[Congressional Record Volume 168, Number 124 (Tuesday, July 26, 2022)]
[House]
[Pages H7098-H7101]
From the Congressional Record Online through the Government Publishing Office [www.gpo.gov]




          MATHEMATICAL AND STATISTICAL MODELING EDUCATION ACT

  Mr. BEYER. Madam Speaker, I move to suspend the rules and pass the 
bill (H.R. 3588) 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. 3588

       Be it enacted by the Senate and House of Representatives of 
     the United States of America in Congress assembled,

     SECTION 1. SHORT TITLE.

       This Act may be cited as the ``Mathematical and Statistical 
     Modeling Education Act''.

     SEC. 2. MATHEMATICAL AND STATISTICAL MODELING EDUCATION.

       (a) Findings.--Congress finds the following:
       (1) The mathematics taught in schools, including 
     statistical problem solving and data science, is not keeping 
     pace with the rapidly evolving needs of the public and 
     private sector, resulting in a STEM skills shortage and 
     employers needing to expend resources to train and upskill 
     employees.
       (2) According to the Bureau of Labor Statistics, the United 
     States will need 1,000,000 additional STEM professionals than 
     it is on track to produce in the coming decade.
       (3) The field of data science, which is relevant in almost 
     every workplace, relies on the ability to work in teams and 
     use computational tools to do mathematical and statistical 
     problem solving.
       (4) Many STEM occupations offer higher wages, more 
     opportunities for advancement, and a higher degree of job 
     security than non-STEM jobs.
       (5) The STEM workforce relies on computational and data-
     driven discovery, decision making, and predictions, from 
     models that often must quantify uncertainty, as in weather 
     predictions, spread of disease, or financial forecasting.
       (6) Most fields, including analytics, science, economics, 
     publishing, marketing, actuarial science, operations 
     research, engineering, and medicine, require data savvy, 
     including the ability to select reliable sources of data, 
     identify and remove errors in data, recognize and quantify 
     uncertainty in data, visualize and analyze data, and use data 
     to develop understanding or make predictions.
       (7) Rapidly emerging fields, such as artificial 
     intelligence, machine learning, quantum computing and quantum 
     information, all rely on mathematical and statistical 
     concepts, which are critical to prove under what 
     circumstances an algorithm or experiment will work and when 
     it will fail.
       (8) Military academies have a long tradition in teaching 
     mathematical modeling and would benefit from the ability to 
     recruit students with this expertise from their other school 
     experiences.
       (9) Mathematical modeling has been a strong educational 
     priority globally, especially in China, where participation 
     in United States mathematical modeling challenges in high 
     school and higher education is orders of magnitude higher 
     than in the United States, and Chinese teams are taking a 
     majority of the prizes.
       (10) Girls participate in mathematical modeling challenges 
     at all levels at similar levels as boys, while in traditional 
     mathematical competitions girls participate less and drop out 
     at every stage. Students cite opportunity for teamwork, using 
     mathematics and statistics in meaningful contexts, ability to 
     use computation, and emphasis on communication as reasons for 
     continued participation in modeling challenges.
       (b) Definitions.--In this section:
       (1) Director.--The term ``Director'' means the Director of 
     the National Science Foundation.
       (2) Federal laboratory.--The term ``Federal laboratory'' 
     has the meaning given such term in section 4 of the 
     Stevenson-Wydler Technology Innovation Act of 1980 (15 U.S.C. 
     3703).

[[Page H7099]]

       (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.
       (c) Preparing Educators To Engage Students in Mathematical 
     and Statistical Modeling.--The Director shall provide grants 
     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 operated by local 
     education 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 a grant 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 grant 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 
     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 awarding grants 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 a grant under 
     this section shall use the grant funds 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--
       (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) addressing critical transitions, such as middle school 
     to high school, high school to college, and school to 
     internships and jobs; and
       (13) any other activity the Director determines will 
     accomplish the goals of this section.
       (g) Evaluations.--All proposals for grants under this 
     section shall include an evaluation plan that includes the 
     use of outcome oriented measures to assess the impact and 
     efficacy of the grant. Each recipient of a grant under this 
     section shall include results from these evaluative 
     activities in annual and final projects.
       (h) Accountability and Dissemination.--
       (1) Evaluation required.--The Director shall evaluate the 
     portfolio of grants awarded under this section. Such 
     evaluation shall--
       (A) use a common set of benchmarks and tools to assess the 
     results of research conducted under such grants and identify 
     best practices; and
       (B) to the extent practicable, integrate the findings of 
     research resulting from the activities funded through such 
     grants 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 grants 
     awarded under this section.
       (i) Authorization of Appropriations.--For each of fiscal 
     years 2023 through 2027, there are authorized to be 
     appropriated to the National Science Foundation $10,000,000 
     to carry out the activities under this section.

