[Congressional Record Volume 171, Number 53 (Monday, March 24, 2025)]
[House]
[Pages H1197-H1201]
From the Congressional Record Online through the Government Publishing Office [www.gpo.gov]
MATHEMATICAL AND STATISTICAL MODELING EDUCATION ACT
Mr. BABIN. Mr. Speaker, I move to suspend the rules and pass the bill
(H.R. 730) 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, as amended.
The Clerk read the title of the bill.
The text of the bill is as follows:
H.R. 730
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
[[Page H1198]]
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 such 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 such 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 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 one or more local educational agencies
and one 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 the
following:
(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.
(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, including statistical modeling, data science,
operations research, and computational thinking, which may
include the following:
(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 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 the following:
(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.
(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) Reducing gaps in access to learning opportunities for
students from groups historically underrepresented in STEM.
(13) Providing 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.
[[Page H1199]]
(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 such 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 the following:
(A) The results of the evaluation.
(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 2026
through 2030 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 of the National Science
Foundation (in this section referred to as 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
students are able to identify opportunities to use their
school mathematics and statistics in a variety of jobs and
life situations and so 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 fewer 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 Director, the Secretary of Education, and the
Congress a report containing the following:
(1) The results of the study conducted under subsection
(a).
(2) Recommendations to modernize the processes described in
subsection (a)(1).
(3) Recommendations for such legislative and administrative
action as NASEM, or such other appropriate entity, determines
appropriate.
(d) Funding.--$1,000,000 for each of the fiscal years 2026
through 2030 is authorized to be used by the Directorate for
STEM Education of the National Science Foundation 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, 2029.
The SPEAKER pro tempore. Pursuant to the rule, the gentleman from
Texas (Mr. Babin) and the gentlewoman from Michigan (Ms. Stevens) each
will control 20 minutes.
The Chair recognizes the gentleman from Texas.
General Leave
Mr. BABIN. Mr. Speaker, I ask unanimous consent that all Members may
have 5 legislative days to revise and extend their remarks and include
extraneous material on H.R. 730, the bill now under consideration.
The SPEAKER pro tempore. Is there objection to the request of the
gentleman from Texas?
There was no objection.
Mr. BABIN. Mr. Speaker, I yield myself such time as I may consume.
Mr. Speaker, I am proud to support H.R. 730, the Mathematical and
Statistical Modeling Education Act, sponsored by my colleagues
Representatives Houlahan and Baird.
The importance of STEM education to our economy cannot be overstated.
The National Science Board's 2024 Science and Engineering Indicators
report estimates that our country's STEM workforce constitutes 24
percent of all U.S. jobs. Further still, the Bureau of Labor Statistics
predicts that the need for STEM jobs will increase by another 11
percent by 2032.
America's education sector must ensure that we meet this growing
demand head-on. Many STEM jobs require data comprehension to inform
decisionmaking, but we are currently not providing a strong foundation
for that skill in our schools.
H.R. 730 would modernize our mathematics curriculum by providing
competitive, merit-based grants to support mathematical and statistical
modeling education.
Having served on the House Committee on Science, Space, and
Technology since joining Congress, and now as the sitting chairman, I
understand the importance of mathematical and statistical analyses. I
have had a front row seat to the extraordinary accomplishments of our
domestic STEM talent across many industries and professions. One thing
they all share is a solid foundation and understanding of mathematics
and modeling.
These skills are crucial to a wide variety of occupations, informing
computational and data-driven thinking that supports the growth of a
versatile STEM workforce. Statistical analysis underpins everything
from the development of artificial intelligence to improving advanced
manufacturing.
This bill will allow us to teach these skills more effectively
through R&D and new curricula and methodologies. H.R. 730 also directs
the National Academies to conduct a study identifying best practices
for mathematical and statistical modeling education.
I thank Representatives Houlahan and Baird for their work on this
logical legislation that supports our students and our economy. This
bill passed the House in the 117th and 118th Congresses, and I urge my
colleagues to pass it again today.
Mr. Speaker, I reserve the balance of my time.
Ms. STEVENS. Mr. Speaker, I yield myself such time as I may consume.
Mr. Speaker, this is a real honor and a delight to be speaking on
behalf of and in support of the Mathematical and Statistical Modeling
Education Act, otherwise known as H.R. 730.
We have here in the House Chamber gallery an audience of about 75
people. It is really quite amazing to have the outside public in the
Hall of the House of Representatives watch this debate today, because
if you are interested in government, maybe sometimes you are attuned to
what is going on, on social media or the cable news, and sometimes that
really misses the mark of what we are doing here in the Nation's
Capital, which is bipartisan legislation committed to moving this
Nation forward.
