IIB 

118TH CONGRESS 

2D SESSION H. R. 1735 

IN THE SENATE OF THE UNITED STATES 

SEPTEMBER 24, 2024 

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. 

1 Be it enacted by the Senate and House of Representa2 tives of the United States of America in Congress assembled, 


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1 SECTION 1. SHORT TITLE. 

2 This Act may be cited as the ‘‘Mathematical and Sta3 tistical Modeling Education Act’’. 

4 SEC. 2. MATHEMATICAL AND STATISTICAL MODELING EDU5 CATION. 

6 (a) FINDINGS.—Congress finds the following: 

7 (1) The mathematics taught in schools, includ8 ing statistical problem solving and data science, is 

9 not keeping pace with the rapidly evolving needs of 

10 the public and private sector, resulting in a STEM 

11 skills shortage and employers needing to expend re12 sources to train and upskill employees. 

13 (2) According to the Bureau of Labor Statis14 tics, the United States will need 1,000,000 addi15 tional STEM professionals than it is on track to 

16 produce in the coming decade. 

17 (3) The field of data science, which is relevant 

18 in almost every workplace, relies on the ability to 

19 work in teams and use computational tools to do 

20 mathematical and statistical problem solving. 

21 (4) Many STEM occupations offer higher 

22 wages, more opportunities for advancement, and a 

23 higher degree of job security than non-STEM jobs. 

24 (5) The STEM workforce relies on computa25 tional and data-driven discovery, decision making, 

26 and predictions, from models that often must quanVerDate Sep 11 2014 03:03 Sep 25, 2024 Jkt 049200 PO 00000 Frm 00002 Fmt 6652 Sfmt 6201 E:\BILLS\H1735.RFS H1735

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1 tify uncertainty, as in weather predictions, spread of 

2 disease, or financial forecasting. 

3 (6) Most fields, including analytics, science, eco4 nomics, publishing, marketing, actuarial science, op5 erations research, engineering, and medicine, require 

6 data savvy, including the ability to select reliable 

7 sources of data, identify and remove errors in data, 

8 recognize and quantify uncertainty in data, visualize 

9 and analyze data, and use data to develop under10 standing or make predictions. 

11 (7) Rapidly emerging fields, such as artificial 

12 intelligence, machine learning, quantum computing 

13 and quantum information, all rely on mathematical 

14 and statistical concepts, which are critical to prove 

15 under what circumstances an algorithm or experi16 ment will work and when it will fail. 

17 (8) Military academies have a long tradition in 

18 teaching mathematical modeling and would benefit 

19 from the ability to recruit students with this exper20 tise from their other school experiences. 

21 (9) Mathematical modeling has been a strong 

22 educational priority globally, especially in China, 

23 where participation in United States mathematical 

24 modeling challenges in high school and higher edu25 cation is orders of magnitude higher than in the 


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1 United States, and Chinese teams are taking a ma2 jority of the prizes. 

3 (10) Girls participate in mathematical modeling 

4 challenges at all levels at similar levels as boys, while 

5 in traditional mathematical competitions girls par6 ticipate less and drop out at every stage. Students 

7 cite opportunity for teamwork, using mathematics 

8 and statistics in meaningful contexts, ability to use 

9 computation, and emphasis on communication as 

10 reasons for continued participation in modeling chal11 lenges. 

12 (b) DEFINITIONS.—In this section: 

13 (1) DIRECTOR.—The term ‘‘Director’’ means 

14 the Director of the National Science Foundation. 

15 (2) FEDERAL LABORATORY.—The term ‘‘Fed16 eral laboratory’’ has the meaning given such term in 

17 section 4 of the Stevenson-Wydler Technology Inno18 vation Act of 1980 (15 U.S.C. 3703). 

19 (3) FOUNDATION.—The term ‘‘Foundation’’ 

20 means the National Science Foundation. 

