119THCONGRESS
1
STSESSION H. R. 730
AN ACT
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. 2
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Be it enacted by the Senate and House of Representa-1
tives of the United States of America in Congress assembled, 2
SECTION 1. SHORT TITLE. 3
This Act may be cited as the ‘‘Mathematical and Sta-4
tistical Modeling Education Act’’. 5
SEC. 2. MATHEMATICAL AND STATISTICAL MODELING EDU-6
CATION. 7
(a) F
INDINGS.—Congress finds the following: 8
(1) The mathematics taught in schools, includ-9
ing statistical problem solving and data science, is 10
not keeping pace with the rapidly evolving needs of 11
the public and private sector, resulting in a STEM 12
skills shortage and employers needing to expend re-13
sources to train and upskill employees. 14
(2) According to the Bureau of Labor Statis-15
tics, the United States will need 1,000,000 addi-16
tional STEM professionals than it is on track to 17
produce in the coming decade. 18
(3) The field of data science, which is relevant 19
in almost every workplace, relies on the ability to 20
work in teams and use computational tools to do 21
mathematical and statistical problem solving. 22
(4) Many STEM occupations offer higher 23
wages, more opportunities for advancement, and a 24
higher degree of job security than non-STEM jobs. 25 3
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(5) The STEM workforce relies on computa-1
tional and data-driven discovery, decision making, 2
and predictions, from models that often must quan-3
tify uncertainty, as in weather predictions, spread of 4
disease, or financial forecasting. 5
(6) Most fields, including analytics, science, eco-6
nomics, publishing, marketing, actuarial science, op-7
erations research, engineering, and medicine, require 8
data savvy, including the ability to select reliable 9
sources of data, identify and remove errors in data, 10
recognize and quantify uncertainty in data, visualize 11
and analyze data, and use data to develop under-12
standing or make predictions. 13
(7) Rapidly emerging fields, such as artificial 14
intelligence, machine learning, quantum computing 15
and quantum information, all rely on mathematical 16
and statistical concepts, which are critical to prove 17
under what circumstances an algorithm or experi-18
ment will work and when it will fail. 19
(8) Military academies have a long tradition in 20
teaching mathematical modeling and would benefit 21
from the ability to recruit students with this exper-22
tise from their other school experiences. 23
(9) Mathematical modeling has been a strong 24
educational priority globally, especially in China, 25 4
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where participation in United States mathematical 1
modeling challenges in high school and higher edu-2
cation is orders of magnitude higher than in the 3
United States, and Chinese teams are taking a ma-4
jority of the prizes. 5
(10) Girls participate in mathematical modeling 6
challenges at all levels at similar levels as boys, while 7
in traditional mathematical competitions girls par-8
ticipate less and drop out at every stage. Students 9
cite opportunity for teamwork, using mathematics 10
and statistics in meaningful contexts, ability to use 11
computation, and emphasis on communication as 12
reasons for continued participation in modeling chal-13
lenges. 14
(b) D
EFINITIONS.—In this section: 15
(1) D
IRECTOR.—The term ‘‘Director’’ means 16
the Director of the National Science Foundation. 17
(2) F
EDERAL LABORATORY .—The term ‘‘Fed-18
eral laboratory’’ has the meaning given such term in 19
section 4 of the Stevenson-Wydler Technology Inno-20
vation Act of 1980 (15 U.S.C. 3703). 21
(3) F
OUNDATION.—The term ‘‘Foundation’’ 22
means the National Science Foundation. 23
(4) I
NSTITUTION OF HIGHER EDUCATION .—The 24
term ‘‘institution of higher education’’ has the 25 5
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meaning given such term in section 101(a) of the 1
Higher Education Act of 1965 (20 U.S.C. 1001(a)). 2
(5) M
ATHEMATICAL MODELING .—The term 3
‘‘mathematical modeling’’ has the meaning given 4
such term in the 2019 Guidelines to Assessment and 5
Instruction in Mathematical Modeling Education 6
(GAIMME) report, 2nd edition. 7
(6) O
PERATIONS RESEARCH .—The term ‘‘oper-8
ations research’’ means the application of scientific 9
methods to the management and administration of 10
organized military, governmental, commercial, and 11
