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Version 00 · Introduced in House · Sep 10, 2026
Data Science and Literacy Act of 2026
This bill establishes a grant program for data literacy education and requires additional reporting regarding secondary school teachers.
Specifically, the bill directs the Department of Education to award grants to educational agencies, tribal schools, institutions of higher education, or consortia of such entities for programs to increase access to and support for data literacy, data science, and statistics education. The Institute of Education Sciences must evaluate the grant program within five years after the first grant is made to assess its effectiveness in improving access to data science and literacy.
Additionally, the bill requires the National Center for Education Statistics to collect and report information on the number of science, technology, engineering, and math (STEM) teachers in secondary schools in each state.
People & committees
Rep. Stevens, Haley M. [D-MI-11] · D–MI
Legislative record
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Referred to the House Committee on Education and Workforce.
Introduced in House
Introduced in House
Primary sources
Text links open the official source. We also preserved the text version used in the PlainBill explanation below.
Source last updated: Sep 18, 2026. Consult Congress.gov for the current record.
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PlainBill explanation
Based on the full Introduced in House · 2026-09-10 text. This explanation has not received human editorial review. This overview describes the proposal’s major provisions; it does not establish what its real-world effects would be.
The proposal would create competitive grants to help students from pre-kindergarten through college understand and use data. Eligible education agencies, Tribal schools, colleges, and partnerships could apply. It would authorize $10 million annually for fiscal years 2027–2031, but grants would depend on money being appropriated. It would also add collection and reporting of state-by-state information about secondary school science, technology, engineering, and mathematics teachers.
From the amounts appropriated under section 106, the Secretary shall award grants, on a competitive basis, to eligible entities to carry out projects— (1) that increase access to data literacy education for students at the pre-kindergarten through postsecondary levels; (2) that improve data reasoning skills in such students;
The term eligible entity means an eligible State educational agency, eligible local educational agency, eligible Tribal school, institution of higher education, or eligible consortium.
There is authorized to be appropriated to carry out this title $10,000,000 for each of fiscal years 2027 through 2031.
the number of science, technology, engineering, and math (STEM) teachers in secondary schools in each State
The statistical data described in subsection (a)(1)(P) shall be collected and reported not more frequently than once every 5 years.
The bill's findings present data education as important for understanding data-based claims and making personal decisions. They also describe workforce expansion and broader participation as expected benefits; these are Congress's stated findings, not demonstrated results of the proposed program.
Congress finds the following:
Data literacy is an integral skill for understanding data-driven claims and making personal decisions in the 21st century.
The expanded focus on data science and literacy would have several benefits, such as— (A) helping the United States compete in the emerging field of data science and growing discipline of statistics; (B) expanding the STEM workforce by accessing talent across the socioeconomic spectrum; and (C) broadening participation in the STEM workforce by bringing access and support to populations traditionally underrepresented in STEM fields.
The Secretary of Education would administer competitive grants. Funded projects would have to expand access to data education, improve students' data reasoning, serve as national models, and follow the bill's spending rules.
The term Secretary means the Secretary of Education.
From the amounts appropriated under section 106, the Secretary shall award grants, on a competitive basis, to eligible entities to carry out projects— (1) that increase access to data literacy education for students at the pre-kindergarten through postsecondary levels; (2) that improve data reasoning skills in such students; (3) that will serve as models for national data science and data literacy education; and (4) in accordance with section 103.
Eligible applicants would include qualifying state and local education agencies, Tribal schools, higher education institutions, and joint groups called consortia. A consortium would need at least one qualifying education member and could also include nonprofit or for-profit organizations. Local agency eligibility would depend on an existing statutory definition; a state agency would qualify by serving at least one eligible local agency.
The term eligible consortium means a consortium that— (A) includes— (i) an eligible State educational agency; (ii) an eligible local educational agency; (iii) an eligible Tribal school; or (iv) an institution of higher education; and (B) may include a non-profit or for-profit organization.
The term eligible entity means an eligible State educational agency, eligible local educational agency, eligible Tribal school, institution of higher education, or eligible consortium.
