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Kids’ test scores began declining way before COVID. These schools are making gains
The pandemic-era backslide in math and reading scores for students across the U.S. was not a sudden catastrophe but the continuation of a brutal, decade-long “learning recession” that began years before COVID-19’s arrival. That’s according to the latest Education Scorecard, an annual deep-dive into student data from The Educational Opportunity Project at Stanford University and Harvard University’s Center for Education Policy Research.
The new Scorecard, released Wednesday and in its fourth year, offers several revelations for families, educators and policymakers looking for clarity — and hope — at a time when public education has been blamed and battered for those persistent declines in student performance.
Among the report’s takeaways: Most states are finally making gains in math; federal relief dollars likely helped the lowest-income districts mount a hearty comeback; and, while most states have yet to make gains in reading, those that have all made legislative changes to how it’s taught in their schools.
Before we dive in, one caveat: The annual Education Scorecard includes data from the vast majority of states and Washington D.C. drawn from their own state tests — as opposed to the Nation’s Report Card. But some states were excluded for various reasons, including if their state assessments had changed recently (Illinois, Kansas), if test opt-out rates were too high (New York, Colorado) or if a state didn’t publish district-level data with enough detail.
‘The learning recession’
For nearly a quarter-century, from 1990 to 2013, math achievement among fourth- and eighth-graders “rose steadily,” according to the Scorecard’s analysis. So steadily that “the average fourth grader in 2013 could perform the same math skills as the average sixth grader could in 1990. That’s enormous progress,” says Stanford University’s Sean Reardon, one of the Scorecard’s authors.
Reading gains weren’t quite as eye-popping, but they were gains nonetheless.
These sustained gains “may be one of the most important social policy successes of the last half-century that nobody knows about,” says Harvard’s Thomas Kane, one of the Scorecard’s authors. “Racial gaps were narrowing too. We just need to get back on that track.“
In short, much was right with America’s schools, which makes the decline that began around 2013 “appear more striking and anomalous,” the report says.
“Particularly in reading, test scores were going down for four to six years before the pandemic,” says Reardon. “In fact, you wouldn’t really know there was a pandemic effect if you just looked at the last 10 or 12 years of test scores. There’s been just a steady kind of decline regardless of the pandemic.”
What might have triggered that decline?
The Scorecard’s trigger theories
Scorecard researchers offer two possible explanations for the beginning of schools’ learning recession:
1. The fade-out of test-based accountability: Remember the much-maligned federal education law, No Child Left Behind (NCLB), that took a tough-love approach with schools to improve student performance? The law, implemented in 2003, threatened a host of sanctions, including school closure, if student test scores didn’t rise, but its standards were seen by many to be not just unrealistic but unattainable. By 2013, the Obama administration began issuing waivers to free states from the law’s consequences. According to the Scorecard, 38 states were granted relief in the 2012-13 school year. Eventually, Congress replaced NCLB with a new federal law that de-emphasized test-based accountability.
Around 2013, Kane says, “school districts learned that nobody was looking over their shoulders in terms of student achievement.“
While the Scorecard researchers don’t draw a direct, causal connection between the declines of test-based accountability and student scores, it’s clear that the nation’s learning recession began at roughly the same time states and schools stepped back from the punishing consequences of NCLB.
2. Students’ social media use: It turns out, 2013 also marks a period of explosive growth in teenagers use of social media. A Pew Research study found that in 2014-15, roughly 1 in 4 teens said they used the internet “almost constantly.” By 2022, it was nearly half of teens.
The researchers also point to international testing data that shows that lower-achieving students are the heaviest users of social media. Students who spend more time (7+ hours per day) on social media score below students who spend less (1-3 hours). And this gap, between the highest and lowest performers, began growing before the pandemic, not just in the U.S. but in many other countries too.
The end of the learning recession?