Mr. Speaker, I don't say that lightly. I look at Representative
Houlahan and Representative Baird, two Members of the class of 2018,
both in their fourth term. I have passed legislation with both of them.
Now they have joined together to pass H.R. 730, a STEM bill, science,
technology, engineering, and mathematics. You don't have STEM without
mathematics.
We call on the National Science Foundation to support mathematical
and statistical modeling education starting in elementary school and
secondary schools. These activities include providing grants to
academic institutions and nonprofit organizations
[[Page H1200]]
that improve data, science skills, enhance computational thinking, and
enable access to professional development opportunities. My friends,
this is how we compete and win on the world's stage.
It is so very important to me, as somebody who worked in a
manufacturing research lab. I have brought in expert witnesses to the
Science Committee that, yes, our great chairman has been a part of for
his whole tenure in Congress. We have heard this from the researchers.
I have heard this since before I came to Congress. We need this skill
set.
This is what we want to say to the young people we have observing the
floor right now. I don't know the full curriculum that they are in and
whatnot. I imagine there is an interest in government. STEM is also of
note. When we were doing STEM education in the lab I was in, we had a
great researcher. This man had a great engineering degree, and we would
do the STEM education. He would tell the students that he didn't always
pass his math classes the first round, but he had the surrounding
cushion to help him go back for a second round.
That is what it is all about in America. If you want to be an
engineer or if you want to contribute to our advanced manufacturing
economy, we want your talent. With the Baird-Houlahan bill, what we are
going to do is see NSF do what it is already doing but double down for
a continuing educational experience at the NSF so that students can
thrive.
What we don't want is a bunch of one-offs and all of a sudden you are
graduating high school and maybe you had some exposure to these
computational skills. We are competing across the world with talent.
Our schools need to have the best ability to thrive. I urge everybody
in this data-driven, AI, exciting world that the United States is
leading, and encourage our colleagues on both sides of the aisle to
say, yes, we want this bill, H.R. 730, to move forward.
Mr. Speaker, I reserve the balance of my time.
The SPEAKER pro tempore (Mr. Bentz). The Chair reminds Members that
the rules do not allow references to persons in the gallery.
{time} 1430
Mr. BABIN. Mr. Speaker, I am prepared to close, and I reserve the
balance of my time.
Ms. STEVENS. Mr. Speaker, I yield 3 minutes to the gentlewoman from
Pennsylvania (Ms. Houlahan) for her remarks.
Ms. HOULAHAN. Mr. Speaker, I thank Representative Haley Stevens for
this opportunity to speak on behalf of this really important
legislation.
Imagine, if you will, the ability to model a manufacturing process to
design a basketball shoe, maybe modeling the opportunity to cure a
disease, maybe modeling market behavior, perhaps modeling a system to
be able to equitably donate organs to people or molecules to cure a
disease, modeling energy sources so that we can have a more safe and
healthy planet, or maybe even, unfortunately, having to model the
destruction of our infrastructure so that we can make sure that we have
the national security resources to be able to protect our fine Nation.
H.R. 730, the Mathematical and Statistical Modeling Education Act, is
designed to address all of these different issues in our society, but I
come to the floor with really bad news, as though we needed more.
America's K-12 students are falling further and further behind,
particularly behind China's students, academically.
This lag is particularly concerning when we talk about the STEM
fields because our industrial base continues to tell us that we are not
educating and preparing the designers, engineers, and modelers of the
future in order to be able to compete with our adversaries.
The National Assessment on Education Progress, which is colloquially
known as the Nation's report card, has shown us that this knowledge and
talent shortage is a nationwide challenge. In 2022, the assessment
registered the largest decline in mathematics scores since we first
started assessing in 1990. The scores of the average fourth grader were
down 5 points. Worse, the average eighth grader recorded a score of 8
points lower than the previous assessment. The 2024 survey was even
more concerning because it showed an overall growth of zero from 2022
and even declines among some students, as well.
With all the chaos that is unfolding in other parts of our
government, particularly in the education sector, now is the time to
invest in math and STEM education.
The Mathematical and Statistical Modeling Education Act is just one
answer to this challenge. It is a bipartisan bill, and it directs $10
million of already-appropriated money to the National Science
Foundation for a grant program that will support the modernization of
mathematical and statistical modeling for education across this Nation.
