[Congressional Bills 118th Congress]
[From the U.S. Government Publishing Office]
[H.R. 1735 Referred in Senate (RFS)]
<DOC>
118th CONGRESS
2d Session
H. R. 1735
_______________________________________________________________________
IN THE SENATE OF THE UNITED STATES
September 24, 2024
Received; read twice and referred to the Committee on Health,
Education, Labor, and Pensions
_______________________________________________________________________
AN ACT
To coordinate Federal research and development efforts focused on
modernizing mathematics in STEM education through mathematical and
statistical modeling, including data-driven and computational thinking,
problem, project, and performance-based learning and assessment,
interdisciplinary exploration, and career connections, 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.
This Act may be cited as the ``Mathematical and Statistical
Modeling Education Act''.
SEC. 2. MATHEMATICAL AND STATISTICAL MODELING EDUCATION.
(a) Findings.--Congress finds the following:
(1) The mathematics taught in schools, including
statistical problem solving and data science, is not keeping
pace with the rapidly evolving needs of the public and private
sector, resulting in a STEM skills shortage and employers
needing to expend resources to train and upskill employees.
(2) According to the Bureau of Labor Statistics, the United
States will need 1,000,000 additional STEM professionals than
it is on track to produce in the coming decade.
(3) The field of data science, which is relevant in almost
every workplace, relies on the ability to work in teams and use
computational tools to do mathematical and statistical problem
solving.
(4) Many STEM occupations offer higher wages, more
opportunities for advancement, and a higher degree of job
security than non-STEM jobs.
(5) The STEM workforce relies on computational and data-
driven discovery, decision making, and predictions, from models
that often must quantify uncertainty, as in weather
predictions, spread of disease, or financial forecasting.
(6) Most fields, including analytics, science, economics,
publishing, marketing, actuarial science, operations research,
engineering, and medicine, require data savvy, including the
ability to select reliable sources of data, identify and remove
errors in data, recognize and quantify uncertainty in data,
visualize and analyze data, and use data to develop
understanding or make predictions.
(7) Rapidly emerging fields, such as artificial
intelligence, machine learning, quantum computing and quantum
information, all rely on mathematical and statistical concepts,
which are critical to prove under what circumstances an
algorithm or experiment will work and when it will fail.
(8) Military academies have a long tradition in teaching
mathematical modeling and would benefit from the ability to
recruit students with this expertise from their other school
experiences.
(9) Mathematical modeling has been a strong educational
priority globally, especially in China, where participation in
United States mathematical modeling challenges in high school
and higher education is orders of magnitude higher than in the
United States, and Chinese teams are taking a majority of the
prizes.
(10) Girls participate in mathematical modeling challenges
at all levels at similar levels as boys, while in traditional
mathematical competitions girls participate less and drop out
at every stage. Students cite opportunity for teamwork, using
mathematics and statistics in meaningful contexts, ability to
use computation, and emphasis on communication as reasons for
continued participation in modeling challenges.
(b) Definitions.--In this section:
(1) Director.--The term ``Director'' means the Director of
the National Science Foundation.
(2) Federal laboratory.--The term ``Federal laboratory''
has the meaning given such term in section 4 of the Stevenson-
Wydler Technology Innovation Act of 1980 (15 U.S.C. 3703).
(3) Foundation.--The term ``Foundation'' means the National
Science Foundation.
(4) Institution of higher education.--The term
``institution of higher education'' has the meaning given such
term in section 101(a) of the Higher Education Act of 1965 (20
U.S.C. 1001(a)).
(5) Mathematical modeling.--The term ``mathematical
modeling'' has the meaning given the term in the 2019
Guidelines to Assessment and Instruction in Mathematical
Modeling Education (GAIMME) report, 2nd edition.
(6) 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.
(7) Statistical modeling.--The term ``statistical
modeling'' has the meaning given the term in the 2021
Guidelines to Assessment and Instruction in Statistical
Education (GAISE II) report.
(8) Stem.--The term ``STEM'' means the academic and
professional disciplines of science, technology, engineering,
and mathematics, including computer science.
(c) Preparing Educators To Engage Students in Mathematical and
Statistical Modeling.--The Director shall make awards on a merit-
reviewed, competitive basis to institutions of higher education, and
nonprofit organizations (or a consortium thereof) for research and
development to advance innovative approaches to support and sustain
high-quality mathematical modeling education in schools that are
private, faith-based, or homeschools, or operated by local educational
agencies, including statistical modeling, data science, operations
research, and computational thinking. The Director shall encourage
applicants to form partnerships to address critical transitions, such
as middle school to high school, high school to college, and school to
internships and jobs.
