The Briefing:
- The Alliance for Learning Innovation, a coalition of more than 150 nonprofits, philanthropies, researchers, and private-sector leaders, released a report on October 15, 2026, calling on Congress and the Trump administration to fund rigorous research into whether AI tools genuinely improve student learning outcomes.
- The Institute of Education Sciences lost about 90% of its workforce after DOGE swept through the Education Department in early 2025, falling from roughly 200 employees to just 31, according to the Hechinger Report. The Education Department's own inspector general found that 97 IES contracts totaling more than $1.1 billion were canceled.
- Stanford's SCALE Initiative reviewed more than 800 academic papers on AI in K-12 education and found only 20 that produced strong causal evidence of learning impact — a finding cited in the ALI report and covered by Education Week.
- In Texas alone, more than 1.4 million English learners — roughly one in four public school students statewide — attend districts that now lack the federal research backbone needed to independently evaluate the AI platforms being marketed to them.
A coalition of more than 150 education nonprofits, researchers, and private-sector leaders is pressing Congress to fund rigorous AI-in-education research at the exact moment the federal agency responsible for that work has been cut to a skeleton crew of just 31 employees, down from roughly 200 before 2025.
That collision of urgency and incapacity is not a coincidence — it is a structural crisis. For the nation's approximately 5 million English learners, the majority of them Latino and concentrated in the school systems of Los Angeles, Houston, and Chicago, AI tools are already arriving in classrooms with no independent validation of whether they actually move the needle on learning.
The Research Collapse, By the Numbers
The Trump administration's first year effectively dismantled the Institute of Education Sciences, eliminating more than $1.1 billion in congressionally mandated research contracts and laying off roughly 90% of the agency's workforce — stripping it of the capacity to carry out its core mission. The Education Department's own inspector general confirmed the scale: 97 IES contracts totaling more than $1.1 billion were canceled, the deepest contract cuts of any office inside the department.
The National Center for Education Statistics — the arm that has collected U.S. education data since 1867 — was particularly devastated, falling from roughly 100 employees to a bare-bones crew of three in the weeks after the March 2025 mass layoffs, according to former department officials. Some rebuilding has occurred: by mid-2026 the center had grown to about 11 staff, though that remains a fraction of what it needs to perform its congressionally mandated functions.
On top of the staffing collapse, IES launched no new research grant competitions for the entirety of fiscal year 2026 — a standstill of more than 15 months — before finally announcing a new set of competitions in August 2026. Meanwhile, the White House Office of Management and Budget has withheld more than half of IES's 2026 budget, blocking funds Congress already appropriated from reaching the agency.
The ripple effects reach every school district in the country. Among the initially canceled IES programs was the What Works Clearinghouse — the nation's primary database of vetted, evidence-based education interventions — a tool that districts across the country relied on before making major curriculum and technology investments. Though the Education Department later announced the contract would be reinstated, the agency still lacks the staff to operate it at full capacity.
The Coalition's Push — and What the Evidence Actually Shows
The Alliance for Learning Innovation released its October 2026 report against that backdrop, citing a finding from Stanford's SCALE Initiative that underscores just how thin the research base actually is: of more than 800 academic papers on AI in K-12 education, only 20 produced strong causal evidence of learning impact. The gap between the volume of AI adoption and the volume of reliable evidence is enormous.
"No state, district, or school should have to answer these questions alone, and the answers shouldn't depend on whether they have the resources to run their own pilots," ALI executive director Sara Schapiro wrote. The report's federal recommendations call on Congress and the administration to build a stronger evidence base for safe and effective AI use, improve AI-enabled tools, and construct the infrastructure needed to accelerate credible research and development across the country.
On the legislative side, ALI and its coalition are pushing Congress to pass the NEED Act, and have called for any federally funded AI study to measure how students perform after they stop using a tool — not just during active use — a standard the American Psychological Association has also endorsed.
What This Means for Latino Students in LA, Houston, and Chicago
Federal data show that K-12 schools with high concentrations of Hispanic students offer fewer STEM courses than schools with lower shares of Latino students — and that only 1 in 10 tech workers today is Latino, a gap rooted in part in unequal access to quality technology education. More than 90% of Latino students attend public schools, making them almost entirely reliant on what federal research and federally funded programs make available to their districts.
The stakes are sharpest for English learners. An IES-funded study at the University of Chicago found that among active English learners entering Chicago high schools, 83% were Latino and spoke Spanish at home — a population that depends on evidence-based bilingual and language-support interventions to stay on track academically. In Houston, Texas's emergent bilingual enrollment has grown to more than 1.4 million students — roughly one in four kids in the state's public and charter schools, according to a 2026 analysis from the nonprofit Every Texan.
AI tools have become especially popular among teachers serving English learners, according to a survey by the RAND Corporation. Student-facing AI can give language learners more individualized practice and immediate feedback. But teachers' reliance on those tools has outpaced any federal guidance addressing bias in AI platforms or the particular needs of English-learning populations.
The Bias Problem Is Already Documented
The documented risks are not theoretical. A Stanford University study found that AI-detection algorithms flag more than 61% of essays written by non-native English speakers as AI-generated — even when those students wrote entirely on their own. Native English speakers' essays, by contrast, were misclassified at a rate of about 5%. The pattern carries direct academic consequences for Latino students in any classroom relying on these tools for academic integrity enforcement.
That caveat carries particular weight for under-resourced districts in cities like Chicago, Houston, and Los Angeles, where large Latino enrollment, constrained budgets, and rapid AI adoption converge — but where the capacity to independently audit AI vendors is essentially nonexistent.
Congress Has Signaled Support. Rebuilding Will Take Years.
Congress has shown some willingness to act. The committee report accompanying the 2026 appropriations bill directs the Education Department to rebuild IES staffing to levels needed to fulfill its statutory responsibilities. Lawmakers from both parties also rejected the administration's proposed two-thirds cut to IES funding earlier this year, keeping the agency's budget at roughly the prior year's level.
But with current IES staffing still at just 31 employees — far below the roughly 200 who were in place before 2025 — meaningful rebuilding will take years. That is time that millions of Latino students enrolling in AI-integrated classrooms right now simply do not have.
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