The Scorecard devotes considerable analysis to what’s been happening in schools since the end of the pandemic, from 2022 through the spring of 2025. There are signs that the nation’s learning recession may be turning around, albeit slowly.
In that span of time, most of the states covered by this year’s Scorecard showed students making meaningful improvement in math, with Washington D.C. coming in as the clear winner there. Only five states failed to make gains in math: Georgia, Idaho, Wyoming, Nebraska and Iowa.
Reading, though, remains a cause for concern. While D.C., Louisiana, Maryland and five other states did experience meaningful improvement between 2022 and 2025, most states continued to stagnate or, as in Florida, Arizona and Nebraska, further declined.
It’s also worth noting, while schools are once again, on average, regaining ground in math and slowly turning the corner in reading, the declines that began around 2013 have been so steep and lasting that only one state, Louisiana, has returned to 2019 performance levels in both subjects.
No state has returned to 2013 levels, according to Reardon.
“It’s easy to be sort of doom and gloom,” he adds, “but when you look at the period from the ’90s through 2013, we made enormous gains. And we actually narrowed achievement gaps between racial groups. That says we can actually improve our schools in ways that also improve equality of opportunity. We just haven’t been doing it for the last decade. But we could do it again.”
The U-shaped recovery
The Scorecard reveals a fascinating phenomenon in schools from 2022 to 2025: a U-shaped recovery. Meaning, schools with the least amount of poverty, alongside schools with the most poverty, saw similar gains in math and similarly small losses in reading achievement. That’s while the schools in the middle of the income spectrum, at the bottom of this U, improved the least in both subjects.
Why? One theory is that the highest-poverty districts got the most help from Congress in the form of federal COVID relief dollars — money they could spend on interventions such as tutoring and summer school. Districts with the lowest poverty rates got little help from the federal government but were already well-positioned financially. It was the middle-income districts that needed more help but didn’t qualify for full federal support.
“If it hadn’t been for the federal pandemic relief,” says Kane, “we estimate there would have been no recovery on average for the highest-poverty districts.”
The science of reading effect
There’s been an important wild card in the effort to improve students’ reading skills: A movement among states to change their approach to teaching reading to young children by embracing the “science of reading.” As of March, the Scorecard says, most states had passed new literacy laws, including doubling down on the importance of teaching phonics.
The Scorecard authors note that all seven of the states (plus D.C.) that saw reading gains between 2022 and 2025 had put comprehensive science of reading reforms into place. Of the states that had not by January 2024, none saw improvement. The connection between these reforms and improved results isn’t necessarily causal, they warn, but there’s clearly a link.
With most states struggling to make reading gains, one district-level success story highlighted by the Scorecard stands out: Baltimore City Public Schools. In spite of the challenges posed by poverty — most students there qualify for free or reduced-price meals — Baltimore students have been making striking reading gains.
Under CEO Sonja Brookins Santelises, the district reformed its approach to literacy. It embraced the science of reading even before the pandemic and years ahead of the national wave of state-based literacy legislation.
When Brookins Santelises took the lead in Baltimore in 2016, she says she quickly embraced the science of reading districtwide and its emphasis on phonics, as opposed to the whole language approach, which teaches children to guess at words using cues from a text’s pictures.
“I remember gathering the [district’s] literacy department. And I said, ‘If you want to do whole language, there are other districts in Maryland that are doing whole language, and you are free to go there. We are not doing that in Baltimore City. I respect you, but you cannot stay here. I’ve been ferocious about it ever since.”
‘Kiss your brains!’
The benefits of these changes appear to have been twofold. During the pandemic, the Scorecard shows Baltimore schools lost far less ground in reading than schools with similar levels of poverty. Then, in 2022, with those practices firmly in place, the city’s reading scores began to skyrocket, erasing pandemic-era losses and rising back around 2017 levels.