industrial processes to maximize operational effi-12
ciency. 13
(7) S
TATISTICAL MODELING .—The term ‘‘sta-14
tistical modeling’’ has the meaning given such term 15
in the 2021 Guidelines to Assessment and Instruc-16
tion in Statistical Education (GAISE II) report. 17
(8) STEM.—The term ‘‘STEM’’ means the 18
academic and professional disciplines of science, 19
technology, engineering, and mathematics, including 20
computer science. 21
(c) P
REPARINGEDUCATORSTOENGAGESTUDENTS 22
INMATHEMATICAL AND STATISTICALMODELING.—The 23
Director shall make awards on a merit-reviewed, competi-24
tive basis to institutions of higher education and nonprofit 25 6
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organizations (or a consortium thereof) for research and 1
development to advance innovative approaches to support 2
and sustain high-quality mathematical modeling education 3
in schools that are operated by local educational agencies, 4
including statistical modeling, data science, operations re-5
search, and computational thinking. The Director shall en-6
courage applicants to form partnerships to address critical 7
transitions, such as middle school to high school, high 8
school to college, and school to internships and jobs. 9
(d) A
PPLICATION.—An entity seeking an award 10
under subsection (c) shall submit an application at such 11
time, in such manner, and containing such information as 12
the Director may require. The application shall include the 13
following: 14
(1) A description of the target population to be 15
served by the research activity for which such an 16
award is sought, including student subgroups de-17
scribed in section 1111(b)(2)(B)(xi) of the Elemen-18
tary and Secondary Education Act of 1965 (20 19
U.S.C. 6311(b)(2)(B)(xi)), and students experi-20
encing homelessness and children and youth in fos-21
ter care. 22
(2) A description of the process for recruitment 23
and selection of students, educators, or local edu-24 7
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cational agencies to participate in such research ac-1
tivity. 2
(3) A description of how such research activity 3
may inform efforts to promote the engagement and 4
achievement of students, including students from 5
groups historically underrepresented in STEM, in 6
prekindergarten through grade 12 in mathematical 7
modeling and statistical modeling using problem-8
based learning with contextualized data and com-9
putational tools. 10
(4) In the case of a proposal consisting of a 11
partnership or partnerships with one or more local 12
educational agencies and one or more researchers, a 13
plan for establishing a sustained partnership that is 14
jointly developed and managed, draws from the ca-15
pacities of each partner, and is mutually beneficial. 16
(e) P
ARTNERSHIPS.—In making awards under sub-17
section (c), the Director shall encourage applications that 18
include the following: 19
(1) Partnership with a nonprofit organization 20
or an institution of higher education that has exten-21
sive experience and expertise in increasing the par-22
ticipation of students in prekindergarten through 23
grade 12 in mathematical modeling and statistical 24
modeling. 25 8
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(2) Partnership with a local educational agency, 1
a consortium of local educational agencies, or Tribal 2
educational agencies. 3
(3) An assurance from school leaders to making 4
reforms and activities proposed by the applicant a 5
priority. 6
(4) Ways to address critical transitions, such as 7
middle school to high school, high school to college, 8
and school to internships and jobs. 9
(5) Input from education researchers and cog-10
nitive scientists, as well as practitioners in research 11
and industry, so that what is being taught is up-to-12
date in terms of content and pedagogy. 13
(6) A communications strategy for early con-14
versations with parents, school leaders, school 15
boards, community members, employers, and other 16
stakeholders. 17
(7) Resources for parents, school leaders, school 18
boards, community members, and other stakeholders 19
to build skills in modeling and analytics. 20
(f) U
SE OFFUNDS.—An entity that receives an 21
award under this section shall use the award for research 22
and development activities to advance innovative ap-23
proaches to support and sustain high-quality mathe-24
matical modeling education in public schools, including 25 9