(d) Application.--An entity seeking an award under subsection (c)
shall submit an application at such time, in such manner, and
containing such information as the Director may require. The
application shall include the following:
(1) A description of the target population to be served by
the research activity for which such an award is sought,
including student subgroups described in section
1111(b)(2)(B)(xi) of the Elementary and Secondary Education Act
of 1965 (20 U.S.C. 6311(b)(2)(B)(xi)), and students
experiencing homelessness and children and youth in foster
care.
(2) A description of the process for recruitment and
selection of students, educators, or local educational agencies
to participate in such research activity.
(3) A description of how such research activity may inform
efforts to promote the engagement and achievement of students,
including students from groups historically underrepresented in
STEM, in prekindergarten through grade 12 in mathematical
modeling and statistical modeling using problem-based learning
with contextualized data and computational tools.
(4) In the case of a proposal consisting of a partnership
or partnerships with 1 or more local educational agencies and 1
or more researchers, a plan for establishing a sustained
partnership that is jointly developed and managed, draws from
the capacities of each partner, and is mutually beneficial.
(e) Partnerships.--In making awards under subsection (c), the
Director shall encourage applications that include--
(1) partnership with a nonprofit organization or an
institution of higher education that has extensive experience
and expertise in increasing the participation of students in
prekindergarten through grade 12 in mathematical modeling and
statistical modeling;
(2) partnership with a local educational agency, a
consortium of local educational agencies, or Tribal educational
agencies;
(3) an assurance from school leaders to making reforms and
activities proposed by the applicant a priority;
(4) ways to address critical transitions, such as middle
school to high school, high school to college, and school to
internships and jobs;
(5) input from education researchers and cognitive
scientists, as well as practitioners in research and industry,
so that what is being taught is up-to-date in terms of content
and pedagogy;
(6) a communications strategy for early conversations with
parents, school leaders, school boards, community members,
employers, and other stakeholders; and
(7) resources for parents, school leaders, school boards,
community members, and other stakeholders to build skills in
modeling and analytics.
(f) Use of Funds.--An entity that receives an award under this
section shall use the award for research and development activities to
advance innovative approaches to support and sustain high-quality
mathematical modeling education in public schools, private schools
(including faith-based schools), or homeschools, including statistical
modeling, data science, operations research, and computational
thinking, which may include--
(1) engaging prekindergarten through grade 12 educators in
professional learning opportunities to enhance mathematical
modeling and statistical problem solving knowledge, and
developing training and best practices to provide more
interdisciplinary learning opportunities;
(2) conducting research on curricula and teaching practices
that empower students to choose the mathematical, statistical,
computational, and technological tools that they will apply to
a problem, as is required in life and the workplace, rather
than prescribing a particular approach or method;
(3) providing students with opportunities to explore and
analyze real data sets from contexts that are meaningful to the
students, which may include--
(A) missing or incorrect values;
(B) quantities of data that require choice and use
of appropriate technology;
(C) multiple data sets that require choices about
which data are relevant to the current problem; and
(D) data of various types including quantities,
words, and images;
(4) taking a school or district-wide approach to
professional development in mathematical modeling and
statistical modeling;
(5) engaging rural local agencies;
(6) supporting research on effective mathematical modeling
and statistical modeling teaching practices, including problem-
and project-based learning, universal design for accessibility,
and rubrics and mastery-based grading practices to assess
student performance;
(7) designing and developing pre-service and in-service
training resources to assist educators in adopting
transdisciplinary teaching practices within mathematics and
statistics courses;
(8) coordinating with local partners to adapt mathematics
and statistics teaching practices to leverage local natural,
business, industry, and community assets in order to support
community-based learning;
(9) providing hands-on training and research opportunities
for mathematics and statistics educators at Federal
laboratories, institutions of higher education, or in industry;
(10) developing mechanisms for partnerships between
educators and employers to help educators and students make
connections between their mathematics and statistics projects
and topics of relevance in today's world;
(11) designing and implementing professional development
courses and experiences, including mentoring for educators,
that combine face-to-face and online experiences;
(12) reduce gaps in access to learning opportunities for
students from groups historically underrepresented in STEM;
(13) provide support and resources for students from groups
historically underrepresented in STEM;
(14) addressing critical transitions, such as middle school
to high school, high school to college, and school to
internships and jobs;
(15) researching effective approaches for engaging students
from groups historically underrepresented in STEM; and
(16) any other activity the Director determines will
accomplish the goals of this section.