Baltimore’s successful approach to teaching literacy was on full display on a recent May morning, in veteran teacher Kimberly Lowery’s kindergarten class at Johnston Square Elementary. Lowery sat at the front of a rainbow-colored reading rug, running through a series of phonics-based games that her kindergarteners seemed to genuinely enjoy.
There was letter-sound bingo, guess-the-sound flashcards and even a visit from a special spelling helper — a toy owl, named Echo, who lives at the end of a yardstick. If the kids’ laughter and cheering isn’t sign enough that they’re learning, district data shows that, by the end of last year, three-quarters of Lowery’s students were reading at or above grade level.
Lowery told the children to kiss their brains and asked, “You guys are super-duper what?”
In unison, the children hollered, “Smart!”
“Yes you are,” Lowery answered.
Edited by: Nirvi Shah and Steve Drummond
Visual design and development by: LA Johnson
The U.S. Supreme Court
Tasos Katopodis/Getty Images
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Tasos Katopodis/Getty Images
The Supreme Court on Tuesday cleared the way for Alabama to use a congressional district map favored by Republicans.
The court, in an unsigned order, overturned a three-judge district court panel that found that the map is “tainted by intentional race-based discrimination.” The court’s three liberals publicly dissented.
The ruling means that Alabama’s 2026 midterm elections will feature six Republican-leaning districts and one Democratic-leaning one, as opposed to a map with only five safe Republican seats. Democrat Shomari Figures, who represents Alabama’s Second District, will likely lose his seat as a result of the high court’s ruling.
The story of Alabama’s congressional map is long and tortured. It began in 2021, when the state implemented a new map to account for population changes in the census. The map featured only one majority-black district out of seven, even though the state is more than one-quarter Black.
Voters immediately sued, claiming the map illegally diluted minority votes in violation of the Voting Rights Act and the Constitution. Lower court judges agreed, ruling that the state must draw a map with two districts where Black voters have a realistic chance of electing their candidate of choice. The Supreme Court more than once has ordered Alabama to draw a compliant map.
But the state has refused and instead continued to litigate the case. On Tuesday, that tactic paid off.
What changed? In April, the Supreme Court’s conservative supermajority all but gutted what remains of the Voting Rights Act, ruling that states cannot purposefully draw districts that are majority-minority.
Alabama then asked the high court to reinstate the state’s old map, under the theory that this new ruling meant that it was permissible to use a map with only one majority-Black district. In an unsigned, unexplained order in May, the high court essentially reversed its previous opinions, and allowed Alabama to use the old map for the upcoming midterm elections.
This set off a flurry of activity in Alabama. By the time the Supreme Court issued its May order, absentee balloting had already begun, using the court-drawn map. So Republican Governor Kay Ivey cancelled elections and scheduled a special primary for August for the affected congressional races.
The case, however, was not over.
In its ruling, the Supreme Court had ordered a lower court panel to continue evaluating Alabama’s map in light of its recent Voting Rights Act decision. And just 15 days after that order, the panel, composed of three Republican judges—two of them Trump appointees—concluded unanimously that even under the Supreme Court’s new standards, the plan for a single black district was “intentionally discriminatory.”
So, once again, Alabama returned to the Supreme Court, arguing that the map was partisan, not racially discriminatory. In short, that the Republican legislature simply drew the map to elect more Republicans. And that under the Supreme Court’s new interpretation of the Voting Rights Act, the GOP map should be allowed to stand.
The court’s conservative agreed, writing that the lower court “did not heed the presumption of legislative good faith.”
The court’s three liberals publicly dissented, castigating the conservative majority for failing to abide by its 2006 decision in the case of Purcell v. Gonzalez. That decision declared that courts should not change election rules too close to an election.
Justice Sonia Sotomayor, in her dissent, said the court “debases the democratic process” and “corrodes the rule of law by rewarding Alabama’s gamesmanship and outright defiance of court orders.”
Tuesday’s decision is the latest in a series of Supreme Court rulings that could well reshape the 2026 midterm elections, making it much harder for Democrats to prevail.
