I 
118TH CONGRESS 
1ST SESSION H. R. 1050 
To direct the Secretary of Education to make grants for the purpose of 
increasing access to data literacy education, and for other purposes. 
IN THE HOUSE OF REPRESENTATIVES 
FEBRUARY 14, 2023 
Ms. STEVENS (for herself, Mr. BAIRD, Mr. BEYER, and Mrs. KIM of Cali-
fornia) introduced the following bill; which was referred to the Committee 
on Education and the Workforce 
A BILL 
To direct the Secretary of Education to make grants for 
the purpose of increasing access to data literacy edu-
cation, and for other purposes. 
Be it enacted by the Senate and House of Representa-
tives of the United States of America in Congress assembled, 
SECTION 1. SHORT TITLE; TABLE OF CONTENTS. 
(a) SHORT TITLE.—This Act may be cited as the 
‘‘Data Science and Literacy Act of 2023’’. 
(b) TABLE OF CONTENTS.—The table of contents for 
this Act is as follows: 
Sec. 1. Short title; table of contents. 
Sec. 2. Findings. 
TITLE I—DATA LITERACY EDUCATION GRANT PROGRAM 
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Sec. 101. Grant program established. 
Sec. 102. Applications. 
Sec. 103. Use of funds. 
Sec. 104. Reporting and evaluation. 
Sec. 105. Definitions. 
Sec. 106. Authorization of appropriations. 
TITLE II—STATISTICS ON SECONDARY SCHOOL STEM TEACHERS 
Sec. 201. Amendments to the Education Sciences Reform Act of 2002. 
SEC. 2. FINDINGS. 
Congress finds the following: 
(1) Data science and literacy are vital for 
United States residents in an era of intense global 
competition and growing reliance on data. 
(2) The American people constantly interact 
with and are affected by data. For example, they— 
(A) regularly consume data, such as edu-
cational data, business data, financial data, 
medical data, sports statistics, and data-based 
claims in news media; 
(B) are included in a variety of data sets, 
such as medical and credit histories, web 
searches, social media activity, and purchase 
histories; and 
(C) interact with products that are the re-
sult of data-driven processes. For example, 
medications and other medical interventions are 
tested in randomized trials to assess their effi-
cacy and safety. Similarly, data are often used 
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to inform policy decisions that have consider-
able impact on citizens. 
(3) Data literacy is increasingly integral in the 
fields of science, technology, engineering, and mathe-
matics (STEM) and other fields. 
(4) Data literacy is essential for both effective 
citizenship and personal well-being. Data literacy is 
an integral skill for understanding data-driven 
claims and making personal decisions in the 21st 
century. This includes the need to— 
(A) contribute to the digital economy as a 
productive member of the workforce; 
(B) interpret and synthesize data displays 
and summaries, such as polls, surveys, and 
study outcomes; and 
(C) critically evaluate claims based on data 
both in consuming news media, advertising, and 
social media and in making personal decisions, 
such as those related to medical care or finan-
cial well-being. 
(5) Access to high-quality data science and lit-
eracy education is vital for building the United 
States STEM workforce and United States competi-
tiveness in the 21st century in the following ways: 
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(A) STEM fields are a well-known driver 
of the United States economy, job growth, and 
competitiveness. A 2022 government report 
from the National Science Foundation under-
scores this point and also notes growing STEM 
competition from around the globe. 
(B) Accessing talent and ideas from across 
the socioeconomic spectrum and from diverse 
geography is critical for building a vibrant 
United States STEM workforce. 
(C) Concerted efforts to cultivate such tal-
ent in the data-driven fields of statistics, data 
science, 
mathematical 
modeling, 
computer 
science, machine learning, artificial intelligence, 
operations research, and analytics are critical to 
United States competitiveness efforts. 
(D) Data scientist, statistician, and oper-
ations researcher roles are among the fastest 
growing positions in the United States. How-
ever, United States companies often struggle to 
fill their data scientist, statistician, and oper-
ations researcher positions, a situation not ex-
pected to change this decade. 
(E) The STEM workforce is projected to 
grow at a faster pace than the non-STEM 
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workforce; however, some have expressed con-
cern that the domestic supply of STEM workers 
will not meet future workforce needs. 
(F) More and earlier access to quality edu-
cation that includes data-intense disciplines is 
necessary to meet industry demands and com-
petitiveness pressures. 
(G) Access to high-quality data literacy 
education with ongoing support is critical as an 
entry point to STEM fields for students from 
populations traditionally underrepresented in 
STEM fields, including Native Hawaiians, Alas-
ka Natives, and American Indians. 
(H) Such accessibility should also include 
community colleges, which are often more ac-
cessible to diverse groups. 