(g) Evaluations.--All proposals for awards under this section shall
include an evaluation plan that includes the use of outcome oriented
measures to assess the impact and efficacy of the award. Each recipient
of an award under this section shall include results from these
evaluative activities in annual and final project reports.
(h) Accountability and Dissemination.--
(1) Evaluation required.--The Director shall evaluate the
portfolio of awards made under this section. Such evaluation
shall--
(A) use a common set of benchmarks and tools to
assess the results of research conducted under such
awards and identify best practices; and
(B) to the extent practicable, integrate the
findings of research resulting from the activities
funded through such awards with the findings of other
research on student's pursuit of degrees or careers in
STEM.
(2) Report on evaluations.--Not later than 180 days after
the completion of the evaluation under paragraph (1), the
Director shall submit to Congress and make widely available to
the public a report that includes--
(A) the results of the evaluation; and
(B) any recommendations for administrative and
legislative action that could optimize the
effectiveness of the awards made under this section.
(i) Funding.--$10,000,000 for each of the fiscal years 2025 through
2029 is authorized to be used by the Directorate for STEM Education of
the National Science Foundation to carry out this section.
SEC. 3. NASEM REPORT ON MATHEMATICAL AND STATISTICAL MODELING EDUCATION
IN PREKINDERGARTEN THROUGH 12TH GRADE.
(a) Study.--Not later than 180 days after the date of the enactment
of this Act, the Director shall seek to enter into an agreement with
the National Academies of Sciences, Engineering and Medicine (in this
section referred to as ``NASEM'') (or if NASEM declines to enter into
such an agreement, another appropriate entity) under which NASEM, or
such other appropriate entity, agrees to conduct a study on the
following:
(1) Factors that enhance or barriers to the implementation
of mathematical modeling and statistical modeling in elementary
and secondary education, including opportunities for and
barriers to use modeling to integrate mathematical and
statistical ideas across the curriculum, including the
following:
(A) Pathways in mathematical modeling and
statistical problem solving from kindergarten to the
workplace so that students are able to identify
opportunities to use their school mathematics and
statistics in a variety of jobs and life situations and
so that employers can benefit from students' school
learning of data science, computational thinking,
mathematics, statistics, and related subjects.
(B) The role of community-based problems, service-
based learning. and internships for connecting students
with career preparatory experiences.
(C) Best practices in problem-, project-,
performance-based learning and assessment.
(2) Characteristics of teacher education programs that
successfully prepare teachers to engage students in
mathematical modeling and statistical modeling, as well as gaps
and suggestions for building capacity in the pre-service and
in-service teacher workforce.
(3) Mechanisms for communication with stakeholders,
including parents, administrators, and the public, to promote
understanding and knowledge of the value of mathematical
modeling and statistical modeling in education.
(b) Public Stakeholder Meeting.--In the course of completing the
study described in subsection (a), NASEM or such other appropriate
entity shall hold not less than one public meeting to obtain
stakeholder input on the topics of such study.
(c) Report.--The agreement under subsection (a) shall require
NASEM, or such other appropriate entity, not later than 24 months after
the effective date of such agreement, to submit to the Secretary of
Education and the appropriate committees of jurisdiction of Congress a
report containing--
(1) the results of the study conducted under subsection
(a);
(2) recommendations to modernize the processes described in
subsection (a)(1); and
(3) recommendations for such legislative and administrative
action as NASEM, or such other appropriate entity, determines
appropriate.
(d) Funding.--From amounts appropriated or otherwise made available
for the Directorate for STEM Education of the National Science
Foundation, the Director shall allocate up to $1,000,000 for fiscal
year 2024 to carry out this section.
SEC. 4. LIMITATIONS.
(a) Limitation on Funding.--Amounts made available to carry out
sections 2 and 3 shall be derived from amounts appropriated or
otherwise made available to the National Science Foundation.
(b) Sunset.--The authority to provide awards under this Act shall
expire on September 30, 2028.
Passed the House of Representatives September 23, 2024.
Attest:
KEVIN F. MCCUMBER,
Clerk.