Note: Map shows the area with a shake intensity of 3 or greater, which U.S.G.S. defines as “weak,” though the earthquake may be felt outside the areas shown. The New York Times
A minor, 3.7-magnitude earthquake struck in the San Francisco Bay Area on Tuesday, according to the United States Geological Survey.
The temblor happened at 9:44 a.m. Pacific time about 4 miles southeast of Cloverdale, Calif., data from the agency shows.
U.S.G.S. data earlier reported that the magnitude was 3.6.
As seismologists review available data, they may revise the earthquake’s reported magnitude. Additional information collected about the earthquake may also prompt U.S.G.S. scientists to update the shake-severity map.
Subsequent quakes have been reported in the same area. Such temblors are typically aftershocks caused by minor adjustments along the portion of a fault that slipped at the time of the initial earthquake.
Aftershocks detected
Quakes and aftershocks within 100 miles
Aftershocks can occur days, weeks or even years after the first earthquake. These events can be of equal or larger magnitude to the initial earthquake, and they can continue to affect already damaged locations.
The New York Times When quakes and aftershocks occurred
Sources: United States Geological Survey (epicenter, aftershocks, shake intensity); LandScan via Oak Ridge National Laboratory (population density) | Notes: Shaking categories are based on the Modified Mercalli Intensity scale. When aftershock data is available, the corresponding maps and charts include earthquakes within 100 miles and seven days of the initial quake. All times above are Pacific time. Shake data is as of Tuesday, June 2 at 12:59 p.m. Eastern. Aftershocks data is as of Tuesday, June 2 at 1:59 p.m. Eastern.
By the authority vested in me as President by the Constitution and the laws of the United States of America, it is hereby ordered:
Section 1. Purpose. The United States continues to lead the world in Artificial Intelligence (AI) because of the enormous talent and innovation of our AI industry, and because we refuse to stifle this innovation with overly burdensome regulation. My Administration has unleashed tremendous technological growth and economic investment in AI by slashing the bureaucratic constraints that the prior administration placed on America’s AI developers and researchers, and by instead encouraging AI innovation and accelerating responsible AI adoption across government and industry.
Advanced AI capabilities make our Nation stronger, but also introduce new national security considerations that require coordinated action across executive departments and agencies (agencies), and components. As these capabilities evolve, my Administration will continue to work closely with industry to ensure that the best and most secure technology is deployed rapidly to confront any and all threats to our country. We will continue to lead an America First cybersecurity effort that enhances both our national security and our global AI dominance.
It is the policy of the United States to promote AI innovation and security by working collaboratively with the private sector to modernize government and private sector information systems and harden them against external threats; to protect American ingenuity and intellectual property from exploitation and theft by adversaries; and to cultivate America’s advanced AI-enabled capabilities.
Sec. 2. Upgrading American Systems for Advanced AI. (a) Within 30 days of the date of this order, the Committee on National Security Systems shall prioritize the cyber defense of National Security Systems, as defined in 44 U.S.C. 3552(b)(6)(A), by taking appropriate and expeditious action consistent with the purpose of this order.
(b) Within 30 days of the date of this order, the Secretary of War shall prioritize the cyber defense of Department of War information systems by taking appropriate and expeditious action consistent with the purpose of this order.
(c) Within 30 days of the date of this order, the Secretary of Homeland Security, through the Director of the Cybersecurity and Infrastructure Security Agency (CISA), in consultation with the Director of the Office of Management and Budget (OMB), the Assistant to the President for National Security Affairs, and the National Cyber Director, shall release Binding Operational Directives and other guidance as appropriate to:
(i) expedite and prioritize the cyber defense of civilian Federal Government information systems in order to protect our Nation’s vital functions;
(ii) establish or expand Federal programs and cybersecurity services that enhance AI-enabled defensive tools; and
(iii) facilitate access to cybersecurity tools and services including, where appropriate, covered frontier models for agencies, State and local authorities, and operators of critical infrastructure such as rural hospitals, community banks, and local utilities.