(6) The expanded focus on data science and lit-
eracy 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 ac-
cessing talent across the socioeconomic spec-
trum; and 
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(C) diversifying the STEM workforce by 
bringing access and support to populations tra-
ditionally underrepresented in STEM fields, in-
cluding female students, students of color, and 
students 
from 
disadvantaged 
backgrounds. 
Studies have identified positive associations be-
tween diversity and performance for companies. 
(7) Increased attention to data science and lit-
eracy supports the burgeoning emphasis on evidence- 
based policymaking and data-driven decision, includ-
ing in government as exemplified by the Founda-
tions for Evidence-Based Policymaking Act of 2018 
(Public Law 115–435). 
(8) Effective data science and statistics edu-
cation at the pre-kindergarten through postsec-
ondary levels would— 
(A) ensure graduates have the skills and 
knowledge necessary to compete in the work-
force of the 21st century, with its burgeoning 
growth of and dependence on data, and acquire 
the self-efficacy and motivation to embrace ca-
reers in data science, statistics, and other 
STEM fields; 
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(B) contribute to student learning and 
problem-solving skills across multiple dis-
ciplines; and 
(C) equip students with the knowledge 
needed to be responsible and engaged citizens. 
TITLE I—DATA LITERACY 
EDUCATION GRANT PROGRAM 
SEC. 101. GRANT PROGRAM ESTABLISHED. 
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 edu-
cation 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. 
SEC. 102. APPLICATIONS. 
(a) IN GENERAL.—To be eligible to receive a grant 
under this title, an eligible entity shall submit to the Sec-
retary 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— 
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(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 edu-
cation; 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, oppor-
tunity gaps, and differentiated success for 
underrepresented students; 
(2) for the duration of a grant made to the eli-
gible entity under this title, to continuously assess 
and evaluate project activities funded by such grant; 
and 
(3) to continue project activities after the expi-
ration 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. 
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SEC. 103. USE OF FUNDS. 
(a) IN GENERAL.—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 sup-
port and high-quality learning materials in data 
science and statistics, including online courses and 
interactive learning platforms. 
(3) Creating and implementing plans to— 
(A) increase access to and support for rig-
orous classes in STEM fields; 
(B) use data literacy and statistical think-
ing to increase student interest in STEM fields; 
and 
(C) reduce gaps in access to data science 
and statistics courses for underrepresented stu-
dents. 
(4) Providing— 
(A) evidence-based professional develop-
ment 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. 
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(5) With respect to data literacy education, col-
laborating 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 high-
er education. 
(6) Recruiting and hiring instructional per-
sonnel, including specialists in data science and sta-
tistics pedagogy and curricula. 
(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. 
(b) ADDITIONAL
ALLOWABLE
USES
OF
GRANT 
FUNDS FOR CERTAIN ELIGIBLE ENTITIES.—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-kin-
dergarten through middle school levels to pre-
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transition of students from data science, ana-
lytics, 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. 
(c) LIMITATION.—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. 
SEC. 104. REPORTING AND EVALUATION. 
(a) RECIPIENT REPORTS.—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 ac-
tivities assisted with such funds, disaggregated by— 
(1) race (for Asian and Native Hawaiian or Pa-
cific Islander students using the same race response 
categories as the decennial census of the popu-
lation); 
(2) ethnicity; 
(3) gender; and 
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(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.). 
(b) REPORT BY THE SECRETARY.—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 Sec-
retary pursuant to subsection (a); and 
(2) recommendations for expanding the grant 
program established under this title. 
(c) GRANT PROGRAM EVALUATION.—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, including an analysis 
of the following: 
(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; 
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(B) improving data science and data lit-
eracy 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 statis-
tics educators and specialists. 
(2) The effectiveness of the grants made under 
this title with respect to improving national equi-
table student access to data science and data literacy 
curricula and instruction. 
SEC. 105. DEFINITIONS. 
In this title: 
(1) DATA LITERACY.—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 rep-
resent. 
(2) DATA SCIENCE.—The term ‘‘data science’’ 
means the interdisciplinary use of statistics, mathe-
matics, and computer science to analyze data and 
provide tools to interact with data. 
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(3) DATA
SCIENCE
EDUCATION.—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 prac-
tices of statistics and data science. 
(L) Statistical methods and modeling. 
(M) Statistical problem-solving processes. 
(4) ELIGIBLE CONSORTIUM.—The term ‘‘eligi-
ble consortium’’ means a consortium that— 
(A) includes— 
(i) an eligible State educational agen-
cy; 
(ii) an eligible local educational agen-
cy; 
(iii) an eligible Tribal school; or 
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(iv) an institution of higher education; 
and 
(B) may include a non-profit or for-profit 
organization. 
