of school to calculate strictness, while controlling for student characteristics such as test scores, race, gender, special-education status, and limited-English proficiency status, among others. This produces an estimate of each school’s predicted impact on suspensions based on how frequently it had suspended students in previous years.

We find that an increase of one standard deviation in school strictness expands the likelihood of being suspended in a given school year by 1.7 percentage points, or 7 percent. The average annual number of days suspended per year grows by 0.38, a 16 percent increase.

How does this affect student outcomes later in life? We look at criminal activity throughout Mecklenburg County and find that students who attend a stricter school are more likely to be arrested and incarcerated between the ages of 16 and 21.

Students assigned a school that is one standard deviation more strict are 17 percent more likely to be arrested and 20 percent more likely to go to jail, based on our estimated increases of about 3.2 percentage points for arrests and 2.5 percentage points for incarcerations. In looking at what types of crimes are involved, we find that school strictness increases later involvement in crimes related to illegal drugs, fraud, arson, and burglary, but not in serious violent crimes like murder, manslaughter, rape, robbery, and aggravated assault.

We also look at the impact on student academic performance and educational attainment and find no evidence that school strictness affects overall achievement. Because we measure the net effect across all students in a school, this may be due to a balancing of two opposing forces: negative effects of lost instructional time for those students who were suspended and positive effects of reduced number of disruptive peers in the classroom for students who were not.

However, we do find evidence that suspensions negatively affect educational attainment. A one standard deviation stricter school increases the likelihood that a student drops out of high school by 1.7 percentage points, or 15 percent, and decreases the likelihood of attending a 4-year college by 2.4 percentage points, or 11 percent.

We then compare effects by race and find outsized impacts for Black and Hispanic students. Being assigned to a school that is one standard deviation more strict increases the average number of days suspended each school year by 0.43 for Black and Hispanic students compared to 0.21 days for non-minority students. That number is even larger for Black and Hispanic males, who are suspended 0.82 more days each year, on average—more than three times the effect for non-minority males.

As adults, Black and Hispanic students assigned to stricter schools are more likely to be arrested and incarcerated than their non-minority classmates. A one standard deviation stricter school increases the likelihood of being arrested by 3.9 percentage points for Black and Hispanic students compared to 2.7 percentage points for non-minority students (see Figure 2). The effect on incarceration in adulthood is 3.1 percentage points for Black and Hispanic students compared to 1.9 percentage points for non-minority students. Negative effects are especially pronounced among Black and Hispanic male students, who are 5.4 percentage points more likely to be arrested and 4.4 percentage points more likely to be incarcerated as adults.

While the average impact of a strict school across all students is negative, we do find small positive impacts on academic achievement for white male students. White male students who are assigned a school that is one standard deviation stricter score about 0.06 standard deviations higher on middle-school math and reading tests. This is consistent with prior studies that show positive short-run academic benefits to some students from removing disruptive peers from the classroom. However, we find no long-run impact on educational attainment for white males, who also experience substantial increases in adult arrests and incarcerations of 4.9 and 3.7 percentage points, respectively.

Figure 2: School Strictness Matters Most for Black and Hispanic Males

What Drives School Strictness?

We investigate three potential factors driving differences in school strictness. First, we look at the potential role of school peers. Prior research has found that peers are important contributors to students’ educational experiences, but we find little relationship between school strictness and peer characteristics, suggesting that our results are not driven by changes in peer composition.

Second, we test our main school strictness results alongside two other measures of school effects, based on student-achievement gains and teacher turnover. We find that disciplinary strictness is the only predictor of students’ later involvement in the criminal-justice system. This serves as further evidence that our results are driven by school effects on suspensions rather than other aspects of school quality or simply the disruption caused by sudden changes in enrollment patterns.

Finally, we turn to the role of school leaders, who have considerable discretion in how they handle disciplinary action. Principals have the authority to set parental meetings, after-school interventions, and in-school suspensions. Even the process for short-term out-of-school suspension is almost completely up to school leaders in Charlotte-Mecklenburg; the superintendent’s approval is only required for long-term suspensions of 11 days or more. We look at the movements of principals across schools and find that when a principal who has been strict in prior years switches into a new school, suspensions in the new school increase. This suggests that school effects on suspensions are driven by leadership decisions.