The term eligible local educational agency means a local educational agency described in section 1003(f)(1) of the Elementary and Secondary Education Act of 1965 (20 U.S.C. 6303(f)(1)).
The term eligible State educational agency means a State educational agency that serves 1 or more eligible local educational agencies.
Eligible Tribal schools would include Bureau of Indian Education schools, schools operated under the Indian Self-Determination and Education Assistance Act, and tribally controlled schools as defined in another federal law. Higher education institutions would also have to meet a referenced federal definition.
The term eligible Tribal school means— (A) a school operated by the Bureau of Indian Education; (B) a school operated pursuant to the Indian Self-Determination and Education Assistance Act (25 U.S.C. 5301 et seq.); or (C) a tribally controlled school (as such term is defined in section 5212 of the Tribally Controlled Schools Act of 1988 (25 U.S.C. 2511)).
The term institution of higher education has the meaning given such term in section 101 of the Higher Education Act of 1965 (20 U.S.C. 1001).
The program would define data literacy as understanding and communicating claims drawn from data, including their sources and what they represent. Data science would combine statistics, mathematics, and computer science. Covered education subjects would include artificial intelligence, data privacy and security, ethical data use, machine learning, and statistical methods.
The term data literacy means the ability to understand and communicate claims derived from data, including— (A) what data are; (B) where data come from; and (C) what aspects of the world data represent.
The term data science means the interdisciplinary use of statistics, mathematics, and computer science to analyze data and provide tools to interact with data.
The term data science education includes education in any of the following subjects: (A) Analytics. (B) Applied statistics and data science. (C) Artificial intelligence. (D) Data acquisition and management. (E) Data literacy. (F) Data quality and representation. (G) Data security and privacy. (H) Ethical use of data. (I) Machine learning. (J) Operations research. (K) Social impacts and professional practices of statistics and data science. (L) Statistical methods and modeling. (M) Statistical problem-solving processes.
Applicants would have to explain how their projects would expand access to data and statistics education and rigorous science, technology, engineering, and mathematics classes. Plans would also have to address student interest and gaps in enrollment, opportunity, and success for traditionally underrepresented students. For this grant program, those fields would expressly include statistics and computer science.
an eligible entity shall submit to the Secretary an application at such time, in such manner, and containing such information as the Secretary may require
which shall include a description of how the entity plans— (1) to carry out project activities under section 103 for the purposes of— (A) increasing access to and support for data literacy, data science, and statistics education; and (B) expanding access to and support for rigorous classes in STEM fields, including by— (i) using data and statistical literacy to increase student interest in STEM fields; and (ii) reducing enrollment gaps, opportunity gaps, and differentiated success for underrepresented students;
The term STEM fields means the fields of science, technology, engineering, and mathematics and the fields of statistics and computer science.
The term underrepresented student means a student from a population that is traditionally underrepresented in STEM fields.
Grants would last no more than five years. Applications would need plans for continuous project assessment during the grant and for continuing activities afterward, including how long that continuation was planned to last.
(2) for the duration of a grant made to the eligible entity under this title, to continuously assess and evaluate project activities funded by such grant; and (3) to continue project activities after the expiration of the grant (including a statement of the planned duration of such continuation). (b) Duration A grant made under this title shall be for a term of not more than 5 years.
Recipients would have to spend grant money on at least two activities from the bill's general list. Options would include developing curricula and expanding learning support and materials, including online courses and interactive platforms.
An eligible entity that receives a grant under this title shall use the grant funds for not fewer than 2 of the following activities: (1) Developing curricula in data literacy, data science, and statistics. (2) Expanding student access to learning support and high-quality learning materials in data science and statistics, including online courses and interactive learning platforms.
Another permitted activity would be creating and carrying out plans to expand access to rigorous classes, build student interest through data literacy, and reduce gaps in access to data science and statistics courses for underrepresented students.
(3) Creating and implementing plans to— (A) increase access to and support for rigorous classes in STEM fields; (B) use data literacy and statistical thinking to increase student interest in STEM fields; and (C) reduce gaps in access to data science and statistics courses for underrepresented students.
Grants could support evidence-based professional development for data science and statistics educators or training for educators moving from other subjects. They could also pay to recruit and hire instructional staff, including specialists in teaching methods and curricula.