     SEC. 3. NASEM REPORT ON MATHEMATICAL AND STATISTICAL MODELING 
                   EDUCATION IN PREKINDERGARTEN 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, 
     Engineering and Medicine (in this section referred to as 
     ``NASEM'') (or if NASEM declines to enter into such an 
     agreement, another appropriate entity) under which NASEM, or 
     such other appropriate entity, agrees to conduct a study on 
     the following:
       (1) Factors that enhance or barriers to the implementation 
     of mathematical modeling and statistical modeling in 
     elementary and secondary education, including opportunities 
     for and barriers to use modeling to integrate mathematical 
     and statistical ideas across the curriculum, including the 
     following:
       (A) Pathways in mathematical modeling and statistical 
     problem solving from kindergarten to the workplace so that 
     students are able to identify opportunities to use their 
     school mathematics and statistics in a variety of jobs and 
     life situations and so that employers can benefit from 
     students' school learning of data science, computational 
     thinking, mathematics, statistics, and related subjects.
       (B) The role of community-based problems, service-based 
     learning. and internships for connecting students with career 
     preparatory experiences.
       (C) Best practices in problem-, project-, performance-based 
     learning and assessment.

[[Page H7100]]

       (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) Authorization of Appropriations.--For fiscal year 2023, 
     there are authorized to be appropriated to the National 
     Science Foundation $1,000,000 to carry out the activities 
     under this section.

  The SPEAKER pro tempore. Pursuant to the rule, the gentleman from 
Virginia (Mr. Beyer) and the gentleman from Oklahoma (Mr. Lucas) each 
will control 20 minutes.
  The Chair recognizes the gentleman from Virginia.