These findings echo the public’s anecdotal understanding of the strong role that principals play in establishing school climate and discipline. Consider Charlotte-Mecklenburg’s recent approach to limiting suspensions among young elementary-school students. Suspending very young students has come under public criticism across the country, with policymakers in New York City, Colorado, and New Jersey weighing moratoriums on the practice. The Charlotte-Mecklenburg school board considered a moratorium but opted to limit principal discretion instead and now requires the superintendent’s approval. In 2017–18, the first year of the new policy, the number of suspensions for K–2 students fell by 90 percent.

Implications

Misbehaving peers can have strong negative impacts on other students in the classroom, and all students need a safe, predictable, and peaceful environment to thrive. But our findings show that the school-to-prison pipeline is real and poses substantial risks for students in strict school environments. On average, students who attend middle schools that rely heavily on suspensions are at greater risk of being arrested and incarcerated as young adults and less likely to graduate from high school and go to college. Further, these effects are most pronounced for Black and Hispanic males, who are dramatically underrepresented among college graduates and overrepresented in the nation’s prison system.

This raises a critical question for policymakers and educators who enforce strict school discipline: for whom are our schools safe? And it establishes an opportunity for principals and organizations that support school leadership to weigh the tradeoffs between strict discipline practices and longer-term outcomes for students. As the nation continues to grapple with questions about racial equity and police reform, the contributing causal role that school-discipline practices play in raising the risk of criminality in adulthood cannot be ignored.

Andrew Bacher-Hicks is assistant professor of education at Boston University. Stephen B. Billings is associate professor at the University of Colorado Boulder. David J. Deming is professor at the Harvard Kennedy School and Harvard Graduate School of Education.

For more, please see “The Top 20 Education Next Articles of 2022.”

This article appeared in the Fall 2021 issue of Education Next. Suggested citation format:

Bacher-Hicks, A., Billings, S., Deming, D. (2021). Proving the School-to-Prison Pipeline: Stricter middle schools raise the risk of adult arrest. Education Next, 21(4), 52-57.

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The Covid-19 Pandemic Is a Lousy Natural Experiment for Studying the Effects of Online Learning https://www.educationnext.org/covid-19-pandemic-lousy-natural-experiment-for-studying-the-effects-online-learning/ Tue, 13 Jul 2021 09:00:11 +0000 https://www.educationnext.org/?p=49713712 Focus, instead, on measuring the overall effects of the pandemic itself

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The Covid-19 pandemic that prompted a nationwide shutdown of schools and a shift to online instruction in spring 2020 also prompted a wave of articles calling this instructional change a “natural experiment” that could be used to study the effects of online education. Yet the pandemic disrupted so many aspects of children’s academic, social, emotional, and economic lives that its broad scope poses serious challenges to isolating the causal impact of any specific change, such as the switch to remote instruction.

Educators and policymakers should proceed with caution when interpreting studies that attempt to identify such specific effects. Instead, researchers should focus on helping education leaders understand the overall impact of the pandemic on students, putting particular emphasis on discovering which groups have suffered the worst effects. The best evidence to date indicates that Covid-19 has had a substantial negative impact overall and has disproportionately harmed the learning of disadvantaged students. Continued research in this direction could provide a sharper picture of which students have faced the most severe challenges under Covid-19, pointing the way toward how best to allocate resources to address learning losses.

Econometric Challenges

In econometrics, an “instrument” is a variable that has a direct impact on the probability that an individual is treated by a policy of interest. For example, some people have suggested that the pandemic could serve as an econometric instrument to study the effects of online learning, since the pandemic dramatically increased the number of students learning virtually in 2020. Major concerns arise, though, in using the pandemic as an instrument to study the impacts of such a policy change. These concerns relate to the fact that a rigorous causal study must have both internal and external validity. Internal validity requires that econometric analyses capture the true causal impact of only the policy change of interest—in this case, the shift from in-person to online instruction—rather than the possible effects of other contemporaneous changes. External validity requires that the estimated effects of a policy change induced by the pandemic would accurately predict the effects of similar treatments in other contexts, such as a typical school year. The nature of the pandemic presents serious challenges to both the internal and the external validity of most research designs, including the use of the pandemic as an instrument.