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statistical modeling, data science, operations research, and 1
computational thinking, which may include the following: 2
(1) Engaging prekindergarten through grade 12 3
educators in professional learning opportunities to 4
enhance mathematical modeling and statistical prob-5
lem solving knowledge, and developing training and 6
best practices to provide more interdisciplinary 7
learning opportunities. 8
(2) Conducting research on curricula and teach-9
ing practices that empower students to choose the 10
mathematical, statistical, computational, and techno-11
logical tools they will apply to a problem, as is re-12
quired in life and the workplace, rather than pre-13
scribing a particular approach or method. 14
(3) Providing students with opportunities to ex-15
plore and analyze real data sets from contexts that 16
are meaningful to the students, which may include 17
the following: 18
(A) Missing or incorrect values. 19
(B) Quantities of data that require choice 20
and use of appropriate technology. 21
(C) Multiple data sets that require choices 22
about which data are relevant to the current 23
problem. 24 10
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(D) Data of various types including quan-1
tities, words, and images. 2
(4) Taking a school or district-wide approach to 3
professional development in mathematical modeling 4
and statistical modeling. 5
(5) Engaging rural local agencies. 6
(6) Supporting research on effective mathe-7
matical modeling and statistical modeling teaching 8
practices, including problem- and project-based 9
learning, universal design for accessibility, and ru-10
brics and mastery-based grading practices to assess 11
student performance. 12
(7) Designing and developing pre-service and 13
in-service training resources to assist educators in 14
adopting transdisciplinary teaching practices within 15
mathematics and statistics courses. 16
(8) Coordinating with local partners to adapt 17
mathematics and statistics teaching practices to le-18
verage local natural, business, industry, and commu-19
nity assets in order to support community-based 20
learning. 21
(9) Providing hands-on training and research 22
opportunities for mathematics and statistics edu-23
cators at Federal laboratories, institutions of higher 24
education, or in industry. 25 11
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(10) Developing mechanisms for partnerships 1
between educators and employers to help educators 2
and students make connections between their mathe-3
matics and statistics projects and topics of relevance 4
in today’s world. 5
(11) Designing and implementing professional 6
development courses and experiences, including men-7
toring for educators, that combine face-to-face and 8
online experiences. 9
(12) Reducing gaps in access to learning oppor-10
tunities for students from groups historically under-11
represented in STEM. 12
(13) Providing support and resources for stu-13
dents from groups historically underrepresented in 14
STEM. 15
(14) Addressing critical transitions, such as 16
middle school to high school, high school to college, 17
and school to internships and jobs. 18
(15) Researching effective approaches for en-19
gaging students from groups historically underrep-20
resented in STEM. 21
(16) Any other activity the Director determines 22
will accomplish the goals of this section. 23
(g) E
VALUATIONS.—All proposals for awards under 24
this section shall include an evaluation plan that includes 25 12
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the use of outcome oriented measures to assess the impact 1
and efficacy of the award. Each recipient of an award 2
under this section shall include results from such evalua-3
tive activities in annual and final project reports. 4
(h) A
CCOUNTABILITY AND DISSEMINATION.—5
(1) E
VALUATION REQUIRED .—The Director 6
shall evaluate the portfolio of awards made under 7
this section. Such evaluation shall—8
(A) use a common set of benchmarks and 9
tools to assess the results of research conducted 10
under such awards and identify best practices; 11
and 12
(B) to the extent practicable, integrate the 13
findings of research resulting from the activities 14
funded through such awards with the findings 15
of other research on student’s pursuit of de-16
grees or careers in STEM. 17
(2) R
EPORT ON EVALUATIONS .—Not later than 18
180 days after the completion of the evaluation 19
