[Congressional Bills 118th Congress]
[From the U.S. Government Publishing Office]
[H.R. 1050 Introduced in House (IH)]
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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
California) 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 education, and for other purposes.
Be it enacted by the Senate and House of Representatives 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
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 educational
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 result of
data-driven processes. For example, medications and
other medical interventions are tested in randomized
trials to assess their efficacy and safety. Similarly,
data are often used to inform policy decisions that
have considerable impact on citizens.
(3) Data literacy is increasingly integral in the fields of
science, technology, engineering, and mathematics (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 financial well-being.
(5) Access to high-quality data science and literacy
education is vital for building the United States STEM
workforce and United States competitiveness in the 21st century
in the following ways:
(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 underscores 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 talent 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 operations
researcher roles are among the fastest growing
positions in the United States. However, United States
companies often struggle to fill their data scientist,
statistician, and operations researcher positions, a
situation not expected to change this decade.
(E) The STEM workforce is projected to grow at a
faster pace than the non-STEM workforce; however, some
have expressed concern that the domestic supply of STEM
workers will not meet future workforce needs.
(F) More and earlier access to quality education
that includes data-intense disciplines is necessary to
meet industry demands and competitiveness 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, Alaska Natives, and American Indians.
(H) Such accessibility should also include
community colleges, which are often more accessible to
diverse groups.
(6) 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) diversifying the STEM workforce by bringing
access and support to populations traditionally
underrepresented in STEM fields, including female
students, students of color, and students from
disadvantaged backgrounds. Studies have identified
positive associations between diversity and performance
for companies.
(7) Increased attention to data science and literacy
supports the burgeoning emphasis on evidence-based policymaking
and data-driven decision, including in government as
exemplified by the Foundations for Evidence-Based Policymaking
Act of 2018 (Public Law 115-435).
(8) Effective data science and statistics education at the
pre-kindergarten through postsecondary levels would--
(A) ensure graduates have the skills and knowledge
necessary to compete in the workforce of the 21st
century, with its burgeoning growth of and dependence
on data, and acquire the self-efficacy and motivation
to embrace careers in data science, statistics, and
other STEM fields;
(B) contribute to student learning and problem-
solving skills across multiple disciplines; 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 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.
SEC. 102. APPLICATIONS.
(a) In General.--To be eligible to receive a grant under this
title, 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;
(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.
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 support 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 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.
(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.
(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.
(6) Recruiting and hiring instructional personnel,
including specialists in data science and statistics 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-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 for
underrepresented students;
(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
underrepresented students; and
(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.
(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 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.).
(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 Secretary
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;
(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.
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 represent.
(2) Data science.--The term ``data science'' means the
interdisciplinary use of statistics, mathematics, and computer
science to analyze data and provide tools to interact with
data.
(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 practices of
statistics and data science.
(L) Statistical methods and modeling.
(M) Statistical problem-solving processes.
(4) Eligible consortium.--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.
(5) Eligible entity.--The term ``eligible entity'' means an
eligible State educational agency, eligible local educational
agency, eligible Tribal school, institution of higher
education, or eligible consortium.
(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
Education 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 eligible local educational agencies.
(8) Eligible tribal school.--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)).
(9) ESEA terms.--The terms ``local educational 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 Higher Education Act of 1965 (20
U.S.C. 1001).
(11) Operations research.--The term ``operations research''
means the application of scientific methods to the management
and administration of organized military, governmental,
commercial, and industrial processes to maximize operational
efficiency.
(12) Secretary.--The term ``Secretary'' means the Secretary
of Education.
(13) Statistical problem-solving process.--The term
``statistical problem-solving process'' means a framework for
decisionmaking that includes the following components:
(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 families.
SEC. 106. AUTHORIZATION OF APPROPRIATIONS.
(a) In General.--There is authorized to be appropriated to carry
out this title $10,000,000 for each of fiscal 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 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).
(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).
TITLE II--STATISTICS ON SECONDARY SCHOOL STEM TEACHERS
SEC. 201. AMENDMENTS TO THE EDUCATION SCIENCES REFORM ACT OF 2002.
(a) In General.--Section 153 of the Education Sciences Reform Act
of 2002 (20 U.S.C. 9543) is amended--
(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,
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;''; and
(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 amendments made by this
section shall take effect 1 year after the date of the enactment of
this section.
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