Challenges to internal validity. To understand why many studies of pandemic-induced policy changes could suffer from serious threats to internal validity, first consider a common research design with notably strong internal validity: a randomized experiment. If researchers were to use a randomized experiment to estimate the impact of remote instruction on student learning, they would need to assign students at random to the treatment group (students who receive remote instruction) or the control group (students who receive in-person instruction). Assigning the treatment at random ensures there are no systematic differences between the two groups other than the treatment itself. A randomized experiment has high internal validity because it clearly isolates the impact of a particular treatment.

Quasi-experimental research designs, or “natural experiments,” take advantage of variations in treatment status that occur as a result of policy changes or other “natural” phenomena outside of a researcher’s control. While natural experiments eliminate the need to actively assign individuals to treatment and control groups, they typically face greater threats to internal validity than do randomized experiments. One common type of natural experiment uses an econometric instrument to estimate the effects of a particular policy change. The onset of the pandemic holds obvious appeal as an econometric instrument for studying the effects of online instruction, since the crisis caused a sudden shift to remote teaching. A key assumption of this research design, however, is that the policy change of interest (the shift to online learning) does not coincide with other relevant changes. In econometrics, this is known as the “exclusion restriction,” which requires that the econometric instrument (the pandemic) affect the outcome of interest (student learning) only through the policy change of interest (the shift to online learning) and not through other channels.

While the Covid crisis did spur the shift to online instruction, it fails the exclusion restriction because of the many contemporaneous changes that likely also affected student learning. Students shifted to remote learning as their parents lost jobs, as their family members suffered Covid’s health effects, and as they lost the ability to leave the house and see friends, among other significant changes to their lives. If Covid-19 did affect student learning, it would be difficult to attribute the changes in outcomes to remote instruction rather than any of these other contemporaneous factors. We illustrate this in Figure 1, which shows the potential use of Covid-19 as an econometric instrument for remote instruction. The exclusion restriction requires that there be no “causal arrow” between the other channels affected by Covid-19 and student learning, an assumption that is certainly violated based on both common sense and prior empirical evidence. It may be possible to estimate the overall effect of Covid-19 on student outcomes, but attributing that effect to any one channel is likely impossible.

Pathways through Which Covid May Affect Student Outcomes (Figure 1)

We can illustrate the violation of the exclusion restriction with an example from our own recent research into Covid’s impacts on household Internet-search behavior. In that work, we show that Covid-induced school closings caused parents to seek out online learning resources that might compensate for lost in-school instructional time. An example of this can be seen in the top panel of Figure 2, which shows a large increase in Google searches for “online learning” that corresponded precisely with the timing of the pandemic outbreak in the United States. This provides evidence that the Covid-19 crisis indeed represents a sudden shock to the demand for online learning resources.

Search Intensity for Online Learning and Economic Indicators (Figure 2)

At the same time, however, there were many other changes in students’ lives that are reflected in Internet search behavior. Data show, for example, that there were sudden and contemporaneous increases in Google searches for terms relating to the economic condition of households, such as “unemployment insurance” and “food stamps.” The pandemic changed students’ educational experiences but also generated a considerable economic shock to many households. These large, simultaneous changes make it difficult to separate the effects of one shock from another.

Challenges to external validity. The unprecedented circumstances surrounding the Covid-19 crisis also present serious challenges to external validity. Researchers typically examine whether the context and implementation of a policy shift are representative of potential future enactments of the same policy. Neither the context nor the implementation is likely to be representative in this case.

First, the learning environment during the pandemic is unlikely to generalize to typical school years because of the many changes in students’ lives that likely put a strain on their capacity to learn. For instance, students and young adults have reported substantial increases in anxiety and depression during the pandemic. Second, pandemic-induced policy changes were implemented in a way that is unlikely to resemble a more carefully planned implementation of the same policy in a typical year. For example, the pandemic-induced shift to online learning required teachers, with no advance warning, to quickly redesign lessons originally intended for in-person instruction. Under normal circumstances, teachers would have been afforded time to prepare lessons specifically for online instruction. Even in the fall of 2020, there was still substantial uncertainty around schooling logistics and instructional modality, making it difficult for educators to plan instruction effectively in advance. The unprecedented circumstances of the pandemic and the corresponding ad hoc policy shifts are therefore unlikely to generalize to well-planned policy changes in a typical school year.