(d) Within 30 days of the date of this order, the Secretary of the Treasury, in consultation with the National Cyber Director, the Secretary of War, through the Director of the National Security Agency (NSA), and the Secretary of Homeland Security, through the Director of CISA, shall form an AI cybersecurity clearinghouse, in voluntary collaboration with the AI industry and operators of critical infrastructure, that coordinates and deconflicts scanning for software vulnerabilities, discovers and validates such vulnerabilities, and coordinates and prioritizes remediation and distribution of vulnerability patches.
(e) Within 30 days of the date of this order, the Director of OMB, in coordination with the National Cyber Director and the Director of CISA, shall determine whether any Federal grant programs have available and relevant funding that can be directed toward applicants developing advanced AI vulnerability detection.
(f) Within 60 days of the date of this order, the Director of the Office of Personnel Management shall expand the United States Tech Force Information Cybersecurity Specialist hiring and placement pathways.
Sec. 3. Secure Frontier Model Deployment. Within 60 days of the date of this order, the Secretary of the Treasury, the Secretary of War, through the Director of NSA, and the Secretary of Homeland Security, through the Director of CISA, in consultation with the White House Chief of Staff, through the National Cyber Director, the Assistant to the President for Science and Technology (APST), and the Secretary of Commerce, through the Director of the National Institute of Standards and Technology, and in coordination with other agencies, as appropriate, shall:
(a) develop and maintain a classified benchmarking process to assess the advanced cyber capabilities of AI models and determine the threshold at which an AI model should be designated a “covered frontier model” for the purposes of this order, sharing such assessments with AI developers and researchers as appropriate. Such a determination shall be made by the Director of NSA, in consultation with the National Cyber Director, the APST, the Director of CISA, and other representatives of the Department of War, as appropriate.
(b) design a voluntary framework with AI developers through which developers would be able to:
(i) engage the Federal Government to determine whether model(s) under development meet the designation of “covered frontier model”;
(ii) provide the Federal Government with access to covered frontier models, subject to appropriate confidentiality, cybersecurity, insider-risk, and intellectual-property protection, use, and nondisclosure requirements, for a period of up to 30 days before they plan to release such models to other trusted partners; and
(iii) collaborate with the Federal Government to select trusted partners that will have early access to covered frontier models to promote secure innovation and strengthen the cybersecurity of critical infrastructure.
(c) Nothing in this section shall be construed to authorize the creation of a mandatory governmental licensing, preclearance, or permitting requirement for the development, publication, release, or distribution of new AI models, including frontier models.
Sec. 4. Protection Against Criminal Actors. The Attorney General shall prioritize the enforcement of 18 U.S.C. 1028, 18 U.S.C. 1030, 18 U.S.C. 1343, and all other applicable Federal criminal laws against anyone who utilizes AI to illegally access or damage a computer without authorization, or who utilizes AI while engaged in such illegal access to further any other crime. This includes breaching any public or private information technology system, or employing AI agents to unlawfully access data or information that is subsequently used for a criminal or unlawful purpose.
Sec. 5. General Provisions. (a) Nothing in this order shall be construed to impair or otherwise affect:
(i) the authority granted by law to an executive department or agency, or the head thereof; or
(ii) the functions of the Director of the Office of Management and Budget relating to budgetary, administrative, or legislative proposals.
(b) This order shall be implemented consistent with applicable law and subject to the availability of appropriations.
(c) This order is not intended to, and does not, create any right or benefit, substantive or procedural, enforceable at law or in equity by any party against the United States, its departments, agencies, or entities, its officers, employees, or agents, or any other person.
(d) The costs for publication of this order shall be borne by the Department of War.
DONALD J. TRUMP
THE WHITE HOUSE,
June 2, 2026.
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