under paragraph (1), the Director shall submit to 20
Congress and make widely available to the public a 21
report that includes the following: 22
(A) The results of the evaluation. 23
(B) Any recommendations for administra-24
tive and legislative action that could optimize 25 13
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the effectiveness of the awards made under this 1
section. 2
(i) F
UNDING.—$10,000,000 for each of the fiscal 3
years 2026 through 2030 is authorized to be used by the 4
Directorate for STEM Education of the National Science 5
Foundation to carry out this section. 6
SEC. 3. NASEM REPORT ON MATHEMATICAL AND STATIS-7
TICAL MODELING EDUCATION IN PRE-8
KINDERGARTEN THROUGH 12TH GRADE. 9
(a) S
TUDY.—Not later than 180 days after the date 10
of the enactment of this Act, the Director of the National 11
Science Foundation (in this section referred to as the ‘‘Di-12
rector’’) shall seek to enter into an agreement with the 13
National Academies of Sciences, Engineering and Medi-14
cine (in this section referred to as ‘‘NASEM’’) (or if 15
NASEM declines to enter into such an agreement, another 16
appropriate entity) under which NASEM, or such other 17
appropriate entity, agrees to conduct a study on the fol-18
lowing: 19
(1) Factors that enhance or barriers to the im-20
plementation of mathematical modeling and statis-21
tical modeling in elementary and secondary edu-22
cation, including opportunities for and barriers to 23
use modeling to integrate mathematical and statis-24 14
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tical ideas across the curriculum, including the fol-1
lowing: 2
(A) Pathways in mathematical modeling 3
and statistical problem solving from kinder-4
garten to the workplace so students are able to 5
identify opportunities to use their school mathe-6
matics and statistics in a variety of jobs and 7
life situations and so employers can benefit 8
from students’ school learning of data science, 9
computational thinking, mathematics, statistics, 10
and related subjects. 11
(B) The role of community-based prob-12
lems, service-based learning. and internships for 13
connecting students with career preparatory ex-14
periences. 15
(C) Best practices in problem-, project-, 16
performance-based learning and assessment. 17
(2) Characteristics of teacher education pro-18
grams that successfully prepare teachers to engage 19
students in mathematical modeling and statistical 20
modeling, as well as gaps and suggestions for build-21
ing capacity in the pre-service and in-service teacher 22
workforce. 23
(3) Mechanisms for communication with stake-24
holders, including parents, administrators, and the 25 15
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public, to promote understanding and knowledge of 1
the value of mathematical modeling and statistical 2
modeling in education. 3
(b) P
UBLICSTAKEHOLDERMEETING.—In the course 4
of completing the study described in subsection (a), 5
NASEM or such other appropriate entity shall hold not 6
fewer than one public meeting to obtain stakeholder input 7
on the topics of such study. 8
(c) R
EPORT.—The agreement under subsection (a) 9
shall require NASEM, or such other appropriate entity, 10
not later than 24 months after the effective date of such 11
agreement, to submit to the Director, the Secretary of 12
Education, and the Congress a report containing the fol-13
lowing: 14
(1) The results of the study conducted under 15
subsection (a). 16
(2) Recommendations to modernize the proc-17
esses described in subsection (a)(1). 18
(3) Recommendations for such legislative and 19
administrative action as NASEM, or such other ap-20
propriate entity, determines appropriate. 21
(d) F
UNDING.—$1,000,000 for each of the fiscal 22
years 2026 through 2030 is authorized to be used by the 23
Directorate for STEM Education of the National Science 24
Foundation to carry out this section. 25 16
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SEC. 4. LIMITATIONS. 1
(a) L
IMITATION ONFUNDING.—Amounts made avail-2
able to carry out sections 2 and 3 shall be derived from 3
amounts appropriated or otherwise made available to the 4
National Science Foundation. 5
(b) S
UNSET.—The authority to provide awards under 6
this Act shall expire on September 30, 2029. 7
Passed the House of Representatives March 24,
2025.
Attest:
Clerk. 119
TH
CONGRESS
1
ST
S
ESSION
H. R. 730
AN ACT
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.