The Overall Impacts of Covid-19 on Students

Although it is nearly impossible to disentangle the effect of any specific policy, the overall effect of the pandemic—including economic, health, social, and educational changes—is something we can attempt to assess. Moreover, as the pandemic continues to disrupt daily life more than a year after schools first closed, it is increasingly important to understand the impact of the pandemic itself. In addition to the short-run impacts on learning, a range of prior evidence suggests that the effects of health, social, and economic experiences in early childhood can persist into adulthood.

Emerging evidence on the short-run impacts shows that Covid-19 has caused substantial disruptions to students’ learning, particularly for disadvantaged students. Raj Chetty and colleagues find that student progress on Zearn, a popular online math platform, decreased by roughly 30 percent over spring 2020, with children in the lowest-income schools seeing progress drop by 50 percent and those in the highest-income schools quickly recovering to pre-pandemic levels. Nationwide evidence from fall 2020 MAP Growth assessments suggests that students lost ground in mathematics and that reading losses were concentrated among Black and Hispanic students in upper elementary grades. Recent work in Georgia suggests that students lost further ground as the school year progressed through the winter of 2020, with such losses larger among low-income, Black, and Hispanic students. Our research reveals one potential reason for these disparities: when the pandemic first struck, demand for online learning resources increased substantially less in low-income areas than in high-income areas of the United States (see “What Google Search Data Reveal about Learning During the Pandemic,” web only).

Education researchers predict that the pandemic will substantially increase achievement gaps between students from low- and high-income households, even beyond the 2020–21 school year. The best evidence to date shows that Covid-19 not only reduced the learning of the average student compared to typical school years, but that it also increased achievement gaps by disproportionately harming disadvantaged students.

What Comes Next?

Instead of framing the pandemic as a “natural experiment” for studying specific educational interventions, we propose that researchers and policymakers focus on measuring the overall effects of the pandemic itself. We believe it is possible to generate econometrically sound estimates of the overall social, emotional, and academic costs of the pandemic. The pandemic is, however, too large and unprecedented a shock to give us precise insights into individual aspects of children’s educational experiences that have changed. Too many things changed all at once.

After more than a year of pandemic-induced restrictions and shutdowns, there is reason for guarded optimism. Vaccinations have become widely available in the United States, Covid cases, hospitalizations, and deaths here have dropped rapidly, and the era of widespread school closures and fully remote instruction is ending. The educational effects of the pandemic are, however, likely to linger unless we identify the students who have been most adversely affected and provide additional resources to reverse these impacts. The best evidence to date shows that Covid has not only impeded the learning of the average student, but also widened achievement gaps by disproportionately harming the learning of low-performing students. Educators now face the challenge of not only making up for lost instructional time but also closing gaps that are even wider than usual. Though choices of how best to remedy these losses may be best left to individual states, districts, or schools, substantial resources should be devoted to these efforts. Without such investment, particularly among students who have experienced the greatest setbacks, we will likely enter an era of increased educational inequality persisting beyond the return of fully reopened schools.

Andrew Bacher-Hicks is assistant professor at Boston University Wheelock College of Education and Human Development, where Joshua Goodman is associate professor of education.

This article appeared in the Fall 2021 issue of Education Next. Suggested citation format:

Bacher-Hicks, A. and Goodman, J. (2021). The Covid-19 Pandemic Is a Lousy Natural Experiment for Studying the Effects of Online Learning: Focus, instead, on measuring the overall effects of the pandemic itself. Education Next, 21(4), 38-42.

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What Google Search Data Reveal About Learning During the Pandemic https://www.educationnext.org/google-search-data-reveals-about-learning-pandemic/ Wed, 15 Jul 2020 16:51:06 +0000 https://www.educationnext.org/?p=49711786 “Substantially widened socioeconomic gaps.”

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As states and districts consider how best to educate students this fall, it is critical to understand how the pandemic-induced school closures affected students’ engagement with online learning resources intended to compensate for lost time in school.

One way to do that is by using high frequency, nationally representative Google search data. These data allow us to document in real time how parents and students sought out online resources as schools closed in response to the Covid-19 pandemic. By comparing changes in online search activity across different geographies, we are able to estimate how Covid-induced demand for online resources varied by a range of geographic and socioeconomic factors, including income, internet access and rurality. The results of these comparisons are striking.