                             General Leave

  Mr. BEYER. Madam 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. 3588, the bill now under 
consideration.
  The SPEAKER pro tempore. Is there objection to the request of the 
gentleman from Virginia?
  There was no objection.
  Mr. BEYER. Madam Speaker, I yield myself such time as I may consume.
  Madam Speaker, I rise in support of H.R. 3588, the Mathematical and 
Statistical Modeling Education Act. I thank Representatives Chrissy 
Houlahan and  Jim Baird for introducing this bill.
  U.S. capabilities in science and innovation are critical for our 
future prosperity, national security, and global competitiveness. I am 
thrilled that this week the House will consider landmark legislation 
that will accelerate progress on cutting-edge science and technology. 
However, we cannot fully realize this vision unless we build a domestic 
STEM workforce that is poised to turn these investments into 
breakthrough discoveries and transformative innovations. To that end, 
we must address the longstanding challenges in K-12 STEM education.
  H.R. 3588 will advance research to improve mathematics education by 
incorporating statistical modeling into mathematics curriculum. We know 
that students from diverse backgrounds are attracted to STEM if they 
can see it as a tool for solving real-world challenges. This bill will 
help researchers develop innovative teaching methods to do just that.
  Madam Speaker, I urge my colleagues to support the bill, and I 
reserve the balance of my time.
  Mr. LUCAS. Madam Speaker, I yield myself such time as I may consume.
  I rise in support of H.R. 3588, the Mathematical and Statistical 
Modeling Education Act.
  This bill would direct the National Science Foundation to provide 
competitive grants to support the research and development of curricula 
and teaching methods to improve mathematical and statistical modeling 
education. Ensuring that our teachers are well equipped to encourage 
student interest and involvement in STEM fields is a key component of 
stimulating America's STEM workforce and bolstering our 
competitiveness.
  Mathematics underpins the critical thinking skills we use every day, 
from managing a budget to following a recipe, even to estimating how 
long votes will take today.
  As more and more jobs become tech-reliant, our students will need 
mathematical and computational skills to keep up with the changing 
workplace and fill the growing demand for a domestic STEM-literate 
workforce.
  H.R. 3588 is supported by the American Statistical Association, the 
National Council of Teachers of Mathematics, the American Society of 
Mechanical Engineers, and the Business Software Alliance, among other 
stakeholders.
  Madam Speaker, I thank my colleague, Dr. Baird, for working in a 
bipartisan way to advance this legislation.
  Madam Speaker, I urge all of my colleagues to support this 
legislation, and I reserve the balance of my time.
  Mr. BEYER. Madam Speaker, I yield 3 minutes to the gentlewoman from 
Pennsylvania (Ms. Houlahan).
  Ms. HOULAHAN. Madam Speaker, I rise today in support of my bill, H.R. 
3588, the bipartisan Mathematical and Statistical Modeling Education 
Act.
  This is a very straightforward bipartisan bill. It would modernize 
the math curricula and improve K-12 science, technology, engineering, 
and mathematics, otherwise known as STEM, education in the United 
States.
  We know that STEM education taught in schools today is simply not 
keeping pace with the rapidly evolving needs of the public and private 
sectors. We also know that this lack of skills has a direct correlation 
with the STEM skills shortage across our Nation.
  To fix this, my bill will help schools update their math curricula to 
make them more relevant and applicable to real-world scenarios.
  The National Science Foundation would be tasked with providing 
competitive grants focused on modernizing STEM education through 
mathematical and statistical modeling, including data-driven and 
computational thinking. It will also direct the National Academies of 
Sciences, Engineering, and Medicine to conduct a study on the same 
topic.
  As an engineer myself and a former chemistry teacher and 
entrepreneur, I know firsthand just how vital this is for the next 
generation and for the future of our workforce in our Nation.
  According to the Bureau of Labor Statistics, the United States will 
need 1 million additional STEM professionals than it is on track to 
produce in the coming decade alone.
  Thankfully, with this legislation, we have the opportunity to provide 
tangible critical thinking skills to the next generation that will 
enable them to succeed in the workplace and beyond. It is far past time 
to bring problem-solving into the 21st century.
  When I was in school, math was often portrayed as a one-dimensional 
skill that existed solely in the math classroom. Let's now show our 
students that a skill set in STEM is invaluable to analyzing trends on 
social media or predicting sports outcomes, and it is as valuable for 
that as it is to succeed in any chemistry class.
  I am very grateful to Representative  Jim Baird for joining me, to 
Chairwoman Eddie Bernice Johnson and Ranking Member Lucas for their 
leadership on this topic, and to everyone else who played a role in 
bringing this very important and bipartisan bill to the floor.
  Madam Speaker, I urge all of my colleagues to vote ``yes'' on this 
bill.
  Mr. LUCAS. Madam Speaker, I yield myself the balance of my time for 
closing.
  Madam Speaker, as teachers prepare for the next generation of the 
American workforce, it is vital that we invest in the best STEM 
education curricula and teaching methods. That is why I strongly 
support this bipartisan legislation, which will bolster investments in 
mathematics and statistical modeling curricula.
  Madam Speaker, I again thank Dr. Baird for his hard work to advance 
this legislation.
  Madam Speaker, I urge my colleagues to vote in support of this bill, 
and I yield back the balance of my time.
  Mr. BEYER. Madam Speaker, I yield myself the balance of my time for 
closing.
  Madam Speaker, so far this year, I have completed two undergraduate 
mathematics courses at George Mason University. Calculus II starts on 
August 22.
  I will tell you personally the evolution of the teaching of math has 
come so far since I graduated from college. I am very excited by this 
legislation. The thought that we can take so much progress in teaching 
and software to our next generation of students is very exciting.

[[Page H7101]]

  As I sit, sometimes in despair, watching my friends get out their 
calculators to figure out the 15 percent or 20 percent tip, I think 
this would be wonderful legislation to move forward.
  Madam Speaker, I urge my colleagues to support H.R. 3588, and I yield 
back the balance of my time.
  The SPEAKER pro tempore. The question is on the motion offered by the 
gentleman from Virginia (Mr. Beyer) that the House suspend the rules 
and pass the bill, H.R. 3588, as amended.
  The question was taken.
  The SPEAKER pro tempore. In the opinion of the Chair, two-thirds 
being in the affirmative, the ayes have it.
  Mr. TIFFANY. Madam Speaker, on that I demand the yeas and nays.
  The yeas and nays were ordered.
  The SPEAKER pro tempore. Pursuant to clause 8 of rule XX, further 
proceedings on this motion will be postponed.

                          ____________________