A BILL 
To coordinate Federal research and development efforts fo-
cused 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. 
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Be it enacted by the Senate and House of Representa-
tives of the United States of America in Congress assembled, 
SECTION 1. SHORT TITLE. 
This Act may be cited as the ‘‘Mathematical and Sta-
tistical Modeling Education Act’’. 
SEC. 2. MATHEMATICAL AND STATISTICAL MODELING EDU-
CATION. 
(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 mathe-
matical and statistical problem solving. 
(4) Many STEM occupations offer higher wages, 
more opportunities for advancement, and a higher de-
gree of job security than non-STEM jobs. 
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(5) The STEM workforce relies on computational 
and data-driven discovery, decision making, and pre-
dictions, from models that often must quantify uncer-
tainty, as in weather predictions, spread of disease, or 
financial forecasting. 
(6) Most fields, including analytics, science, eco-
nomics, publishing, marketing, actuarial science, op-
erations 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 under-
standing 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 experi-
ment 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, 
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where participation in United States mathematical 
modeling challenges in high school and higher edu-
cation is orders of magnitude higher than in the 
United States, and Chinese teams are taking a major-
ity of the prizes. 
(10) Girls participate in mathematical modeling 
challenges at all levels at similar levels as boys, while 
in traditional mathematical competitions girls par-
ticipate less and drop out at every stage. Students cite 
opportunity for teamwork, using mathematics and 
statistics in meaningful contexts, ability to use com-
putation, 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 sec-
tion 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 mean-
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ing 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 In-
struction 
in 
Mathematical 
Modeling 
Education 
(GAIMME) report, 2nd edition. 
(6) OPERATIONS RESEARCH.—The term ‘‘oper-
ations research’’ means the application of scientific 
methods to the management and administration of or-
ganized military, governmental, commercial, and in-
dustrial processes to maximize operational efficiency. 
(7) STATISTICAL MODELING.—The term ‘‘statis-
tical 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 aca-
demic and professional disciplines of science, tech-
nology, engineering, and mathematics, including com-
puter science. 
(c) PREPARING EDUCATORS TO ENGAGE STUDENTS IN 
MATHEMATICAL AND STATISTICAL MODELING.—The Direc-
tor shall make awards on a merit-reviewed, competitive 
basis to institutions of higher education, and nonprofit or-
ganizations (or a consortium thereof) for research and de-
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velopment to advance innovative approaches to support and 
sustain high-quality mathematical modeling education in 
schools that are private, faith-based, or homeschools, or op-
erated by local educational agencies, including statistical 
modeling, data science, operations research, and computa-
tional 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 Di-
rector may require. The application shall include the fol-
lowing: 
(1) A description of the target population to be 
served by the research activity for which such an 
award is sought, including student subgroups de-
scribed 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 home-
lessness and children and youth in foster care. 
(2) A description of the process for recruitment 
and selection of students, educators, or local edu-
cational agencies to participate in such research ac-
tivity. 
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(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 com-
putational tools. 
(4) In the case of a proposal consisting of a part-
nership or partnerships with 1 or more local edu-
cational agencies and 1 or more researchers, a plan 
for establishing a sustained partnership that is joint-
ly developed and managed, draws from the capacities 
of each partner, and is mutually beneficial. 
(e) PARTNERSHIPS.—In making awards under sub-
section (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 participa-
tion 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; 
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(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 cog-
nitive 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 con-
versations with parents, school leaders, school boards, 
community members, employers, and other stake-
holders; 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 de-
velopment 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 mod-
eling, data science, operations research, and computational 
thinking, which may include— 
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(1) engaging prekindergarten through grade 12 
educators in professional learning opportunities to 
enhance mathematical modeling and statistical prob-
lem solving knowledge, and developing training and 
best practices to provide more interdisciplinary learn-
ing opportunities; 
(2) conducting research on curricula and teach-
ing practices that empower students to choose the 
mathematical, statistical, computational, and techno-
logical tools that they will apply to a problem, as is 
required in life and the workplace, rather than pre-
scribing a particular approach or method; 
(3) providing students with opportunities to ex-
plore 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 quan-
tities, words, and images; 
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(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, uni-
versal design for accessibility, and rubrics and mas-
tery-based grading practices to assess student per-
formance; 
(7) designing and developing pre-service and in- 
service training resources to assist educators in adopt-
ing transdisciplinary teaching practices within math-
ematics and statistics courses; 
(8) coordinating with local partners to adapt 
mathematics and statistics teaching practices to lever-
age 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 edu-
cation, or in industry; 
(10) developing mechanisms for partnerships be-
tween educators and employers to help educators and 
students make connections between their mathematics 
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and statistics projects and topics of relevance in to-
day’s world; 
(11) designing and implementing professional 
development courses and experiences, including men-
toring for educators, that combine face-to-face and on-
line experiences; 
(12) reduce gaps in access to learning opportuni-
ties for students from groups historically underrep-
resented in STEM; 
(13) provide support and resources for students 
from groups historically underrepresented in STEM; 
(14) addressing critical transitions, such as mid-
dle school to high school, high school to college, and 
school to internships and jobs; 
(15) researching effective approaches for engag-
ing students from groups historically underrep-
resented 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 projects. 
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(h) ACCOUNTABILITY AND DISSEMINATION.— 
(1) EVALUATION REQUIRED.—The Director shall 
evaluate the portfolio of awards made under this sec-
tion. 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 administra-
tive and legislative action that could optimize 
the effectiveness of the awards made under this 
section. 
(i) FUNDING.—From amounts appropriated or other-
wise made available for the Directorate for STEM Edu-
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cation of the National Science Foundation, the Director 
shall allocate up to $10,000,000 for each of fiscal years 2024 
through 2028 to carry out this section. 
SEC. 3. NASEM REPORT ON MATHEMATICAL AND STATIS-
TICAL MODELING EDUCATION IN PREKINDER-
GARTEN THROUGH 12TH GRADE. 
(a) STUDY.—Not later than 60 days after the date of 
enactment of this Act, the Director shall seek to enter into 
an agreement with the National Academies of Sciences, En-
gineering 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 im-
plementation of mathematical modeling and statis-
tical modeling in elementary and secondary edu-
cation, 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 kinder-
garten to the workplace so that students are able 
to identify opportunities to use their school 
mathematics and statistics in a variety of jobs 
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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 con-
necting students with career preparatory experi-
ences. 
(C) Best practices in problem-, project-, per-
formance-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 stake-
holders, 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. 
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(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 agree-
ment, to submit to the Secretary of Education and the ap-
propriate committees of jurisdiction of Congress a report 
containing— 
(1) the results of the study conducted under sub-
section (a); 
(2) recommendations to modernize the processes 
described in subsection (a)(1); and 
(3) recommendations for such legislative and ad-
ministrative action as NASEM, or such other appro-
priate entity, determines appropriate. 
(d) FUNDING.—From amounts appropriated or other-
wise made available for the Directorate for STEM Edu-
cation 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 avail-
able 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. 
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Union Calendar No. 42 
118TH CONGRESS 
1ST SESSION 
H. R. 1735 
[Report No. 118–62] 
A BILL 
To coordinate Federal research and development ef-
forts focused on modernizing mathematics in 
STEM education through mathematical and sta-
tistical modeling, including data-driven and com-
putational thinking, problem, project, and per-
formance-based learning and assessment, inter-
disciplinary exploration, and career connections, 
and for other purposes. 
MAY 16, 2023 
Reported with an amendment, committed to the Com-
mittee of the Whole House on the State of the Union, 
and ordered to be printed 
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