Pre-Covid searches for online learning resources fall largely into two categories, which we call “school-centered resources” and “parent-centered resources.” School-centered resources are platforms typically used by schools to provide instruction, assign work, or communicate with students (such as Google Classroom or Schoology). Parent-centered resources are more generic search terms indicating parents or students are likely seeking supplemental learning resources (such as homeschooling materials or math worksheets). Search intensity for school-centered resources dwarfs that for parent-centered resources. Both follow the school calendar, peaking at the start of each school year and vanishing in the summer.

The onset of Covid disrupted this usual cycle of search intensity, as the pandemic triggered a very large increase in demand for online learning resources. By April 2020, nationwide search intensity for online learning resources had roughly doubled relative to baseline (see Figure 1). Searches for both school- and parent-centered resources spiked, suggesting that increased demand for online support came not only from schools shifting their mode of instruction but also from parents and students seeking additional support as schools closed.

 

 

The pandemic also substantially widened socioeconomic gaps in searches for online learning resources (see Figure 2). Search intensity rose substantially more in areas with above median socioeconomic status (measured by household income, parental education, and computer and internet access) as in areas with below median socioeconomic status. Search intensity for school-centered resources, for example, increased by 15 percent for each additional $10,000 in average household income and by roughly 50 percent for each 10-percentage-point increase in the fraction of households with broadband internet and a computer. Areas with more rural schools and more Black students also saw lower increases in search intensity. Socioeconomic gaps widened both between and within the country’s four Census regions (Northeast, Midwest, South, and West).

 

 

These results reveal a new aspect of the digital divide, namely the extent to which households seek out online learning resources when in-person instruction is unavailable–either prompted by their schools or of their own accord. A large literature documents pre-Covid gaps in access to and proficiency in the use of digital technologies. Multiple post-Covid surveys show socioeconomic gaps in students’ reported engagement with remote learning. We complement this evidence with the first nationally representative measure of such engagement, based on households’ actual behavior rather than teacher or parent reports. The high frequency nature of the data reveals the evolution over time of engagement with online learning resources.

Socioeconomic gaps in engagement with online learning resources are not limited to a single platform or location but are a fundamental feature of the post-Covid landscape. Our findings provide insight into the mechanisms underlying learning losses that are beginning to emerge following this spring’s school closures and can help inform future policy responses to schooling disruptions, whether related to the pandemic or not. That search for school-centered resources increases more in high-income areas suggests either that those areas’ schools are using online platforms more, that those areas’ parents are more likely to engage with such platforms, or both. That search for parent-centered resources increases more in high-income areas suggests that, separate from schools’ actions, parents are differentially likely to seek out their own ways of compensating for their children’s lost learning time.

These results can help policymakers and school leaders formulate more effective responses to the educational disruptions caused by Covid-induced school closures. Students from lower income families and schools may require additional attention and resources given lower engagement with online learning resources during spring 2020. Moreover, because remote learning will remain a central feature of the public education system for the foreseeable future, preventing the widening of achievement gaps may require improving access to home computers and broadband internet for low-income and rural students. Schools may also need to improve the deployment of remote learning platforms to more equitably engage students and parents in the use of those platforms.

Whether efforts to close gaps in online learning engagement succeed will only become clear as new data become available in subsequent school years. One advantage of using publicly available search data to measure household behavior is that our analyses can be easily updated in real time when the school year begins in the fall. This will help reveal whether socioeconomic gaps in engagement with online learning have narrowed since the initial shock of schools closing or if different remote learning strategies across regions were particularly successful.

Household adaptation to schooling shocks is an understudied phenomenon that is readily apparent in internet search data. Understanding and accounting for such behavioral responses by parents and students will be critical to predicting the long-term effects of the pandemic, and, ideally, for preventing those effects from being worse than they would be in the absence of this data.

Andrew Bacher-Hicks is assistant professor of education at Boston University’s Wheelock College of Education and Human Development. Joshua Goodman is associate professor of education and economics at Boston University. Christine Mulhern received her Ph.D. in public policy from Harvard University. Their working paper, “Inequality in Household Adaptation to Schooling Shocks: Covid-Induced Online Learning Engagement in Real Time,” is available here.

Read more from Education Next on coronavirus and Covid-19.

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