(5) ELIGIBLE ENTITY.—The term ‘‘eligible enti-
ty’’ means an eligible State educational agency, eligi-
ble local educational agency, eligible Tribal school, 
institution of higher education, or eligible consor-
tium. 
(6) ELIGIBLE LOCAL EDUCATIONAL AGENCY.— 
The term ‘‘eligible local educational agency’’ means 
a local educational agency described in section 
1003(f)(1) of the Elementary and Secondary Edu-
cation Act of 1965 (20 U.S.C. 6303(f)(1)). 
(7) ELIGIBLE STATE EDUCATIONAL AGENCY.— 
The term ‘‘eligible State educational agency’’ means 
a State educational agency that serves 1 or more eli-
gible local educational agencies. 
(8) ELIGIBLE TRIBAL SCHOOL.—The term ‘‘eli-
gible Tribal school’’ means— 
(A) a school operated by the Bureau of In-
dian Education; 
(B) a school operated pursuant to the In-
dian Self-Determination and Education Assist-
ance Act (25 U.S.C. 5301 et seq.); or 
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(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)). 
(9) ESEA TERMS.—The terms ‘‘local edu-
cational agency’’ and ‘‘State educational agency’’ 
have the meanings given such terms in section 8101 
of the Elementary and Secondary Education Act of 
1965 (20 U.S.C. 7801). 
(10) INSTITUTION OF HIGHER EDUCATION.— 
The term ‘‘institution of higher education’’ has the 
meaning given such term in section 101 of the High-
er Education Act of 1965 (20 U.S.C. 1001). 
(11) OPERATIONS RESEARCH.—The term ‘‘op-
erations research’’ means the application of scientific 
methods to the management and administration of 
organized military, governmental, commercial, and 
industrial processes to maximize operational effi-
ciency. 
(12) 
SECRETARY.—The 
term 
‘‘Secretary’’ 
means the Secretary of Education. 
(13) STATISTICAL
PROBLEM-SOLVING
PROC-
ESS.—The term ‘‘statistical problem-solving process’’ 
means a framework for decisionmaking that includes 
the following components: 
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(A) Formulating statistical investigative 
questions. 
(B) Collecting and considering the data. 
(C) Analyzing the data. 
(D) Interpreting the results. 
(14) STATISTICS.—The term ‘‘statistics’’ means 
the science of learning from data and of measuring 
and communicating uncertainty. 
(15) STEM FIELDS.—The term ‘‘STEM fields’’ 
means the fields of science, technology, engineering, 
and mathematics and the fields of statistics and 
computer science. 
(16) 
UNDERREPRESENTED
STUDENT.—The 
term ‘‘underrepresented student’’— 
(A) means a student from a population 
that is traditionally underrepresented in STEM 
fields; and 
(B) includes— 
(i) female students; 
(ii) students of color; and 
(iii) students from low-income fami-
lies. 
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SEC. 106. AUTHORIZATION OF APPROPRIATIONS. 
(a) IN GENERAL.—There is authorized to be appro-
priated to carry out this title $10,000,000 for each of fis-
cal years 2024 through 2028. 
(b) LIMITATIONS.— 
(1) ADMINISTRATIVE
EXPENSES.—Not more 
than 2.5 percent of the funds made available for a 
fiscal year under subsection (a) may be used for ad-
ministrative 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 sec-
tion 104(c). 
(2) PROGRAM EVALUATION.—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). 
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TITLE II—STATISTICS ON SEC-
ONDARY 
SCHOOL 
STEM 
TEACHERS 
SEC. 201. AMENDMENTS TO THE EDUCATION SCIENCES RE-
FORM ACT OF 2002. 
(a) IN GENERAL.—Section 153 of the Education 
Sciences Reform Act of 2002 (20 U.S.C. 9543) is amend-
ed— 
(1) in subsection (a)(1)— 
(A) in subparagraph (N), by striking 
‘‘and’’ at the end; 
(B) in subparagraph (O), by adding ‘‘and’’ 
at the end; and 
(C) by inserting after subparagraph (O) 
the following: 
‘‘(P) the number of science, technology, en-
gineering, and math (STEM) teachers in sec-
ondary 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 teach-
ers, disaggregated by race, ethnicity, and 
gender;’’; and 
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(2) by adding at the end the following: 
‘‘(c) STEM TEACHERS REPORT FREQUENCY.—The 
statistical data described in subsection (a)(1)(P) shall be 
collected and reported not more frequently than once every 
5 years.’’. 
(b) EFFECTIVE DATE.—This section and the amend-
ments made by this section shall take effect 1 year after 
the date of the enactment of this section. 
Æ 
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