21 (4) INSTITUTION OF HIGHER EDUCATION.—The 

22 term ‘‘institution of higher education’’ has the 

23 meaning given such term in section 101(a) of the 

24 Higher Education Act of 1965 (20 U.S.C. 1001(a)). 


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1 (5) MATHEMATICAL MODELING.—The term 

2 ‘‘mathematical modeling’’ has the meaning given the 

3 term in the 2019 Guidelines to Assessment and In4 struction in Mathematical Modeling Education 

5 (GAIMME) report, 2nd edition. 

6 (6) OPERATIONS RESEARCH.—The term ‘‘oper7 ations research’’ means the application of scientific 

8 methods to the management and administration of 

9 organized military, governmental, commercial, and 

10 industrial processes to maximize operational effi11 ciency. 

12 (7) STATISTICAL MODELING.—The term ‘‘sta13 tistical modeling’’ has the meaning given the term in 

14 the 2021 Guidelines to Assessment and Instruction 

15 in Statistical Education (GAISE II) report. 

16 (8) STEM.—The term ‘‘STEM’’ means the aca17 demic and professional disciplines of science, tech18 nology, engineering, and mathematics, including 

19 computer science. 

20 (c) PREPARING EDUCATORS TO ENGAGE STUDENTS

21 IN MATHEMATICAL AND STATISTICAL MODELING.—The 

22 Director shall make awards on a merit-reviewed, competi23 tive basis to institutions of higher education, and nonprofit 

24 organizations (or a consortium thereof) for research and 

25 development to advance innovative approaches to support 


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1 and sustain high-quality mathematical modeling education 

2 in schools that are private, faith-based, or homeschools, 

3 or operated by local educational agencies, including statis4 tical modeling, data science, operations research, and com5 putational thinking. The Director shall encourage appli6 cants to form partnerships to address critical transitions, 

7 such as middle school to high school, high school to col8 lege, and school to internships and jobs. 

9 (d) APPLICATION.—An entity seeking an award 

10 under subsection (c) shall submit an application at such 

11 time, in such manner, and containing such information as 

12 the Director may require. The application shall include the 

13 following: 

14 (1) A description of the target population to be 

15 served by the research activity for which such an 

16 award is sought, including student subgroups de17 scribed in section 1111(b)(2)(B)(xi) of the Elemen18 tary and Secondary Education Act of 1965 (20 

19 U.S.C. 6311(b)(2)(B)(xi)), and students experi20 encing homelessness and children and youth in fos21 ter care. 

22 (2) A description of the process for recruitment 

23 and selection of students, educators, or local edu24 cational agencies to participate in such research ac25 tivity. 


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1 (3) A description of how such research activity 

2 may inform efforts to promote the engagement and 

3 achievement of students, including students from 

4 groups historically underrepresented in STEM, in 

5 prekindergarten through grade 12 in mathematical 

6 modeling and statistical modeling using problem7 based learning with contextualized data and com8 putational tools. 

9 (4) In the case of a proposal consisting of a 

10 partnership or partnerships with 1 or more local 

11 educational agencies and 1 or more researchers, a 

12 plan for establishing a sustained partnership that is 

13 jointly developed and managed, draws from the ca14 pacities of each partner, and is mutually beneficial. 

15 (e) PARTNERSHIPS.—In making awards under sub16 section (c), the Director shall encourage applications that 

17 include— 

18 (1) partnership with a nonprofit organization or 

19 an institution of higher education that has extensive 

20 experience and expertise in increasing the participa21 tion of students in prekindergarten through grade 

22 12 in mathematical modeling and statistical mod23 eling; 


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1 (2) partnership with a local educational agency, 

2 a consortium of local educational agencies, or Tribal 

3 educational agencies; 

4 (3) an assurance from school leaders to making 

5 reforms and activities proposed by the applicant a 

6 priority; 

7 (4) ways to address critical transitions, such as 

8 middle school to high school, high school to college, 

9 and school to internships and jobs; 

10 (5) input from education researchers and cog11 nitive scientists, as well as practitioners in research 

12 and industry, so that what is being taught is up-to13 date in terms of content and pedagogy; 

14 (6) a communications strategy for early con15 versations with parents, school leaders, school 

16 boards, community members, employers, and other 

17 stakeholders; and 

18 (7) resources for parents, school leaders, school 

19 boards, community members, and other stakeholders 

20 to build skills in modeling and analytics. 

