[Congressional Record Volume 170, Number 148 (Monday, September 23, 2024)]
[House]
[Pages H5638-H5641]
From the Congressional Record Online through the Government Publishing Office [www.gpo.gov]
MATHEMATICAL AND STATISTICAL MODELING EDUCATION ACT
Mr. LUCAS. Mr. Speaker, I move to suspend the rules and pass the bill
(H.R. 1735) 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. 1735
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
[[Page H5639]]
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
[[Page H5640]]
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.
The SPEAKER pro tempore. Pursuant to the rule, the gentleman from
Oklahoma (Mr. Lucas) and the gentlewoman from California (Ms. Lofgren)
each will control 20 minutes.
The Chair recognizes the gentleman from Oklahoma.
General Leave
Mr. LUCAS. Mr. Speaker, I ask unanimous consent that all Members may
have 5 legislative days in which to revise and extend their remarks and
include extraneous material on H.R. 1735, the bill now under
consideration.
The SPEAKER pro tempore. Is there objection to the request of the
gentleman from Oklahoma?
There was no objection.
Mr. LUCAS. Mr. Speaker, I yield myself such time as I may consume.
Mr. Speaker, I am proud to support H.R. 1735, the Mathematical and
Statistical Modeling Education Act, sponsored by my colleagues
Representatives Houlahan and Baird.
Anyone who pays attention to the economy knows the importance of STEM
education. The Bureau of Labor Statistics predicts that our need for
STEM jobs will increase by nearly 11 percent by 2032.
To fill those jobs and ensure that we have a highly productive
workforce, we need to focus on STEM education in our schools. We need
to be sure that we are providing a useful STEM education.
We know that many STEM jobs require data-driven decisionmaking, but
we are not providing a grounding in that skill in our schools. To this
end, H.R. 1735 modernizes our mathematics curriculum by providing
competitive grants to support education in mathematical and statistical
modeling.
As someone trained in agricultural economics, I understand the value
of conducting mathematical and statistical analysis. A solid grounding
in these fields helps us predict crop yields, identify the effects of
temperatures and water levels, and model commodity markets. Those are
just examples from a single industry.
The skills are crucial to a wide variety of professions and help
inform computational and data-driven thinking. Statistical analysis
underpins everything, from developing artificial intelligence to
improving advanced manufacturing.
This bill would allow us to better teach these critical skills
through R&D into new curricula and teaching methods. It would also
direct the National Academies to conduct a study that will identify
best practices for mathematical and statistical modeling education.
I thank Representatives Houlahan and Baird for their work on this
issue over the past several years. This is smart legislation that
supports our students and our economy.
Mr. Speaker, I urge my colleagues to pass it today, and I reserve the
balance of my time.
Ms. LOFGREN. Mr. Speaker, I yield myself such time as I may consume.
Mr. Speaker, this bill is an important one, the Mathematical and
Statistical Modeling Education Act, represented by two really
impressive Members of Congress, Ms. Houlahan and Dr. Baird.
This bill would direct the National Science Foundation to invest in
K-12 education research and development, with a focus on mathematical
modeling.
This bill would help modernize STEM education by supporting the
creation of advanced curricula that cover mathematical and statistical
modeling, including computational and data-driven thinking.
This is the kind of education our students deserve and what they need
for today's society and its technological and data-driven demands.
Members and staff have worked really hard to accommodate many desired
changes to this bill, and I believe it is in a state now that should
satisfy just about everyone. It has support from the premier
educational, statistical, and mathematical organizations in the United
States. The Senate companion bill is in a similar good place. It is
time for this bill to become law.
This is an important bill that will better prepare our students for
careers in STEM, and I hope all of us will join together and support
this bill.
Mr. Speaker, I reserve the balance of my time.
Mr. LUCAS. Mr. Speaker, I yield such time as he may consume to the
gentleman from Indiana (Mr. Baird) to speak on his bill.
Mr. BAIRD. Mr. Speaker, I thank Congresswoman Houlahan for her
dedication to improving STEM education and for being a great partner to
work with on advancing this bill.
Mr. Speaker, the Mathematical and Statistical Modeling Education Act
provides a much-needed solution to improving the quality of STEM
education in America. This bill would advance mathematical instruction
in our classrooms by incorporating modern tools and context, with data
and computational studies.
Mathematical modeling is taught today, but on a limited basis. Even
so, mathematical modeling is the foundation for the important work of
our Nation when it comes to research, development, and, ultimately,
technological innovation.
While the bill directs the National Science Foundation to grant
awards to our institutions of higher education, the bill does not award
any new funding. We must work with the resources we already have.
As an animal scientist, I understand the life-changing effects proper
mathematical modeling can have on our livestock, our food, and,
ultimately, our Nation's well-being.
That is why I am proud to co-lead this bipartisan legislation to
ensure that the United States continues to dominate in STEM education,
and I encourage all of my colleagues to vote ``yes'' for this bill.
Ms. LOFGREN. Mr. Speaker, I yield myself such time as I may consume.
