119-hr730

[Congressional Bills 119th Congress]
[From the U.S. Government Publishing Office]
[H.R. 730 Referred in Senate

    (RFS) ]

<DOC>
119th CONGRESS
 1st Session
 H. R. 730

_______________________________________________________________________

 IN THE SENATE OF THE UNITED STATES

 March 25, 2025

 Received; read twice and referred to the Committee on Health, 
 Education, Labor, and Pensions

_______________________________________________________________________

 AN ACT

 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.

 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).

    (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.

    (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.

 Passed the House of Representatives March 24, 2025.

 Attest:

 KEVIN F. MCCUMBER,

 Clerk.