Data Science and Literacy Act of 2026
- Sponsor
- Rep. Stevens, Haley M. [D-MI-11]
- Committees
- Education and Workforce Committee (primary)
- Last action
- Sep 10, 2026
Bottom line
The Data Science and Literacy Act of 2026 aims to enhance the nation's data literacy and strengthen the STEM workforce by funding educational programs and improving data collection on STEM educators.
What it actually does
This bill establishes a competitive grant program, administered by the Secretary of Education, to increase access to data literacy education for students from pre-kindergarten through postsecondary levels. It authorizes $10 million annually for five fiscal years (2027-2031) for activities such as curriculum development, professional training for educators, and expanding learning materials. Additionally, the bill mandates the collection and reporting of statistics on secondary school STEM teachers, including their subjects, educational backgrounds, and demographics.
Proponents argue
Proponents argue that the bill is crucial for national competitiveness, economic growth, and effective citizenship in an increasingly data-driven world. They highlight the growing demand for data scientists and statisticians, the need to expand the STEM workforce by including underrepresented populations, and the importance of data literacy for informed decision-making and critical evaluation of information, as detailed in the bill's findings.
Opponents contend
Critics might argue that while data literacy is important, establishing a new federal grant program could lead to increased bureaucracy and potential inefficiencies in resource allocation. Some may contend that education initiatives are best handled at the state or local level, or that existing STEM programs could be adapted rather than creating a new, specific data literacy program. Concerns about federal overreach into curriculum development or the effectiveness of competitive grants in achieving widespread impact might also be raised.
The bill is relatively concise and clearly structured, making it accessible for an informed reader to understand its provisions within a reasonable timeframe.
Title I, Sec. 101-106
Data Literacy Education Grant Program Establishment
This title directs the Secretary of Education to award competitive grants to eligible entities, including state and local educational agencies, Tribal schools, institutions of higher education, or consortia. The grants are intended to increase access to data literacy education for students from pre-kindergarten through postsecondary levels, improve data reasoning skills, and serve as models for national data science and data literacy education. Funds can be used for curriculum development, expanding student access to learning support, professional development for educators, and collaborations with regional entities.
Supporters argue
Supporters argue this program directly addresses the critical need for a data-literate populace and a robust STEM workforce. By funding curriculum development and teacher training, it ensures high-quality education, while targeting underrepresented students helps diversify the STEM pipeline and enhance national competitiveness.
Critics contend
Critics might express concern about the efficacy of federal grant programs in driving localized educational improvements, suggesting that a top-down approach may not effectively meet diverse regional needs. They might also argue that the competitive nature could leave out deserving institutions lacking grant-writing resources.
Tradeoffs
The bill balances the goal of national standardization and quality control in data literacy education with the need for local flexibility in implementation. It also navigates the tension between broad accessibility and the competitive nature of grant funding.
Title II, Sec. 201
Statistics on Secondary School STEM Teachers
This title amends the Education Sciences Reform Act of 2002 to require the collection and reporting of statistical data on secondary school STEM teachers in each state. The data will include the subjects taught by these teachers, their educational backgrounds, and their demographics, disaggregated by race, ethnicity, and gender. This data is to be collected and reported not more frequently than once every five years.
Defines "underrepresented student" as "a student from a population that is traditionally underrepresented in STEM fields."
Section 105(16)
Why it matters:Standard legislative practice to define terms, but the lack of explicit enumeration of specific groups leaves room for interpretation or reliance on established federal definitions.
Case for: Supporters argue this provides flexibility for the Secretary of Education and grant recipients to adapt to evolving demographics and data on underrepresentation without needing legislative updates.
Case against: Critics might argue that the lack of explicit enumeration could lead to inconsistent application across different grant recipients or fail to prioritize specific groups most in need without clearer guidance.
Estimated impact: Significant, as it determines which student populations are prioritized for the grant program's efforts to broaden participation.
Stipulates that not more than 15 percent of the funds of a grant made under this title in a fiscal year may be used to purchase equipment to enable the activities described in this section.
Section 103(c)
Why it matters:Standard legislative practice to include limitations on spending categories to ensure funds are primarily used for programmatic activities rather than capital expenditures.
Case for: Proponents argue this ensures that the majority of grant funds are directed towards educational content, professional development, and direct student support, rather than hardware, maximizing the program's core mission.
Case against: Critics might contend that a strict 15% limit could hinder institutions, especially those in underserved areas, from acquiring necessary technology to implement effective data science programs, potentially limiting the quality or reach of their initiatives.
Estimated impact: Limits the capital expenditure component of the $10 million annual appropriation, ensuring at least $8.5 million goes to non-equipment costs.