21 (f) USE OF FUNDS.—An entity that receives an 

22 award under this section shall use the award for research 

23 and development activities to advance innovative ap24 proaches to support and sustain high-quality mathe25 matical modeling education in public schools, private 


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1 schools (including faith-based schools), or homeschools, in2 cluding statistical modeling, data science, operations re3 search, and computational thinking, which may include— 

4 (1) engaging prekindergarten through grade 12 

5 educators in professional learning opportunities to 

6 enhance mathematical modeling and statistical prob7 lem solving knowledge, and developing training and 

8 best practices to provide more interdisciplinary 

9 learning opportunities; 

10 (2) conducting research on curricula and teach11 ing practices that empower students to choose the 

12 mathematical, statistical, computational, and techno13 logical tools that they will apply to a problem, as is 

14 required in life and the workplace, rather than pre15 scribing a particular approach or method; 

16 (3) providing students with opportunities to ex17 plore and analyze real data sets from contexts that 

18 are meaningful to the students, which may include— 

19 (A) missing or incorrect values; 

20 (B) quantities of data that require choice 

21 and use of appropriate technology; 

22 (C) multiple data sets that require choices 

23 about which data are relevant to the current 

24 problem; and 


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1 (D) data of various types including quan2 tities, words, and images; 

3 (4) taking a school or district-wide approach to 

4 professional development in mathematical modeling 

5 and statistical modeling; 

6 (5) engaging rural local agencies; 

7 (6) supporting research on effective mathe8 matical modeling and statistical modeling teaching 

9 practices, including problem- and project-based 

10 learning, universal design for accessibility, and ru11 brics and mastery-based grading practices to assess 

12 student performance; 

13 (7) designing and developing pre-service and in14 service training resources to assist educators in 

15 adopting transdisciplinary teaching practices within 

16 mathematics and statistics courses; 

17 (8) coordinating with local partners to adapt 

18 mathematics and statistics teaching practices to le19 verage local natural, business, industry, and commu20 nity assets in order to support community-based 

21 learning; 

22 (9) providing hands-on training and research 

23 opportunities for mathematics and statistics edu24 cators at Federal laboratories, institutions of higher 

25 education, or in industry; 


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1 (10) developing mechanisms for partnerships 

2 between educators and employers to help educators 

3 and students make connections between their mathe4 matics and statistics projects and topics of relevance 

5 in today’s world; 

6 (11) designing and implementing professional 

7 development courses and experiences, including men8 toring for educators, that combine face-to-face and 

9 online experiences; 

10 (12) reduce gaps in access to learning opportu11 nities for students from groups historically under12 represented in STEM; 

13 (13) provide support and resources for students 

14 from groups historically underrepresented in STEM; 

15 (14) addressing critical transitions, such as 

16 middle school to high school, high school to college, 

17 and school to internships and jobs; 

18 (15) researching effective approaches for engag19 ing students from groups historically underrep20 resented in STEM; and 

21 (16) any other activity the Director determines 

22 will accomplish the goals of this section. 

23 (g) EVALUATIONS.—All proposals for awards under 

24 this section shall include an evaluation plan that includes 

25 the use of outcome oriented measures to assess the impact 


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1 and efficacy of the award. Each recipient of an award 

2 under this section shall include results from these evalua3 tive activities in annual and final project reports. 

4 (h) ACCOUNTABILITY AND DISSEMINATION.— 

5 (1) EVALUATION REQUIRED.—The Director 

6 shall evaluate the portfolio of awards made under 

7 this section. Such evaluation shall— 

8 (A) use a common set of benchmarks and 

9 tools to assess the results of research conducted 

10 under such awards and identify best practices; 

11 and 

12 (B) to the extent practicable, integrate the 

13 findings of research resulting from the activities 

14 funded through such awards with the findings 

15 of other research on student’s pursuit of de16 grees or careers in STEM. 

