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That’s according to a new report released on Thursday, June 18, by scholars at Brown and Harvard universities. The study — “Lifting All Boats? Accomplishments and Challenges from 20 Years of Education Reform in Massachusetts” — was led by John Papay, an associate professor of education at Brown, as part of a research-practice partnership between Brown’s Annenberg Institute for School Reform and the Massachusetts Departments of Elementary and Secondary Education and Higher Education.

To examine how the 1993 Massachusetts Education Reform Act has affected outcomes for children in the state, Papay and his colleagues analyzed two decades of state testing data, college admission and graduation records, and labor market earnings. They found that the last two decades have seen college enrollment rates climb across all demographics, including for children of color and children who come from low-income households.

So how do we rebuild the basic education infrastructure? In a recent paper that I coauthored with Susanna Loeb and Alec Kennedy, we examined one program funded through the American Recovery and Reinvestment Act of 2009—School Improvement Grants (SIGs). Starting in 2010, Congress invested a total of approximately $7 billion in five cohorts of SIGs. These funds typically doubled the grantee schools’ regular budget and were available for schools to use for three years. Drawing on data from four locations across the nation, which represent a geographically diverse group of states and local districts, we find that SIG program had substantial success in both short- and longer-term.

The average student could begin the next school year having lost as much as a third of their expected progress from the previous year in reading and half of their expected progress in math, according to a working paper from NWEA, a nonprofit organization, and scholars at Brown University and the University of Virginia.

A separate analysis from researchers at Brown and Harvard looked at how Zearn, an online math program, was used by 800,000 students both before and after schools closed in March. It found that through late April, student progress in math decreased by about half in classrooms located in low-income ZIP codes, by a third in classrooms in middle-income ZIP codes and not at all in classrooms in high-income ZIP codes.

Just about everybody agrees that the school closures resulting from COVID-19 will lead to some student “learning loss” and that the loss will affect students differently depending on their social advantages, the effectiveness of their schools, and their degree of trauma.

Researchers have tried to predict the magnitude of pandemic-related learning loss by making comparisons with what happens when students are out of school in the summer. Recent work by researchers at NWEA, a nonprofit provider of student assessments, estimated that students would end this school year with only about 40 percent to 60 percent of the learning gains they’d see in a typical year.

This study quantifies the relationship between school closure timing and COVID-19 deaths and cases in the general population in all U.S. states. COVID-19 has higher symptomatic infection rates among the elderly, suggesting school closures could be unrelated to transmission. However, predicting daily cumulative COVID-19 deaths by state, earlier school closure is related to fewer deaths per capita and slower growth in deaths per capita. Results are similar for COVID-19 cases per capita.

With the United States suddenly in a recession, school districts will be thinking seriously about reducing their teaching workforces. On average, salaries account for about 80 percent of district spending, so layoffs may be an inevitable step when budgets must be cut.

For many, budget crises and potential layoffs may feel all too familiar. The long and severe 2008 recession led many districts to let teachers go. Even more teachers received a reduction-in-force or RIF notice—an advance warning issued to teachers whose jobs are at risk. Two federally funded district bailouts helped districts rescind many of the RIF notices, but still, one estimate indicated nearly 300,000 school employees lost their jobs.

To encourage the use of common measures, we must begin by identifying the best measures already in wide use. We are pursuing this in several ways. First, we are searching the What Works Clearinghouse to identify the measures most often found in studies catalogued in its large library. Second, we are identifying the measures that are widely used across the close to 2,000 research grants we have funded over the years. Third, we are forming a panel of experts to help identify a set of common metrics defined by grade/subject band (for example, early reading, middle school algebra). Fourth, we are closely following Susanna Loeb's work at EdInstruments.com and looking for other compendia similar to her growing library of metrics. Finally, we will be soliciting input from the field (including your responses to this post) about how to proceed.