As a former educator myself and an engineer by education and
profession, I know personally that there is a very serious need to
improve mathematics education for our K-12 students. Indeed, when I
taught chemistry, I saw firsthand how my students struggled because
they lacked the basic foundations in math that are necessary for the
sciences. Today, I hear from both our generals and our CEOs about what
these gaps mean for our country. It doesn't just hurt our economy. It
hurts our national security, as well.
Math skills form the basis for all the STEM disciplines, and
importantly, they also form the basis just for critical thinking and
problem-solving in general. If our students can't get ahead in school,
how will they get ahead in the STEM workforce as engineers, computer
scientists, chemists, nurses, doctors, and much more?
The SPEAKER pro tempore. The time of the gentlewoman has expired.
Ms. STEVENS. Mr. Speaker, I yield an additional 1 minute to the
gentlewoman from Pennsylvania.
Ms. HOULAHAN. Mr. Speaker, importantly, how will those who may decide
to pursue STEM fields succeed where these same skills are useful among
the trades or manufacturing?
Thankfully, schools across the country are developing new tools and
curricula with students to help them learn these challenging topics.
I will repeat again that this is without any additional cost. This is
with funds already appropriated.
I will also repeat again that this is a bipartisan piece of
legislation that will provide our young people with the skills they
need to succeed in our marketplace.
It passed in the 118th Congress unanimously out of the Committee on
Science, Space, and Technology as well when it was last marked up. I
hope that my colleagues will support this unanimously and make this
bill finally a law.
Lastly, I thank my Republican colleague and fellow veteran, Mr.
Baird, for his hard work on this legislation and extend appreciation to
the staff of the SST Committee, as well as Representative Stevens and
Representative Babin, who have helped shepherd this legislation through
today.
Mr. Speaker, I urge my colleagues on both sides to support this
commonsense, bipartisan measure to strengthen our national security and
our economy.
Mr. BABIN. Mr. Speaker, I reserve the balance of my time.
Ms. STEVENS. Mr. Speaker, I yield myself the balance of my time to
close.
Mr. Speaker, I thank our wonderful sponsors of this bill. It is
really quite exciting. We continue to move toward urging colleagues to
vote ``yes'' on H.R. 730, the Mathematical and Statistical Modeling
Education Act.
Mr. Speaker, I yield back the balance of my time.
Mr. BABIN. Mr. Speaker, I yield myself the balance of my time.
Mr. Speaker, as teachers prepare the next generation of American STEM
workers, we must invest in the best curricula and teaching methods.
H.R. 730 will improve mathematical and statistical modeling education
in the United States, ensuring American businesses have qualified
workers with the necessary skills to drive innovation in STEM fields,
including artificial intelligence and advanced manufacturing. This is
good policy, which is why this same bill passed the House in the 117th
and the 118th Congresses.
Mr. Speaker, I urge my colleagues to support it once again, and I
yield back the balance of my time.
Mr. BAIRD. Mr. Speaker, the Mathematical and Statistical Modeling
Education Act seeks
[[Page H1201]]
to improve the quality of STEM education in America. This bill will
allow us to modernize math curricula and improve K-12 science,
technology, engineering, and mathematics (STEM) education.
While this bill directs the National Science Foundation to grant
awards to educational institutions, it does not award any new funding.
As we look at reining in the out-of-control government spending and
bureaucracy, we must work with the resources we already have.
As an animal scientist, I understand the life-changing effects STEM
education can have when it comes to our livestock, creating innovative,
more effective farming techniques, our food quality, and ultimately our
Nation's well-being.
Proper STEM education has an invaluable impact on American
innovation. It equips our students--our future workforce--to tackle the
challenges of our modern digital economy. Modernizing STEM education
also has wide-ranging impacts on our national security.
The United States' ability to create cutting-edge technologies has
been vital to defeating our adversaries, especially as our adversary,
Communist China, continues to make huge investments in STEM to try and
out-compete the U.S. Beating China and maintaining our global
competitive edge begins with strengthening STEM education in K-12
schools.
That is why I am proud to co-lead this bipartisan legislation to
ensure that the United States continues to dominate when it comes to
STEM education.
The SPEAKER pro tempore. The question is on the motion offered by the
gentleman from Texas (Mr. Babin) that the House suspend the rules and
pass the bill, H.R. 730, as amended.
The question was taken; and (two-thirds being in the affirmative) the
rules were suspended and the bill, as amended, was passed.
A motion to reconsider was laid on the table.
____________________