17 (2) REPORT ON EVALUATIONS.—Not later than 

18 180 days after the completion of the evaluation 

19 under paragraph (1), the Director shall submit to 

20 Congress and make widely available to the public a 

21 report that includes— 

22 (A) the results of the evaluation; and 

23 (B) any recommendations for administra24 tive and legislative action that could optimize 


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1 the effectiveness of the awards made under this 

2 section. 

3 (i) FUNDING.—$10,000,000 for each of the fiscal 

4 years 2025 through 2029 is authorized to be used by the 

5 Directorate for STEM Education of the National Science 

6 Foundation to carry out this section. 

7 SEC. 3. NASEM REPORT ON MATHEMATICAL AND STATIS8 TICAL MODELING EDUCATION IN PRE9 KINDERGARTEN THROUGH 12TH GRADE. 

10 (a) STUDY.—Not later than 180 days after the date 

11 of the enactment of this Act, the Director shall seek to 

12 enter into an agreement with the National Academies of 

13 Sciences, Engineering and Medicine (in this section re14 ferred to as ‘‘NASEM’’) (or if NASEM declines to enter 

15 into such an agreement, another appropriate entity) under 

16 which NASEM, or such other appropriate entity, agrees 

17 to conduct a study on the following: 

18 (1) Factors that enhance or barriers to the im19 plementation of mathematical modeling and statis20 tical modeling in elementary and secondary edu21 cation, including opportunities for and barriers to 

22 use modeling to integrate mathematical and statis23 tical ideas across the curriculum, including the fol24 lowing: 


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1 (A) Pathways in mathematical modeling 

2 and statistical problem solving from kinder3 garten to the workplace so that students are 

4 able to identify opportunities to use their school 

5 mathematics and statistics in a variety of jobs 

6 and life situations and so that employers can 

7 benefit from students’ school learning of data 

8 science, computational thinking, mathematics, 

9 statistics, and related subjects. 

10 (B) The role of community-based prob11 lems, service-based learning. and internships for 

12 connecting students with career preparatory ex13 periences. 

14 (C) Best practices in problem-, project-, 

15 performance-based learning and assessment. 

16 (2) Characteristics of teacher education pro17 grams that successfully prepare teachers to engage 

18 students in mathematical modeling and statistical 

19 modeling, as well as gaps and suggestions for build20 ing capacity in the pre-service and in-service teacher 

21 workforce. 

22 (3) Mechanisms for communication with stake23 holders, including parents, administrators, and the 

24 public, to promote understanding and knowledge of 


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1 the value of mathematical modeling and statistical 

2 modeling in education. 

3 (b) PUBLIC STAKEHOLDER MEETING.—In the course 

4 of completing the study described in subsection (a), 

5 NASEM or such other appropriate entity shall hold not 

6 less than one public meeting to obtain stakeholder input 

7 on the topics of such study. 

8 (c) REPORT.—The agreement under subsection (a) 

9 shall require NASEM, or such other appropriate entity, 

10 not later than 24 months after the effective date of such 

11 agreement, to submit to the Secretary of Education and 

12 the appropriate committees of jurisdiction of Congress a 

13 report containing— 

14 (1) the results of the study conducted under 

15 subsection (a); 

16 (2) recommendations to modernize the proc17 esses described in subsection (a)(1); and 

18 (3) recommendations for such legislative and 

19 administrative action as NASEM, or such other ap20 propriate entity, determines appropriate. 

21 (d) FUNDING.—From amounts appropriated or oth22 erwise made available for the Directorate for STEM Edu23 cation of the National Science Foundation, the Director 

24 shall allocate up to $1,000,000 for fiscal year 2024 to 

25 carry out this section. 


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1 SEC. 4. LIMITATIONS. 

2 (a) LIMITATION ON FUNDING.—Amounts made avail3 able to carry out sections 2 and 3 shall be derived from 

4 amounts appropriated or otherwise made available to the 

5 National Science Foundation. 

6 (b) SUNSET.—The authority to provide awards under 

7 this Act shall expire on September 30, 2028. 

Passed the House of Representatives September 23, 

2024. 

Attest: KEVIN F. MCCUMBER, 

Clerk. 


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