Mr. Speaker, I am so pleased to serve in the Congress with
Congresswoman Houlahan, who has such a spectacular background in
science. She is an engineer, former business executive, former teacher,
former nonprofit executive, and an Air Force vet. She has it all.
Working with Dr. Baird, she put together this bill that is so
important.
[[Page H5641]]
Mr. Speaker, I yield such time as she may consume to the gentlewoman
from Pennsylvania (Ms. Houlahan).
{time} 2015
Ms. HOULAHAN. Mr. Speaker, I thank Ranking Member Lofgren for
yielding me the time to speak on behalf of my bill, H.R. 1735, and I
thank so much my colleague, Representative Baird, for his tireless
efforts to help us get this across the finish line.
It is past time that America's K-12 students enter the 21st century,
and this Mathematical and Statistical Modeling Education Act is a
bipartisan bill that will help with that and will direct $10 million in
funding, importantly, funding that is already appropriated to the
National Science Foundation, toward grant programs, and it will support
the modernization of mathematical and statistical modeling education
across this fine Nation.
As someone who is educated as a systems engineer, with both
undergraduate and graduate degrees, which focused on things like
operations research and linear programming and statistical modeling, I
have had the privilege of using all of these kinds of maths all during
my career and life.
Also, as a former high school chemistry teacher, I saw firsthand that
many of my students struggled because they lacked the basic foundations
in math that are necessary to succeed in the sciences, and frankly, to
succeed in our economy.
These math skills form the basis of all the STEM disciplines, and
importantly, they also form the basis of critical thinking and problem-
solving as well. Without them, students struggle to keep up, let alone
to get ahead not just in math and science but ultimately in our
competitive workplace and world.
The National Assessment of Educational Progress, which is
colloquially known as the Nation's report card, has shown that this is
a national challenge. The most recent assessment registered the very
largest declines in math scores since we first started assessing them
in 1990. The scores of our average fourth graders were down five
points. Worse, the average score of our eighth graders recorded an
eight-point lower assessment than the last time.
As our students are continuing to recover from the pandemic, now
particularly is a very good time to focus on a renewed and modified
investment in math and STEM education and skills.
If our students can't get ahead in school, how will they get ahead in
the STEM workforce as engineers, as chemists, as nurses, as doctors,
and so much more?
As importantly, how will those who do not pursue STEM fields succeed
where these same kinds of skills are very, very useful in things such
as the trades and manufacturing or any other job in industry?
Thankfully, schools across the country are already developing new
tools and curricula to better connect students and help them learn
these challenging topics.
It is crucial though that the Federal Government deliver its
financial support to schools that are already leading this effort and
that want to in the future.
My colleagues also supported an amendment to the bill ensuring that
this funding is broadly available, so students can benefit from it no
matter what kind of school they go to. Their adjustment made sure that
schools which are private, faith-based, or homeschools also have access
to this funding.
I also want to highlight that this funding is all drawn from funds
that are already appropriated to the National Science Foundation. This
legislation does not represent any new funding authorizations or
authorities. It is simply ensuring that the NSF is able to spend the
money it already receives to bolster innovation in this very important
area.
This bill will go a long way towards providing our very youngest
people with the skills that they need to succeed in today's
marketplace. It passed with a strong bipartisan majority in the 117th
Congress and was passed unanimously out of the Committee on Science,
Space, and Technology last year in this Congress as well.
I once again thank my Republican colleague, Mr. Baird, for his work
on this legislation. I also extend my deep appreciation to the SST
staff and committee who have helped to shepherd this legislation
through today.
Mr. Speaker, I urge all of my colleagues on both sides of the aisle
to support this very commonsense, bipartisan measure.
Ms. LOFGREN. Mr. Speaker, I have no additional requests for time. I
would just like to once again thank Congresswoman Houlahan, Dr. Baird,
and I also thank the chairman. We have had a great run here in the
Science Committee this evening with these terrific bills, which I urge
all Members to support.
Mr. Speaker, I yield back the balance of my time.
Mr. LUCAS. Mr. Speaker, I have no additional speakers, and I yield
myself the balance of my time.
I encourage my colleagues to vote for this awesome bill worked on in
a very productive fashion by our colleagues.
I would note, Mr. Speaker, we have had a very productive session in
the 118th Congress. I thought under the previous committee leadership
the two previous sessions it would be hard to beat, but we have
accomplished a lot, and we have laid the groundwork for whatever
remains of the 118th to tie up a whole bunch of loose ends. That is a
testament to the gentlewoman and her staff, and I think to my staff and
my colleagues on my side of the room.
The issues we work on, as the gentlewoman and I have discussed many
times, are not just today and tomorrow. It is 50 years, it is 150
years, it is 500 years from now, the net effect.
Mr. Speaker, I yield back the balance of my time.
The SPEAKER pro tempore. The question is on the motion offered by the
gentleman from Oklahoma (Mr. Lucas) that the House suspend the rules
and pass the bill, H.R. 1735, 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.
____________________