(4) Providing— (A) evidence-based professional development for data science and statistics educators and specialists; or (B) evidence-based training for educators and specialists transitioning from other subjects to data science and statistics.
(6) Recruiting and hiring instructional personnel, including specialists in data science and statistics pedagogy and curricula.
Other permitted activities would include regional collaboration with industry, nonprofits, out-of-school education providers, or two- or four-year colleges; preparing to continue projects after grants end; and sharing effective educational practices.
(5) With respect to data literacy education, collaborating with 1 or more of the following regional entities: (A) Industry. (B) A nonprofit organization. (C) An out-of-school education provider. (D) A two- or four-year institution of higher education.
(7) Preparing to continue project activities after the end of the grant period. (8) Disseminating information about effective practices in data science and statistics education.
Recipients that are not higher education institutions could additionally support data education from pre-kindergarten through middle school, prepare teachers to teach data understanding and problem-solving, and provide resources to broaden participation.
In addition to the activities described in subsection (a)— (1) in the case of an eligible entity that is not an institution of higher education, such entity may use the grant funds to— (A) increase access to and support for data literacy education for students at the pre-kindergarten through middle school levels to prepare such students for data literacy education at the high school level; (B) prepare and support teachers to teach students to— (i) understand data; and (ii) use computational, analytical, and statistical thinking to solve problems; and (C) provide support and resources to broaden participation in data science and statistics education;
Higher education institutions and eligible consortia that include them could additionally provide financial support and mentoring to broaden participation in data science and statistics education.
(2) in the case of an eligible entity that is an institution of higher education (or an eligible consortium that includes such an institution), such entity may use the grant funds to provide financial support and mentorship to broaden participation in data science and statistics education;
Two-year colleges and eligible consortia that include them could additionally assess local job opportunities, form industry partnerships, and update curricula. They could also develop programs and transfer agreements to help students move into relevant bachelor's degree programs or local employment.
(3) in the case of an eligible entity that is a two-year institution of higher education (or an eligible consortium that includes such an institution), such entity may use the grant funds to: (A) Assess relevant local employment opportunities for students in data science, analytics, and statistics. (B) Establish industry partnerships. (C) Maintain up-to-date curricula. (D) Develop programs, partnerships, and articulation agreements to facilitate the timely transition of students from data science, analytics, and statistics programs at the institution to— (i) bachelor’s degree programs in data science, analytics, statistics, or related fields; or (ii) relevant local employment.
Equipment purchases supporting the authorized activities could use no more than 15 percent of a grant's funds in a fiscal year.
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.
Recipients would report to the Secretary at least twice each year throughout their grants. Reports would describe spending and students served, with student data broken down by race, ethnicity, gender, and eligibility for free or reduced-price school lunch. Race reporting for Asian and Native Hawaiian or Pacific Islander students would use the decennial census response categories.
Not less frequently than twice each year for the duration of a grant made under this title, an eligible entity that receives such a grant shall submit to the Secretary a report on the use of grant funds, including data on the students served through project activities assisted with such funds, disaggregated by— (1) race (for Asian and Native Hawaiian or Pacific Islander students using the same race response categories as the decennial census of the population); (2) ethnicity; (3) gender; and (4) eligibility to receive a free or reduced price lunch under the Richard B. Russell National School Lunch Act (42 U.S.C. 1751 et seq.).
Within five years after the first grant, the Secretary would have to send Congress and publish a report analyzing recipient reports and recommending ways to expand the program.
Not later than 5 years after the date on which the first grant is made under this title, the Secretary shall submit to Congress and make publicly available a report that includes— (1) an analysis of reports received by the Secretary pursuant to subsection (a); and (2) recommendations for expanding the grant program established under this title.
Within the same five-year period after the first grant, the Secretary, acting through the Institute of Education Sciences director, would have to conduct and publish an effectiveness evaluation. It would examine access to instruction, student skills, educator recruitment and retention, and equitable student access nationwide.
Not later than 5 years after the date on which the first grant is made under this title, the Secretary, acting through the Director of the Institute of Education Sciences, shall carry out and make publicly available an evaluation of the effectiveness of the grants made under this title
(1) With respect to a project assisted with a grant made under this title, the effectiveness of such project with respect to— (A) improving access to data science and data literacy curricula and instruction; (B) improving data science and data literacy skills in students at the pre-kindergarten through postsecondary levels; and (C) assisting eligible entities that receive grants under this title in recruiting, preparing, and retaining qualified data science and statistics educators and specialists. (2) The effectiveness of the grants made under this title with respect to improving national equitable student access to data science and data literacy curricula and instruction.
The bill would authorize Congress to provide $10 million for the grant title in each fiscal year from 2027 through 2031. This authorization would not itself supply the money; grant awards would draw on amounts actually appropriated.
There is authorized to be appropriated to carry out this title $10,000,000 for each of fiscal years 2027 through 2031.
From the amounts appropriated under section 106, the Secretary shall award grants, on a competitive basis, to eligible entities
Of the program funds made available each fiscal year, no more than 2.5 percent could cover the Secretary's grant administration, including technical assistance and distribution of the report and evaluation. No more than 1 percent could fund the required program evaluation.
Not more than 2.5 percent of the funds made available for a fiscal year under subsection (a) may be used for administrative expenses of the Secretary associated with grants made under this title, including— (A) technical assistance; and (B) the dissemination of— (i) the report required under section 104(b); and (ii) the evaluation required under section 104(c).
Not more than 1 percent of the funds made available for a fiscal year under subsection (a) may be used to carry out the evaluation required under section 104(c).
Section 201 would amend the Education Sciences Reform Act of 2002 to add statistics on secondary school science, technology, engineering, and mathematics teachers in each state. The information would include teacher numbers, subjects taught, educational backgrounds, and demographics broken down by race, ethnicity, and gender.
Section 153 of the Education Sciences Reform Act of 2002 (20 U.S.C. 9543) is amended
(P) the number of science, technology, engineering, and math (STEM) teachers in secondary schools in each State, including— (i) the subjects taught by such teachers; (ii) the educational backgrounds of such teachers; and (iii) the demographics of such teachers, disaggregated by race, ethnicity, and gender;
The teacher statistics would have to be collected and reported no more frequently than once every five years. That language limits frequency rather than requiring a report at least every five years. Section 201 and its amendments would take effect one year after that section's enactment.
The statistical data described in subsection (a)(1)(P) shall be collected and reported not more frequently than once every 5 years.
This section and the amendments made by this section shall take effect 1 year after the date of the enactment of this section.
The supplied official-actions snapshot, updated September 18, 2026, records introduction in the House and referral to the House Committee on Education and Workforce on September 10, 2026.
Source snapshot updated 2026-09-18T18:27:56Z. 2026-09-10: Referred to the House Committee on Education and Workforce. 2026-09-10: Introduced in House
A closer look
Reviewed version: Introduced in House · 2026-09-10. These findings describe provisions and who may benefit; they are not judgments of waste, corruption, or motive.
This review covers the supplied bill text. “None identified” does not rule out provisions in later versions or accompanying reports and disclosures.
Provisions outside the bill’s main subject, or policy changes attached to appropriations.
None identified in the reviewed text
No unrelated provision or policy rider attached to appropriations was identified in the complete supplied introduced text. This conclusion applies only to that version and does not establish what appears in other versions or accompanying materials.
Spending directed to particular recipients or places outside ordinary competitive or formula-based allocation.
None identified in the reviewed text
No congressionally directed spending for a particular recipient or place was identified in the complete supplied introduced text. This conclusion is limited to that version; formal earmark status cannot be established for absent accompanying materials.
Narrow exceptions, exemptions, or preferential treatment that warrant a closer look.
None identified in the reviewed text
No materially narrow carve-out, special exemption, or preferential treatment warranting a finding was identified in the complete supplied introduced text. Program eligibility, participation support, and institution-specific permitted activities were treated as ordinary program design. This conclusion does not extend to other versions or accompanying materials.
Full text preserved for this analysis. Legislative record snapshot: Sep 18, 2026. How PlainBill uses AI