IB 

Union Calendar No. 42 

118TH CONGRESS 

1ST SESSION H. R. 1735 

[Report No. 118–62] 

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. 

IN THE HOUSE OF REPRESENTATIVES 

MARCH 23, 2023 

Ms. HOULAHAN (for herself and Mr. BAIRD) introduced the following bill; 

which was referred to the Committee on Science, Space, and Technology 

MAY 16, 2023 

Additional sponsors: Ms. LEE of Pennsylvania and Ms. STEVENS

MAY 16, 2023 

Reported with an amendment, committed to the Committee of the Whole 

House on the State of the Union, and ordered to be printed 

[Strike out all after the enacting clause and insert the part printed in italic] 

[For text of introduced bill, see copy of bill as introduced on March 23, 2023] 


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A BILL 

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. 


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

3 SECTION 1. SHORT TITLE. 

4 This Act may be cited as the ‘‘Mathematical and Sta5 tistical Modeling Education Act’’. 

6 SEC. 2. MATHEMATICAL AND STATISTICAL MODELING EDU7 CATION. 

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

9 (1) The mathematics taught in schools, including 

10 statistical problem solving and data science, is not 

11 keeping pace with the rapidly evolving needs of the 

12 public and private sector, resulting in a STEM skills 

13 shortage and employers needing to expend resources to 

14 train and upskill employees. 

15 (2) According to the Bureau of Labor Statistics, 

16 the United States will need 1,000,000 additional 

17 STEM professionals than it is on track to produce in 

18 the coming decade. 

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

20 almost every workplace, relies on the ability to work 

21 in teams and use computational tools to do mathe22 matical and statistical problem solving. 

23 (4) Many STEM occupations offer higher wages, 

24 more opportunities for advancement, and a higher de25 gree of job security than non-STEM jobs. 


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1 (5) The STEM workforce relies on computational 

2 and data-driven discovery, decision making, and pre3 dictions, from models that often must quantify uncer4 tainty, as in weather predictions, spread of disease, or 

5 financial forecasting. 

6 (6) Most fields, including analytics, science, eco7 nomics, publishing, marketing, actuarial science, op8 erations research, engineering, and medicine, require 

9 data savvy, including the ability to select reliable 

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

11 recognize and quantify uncertainty in data, visualize 

12 and analyze data, and use data to develop under13 standing or make predictions. 

14 (7) Rapidly emerging fields, such as artificial 

15 intelligence, machine learning, quantum computing 

16 and quantum information, all rely on mathematical 

17 and statistical concepts, which are critical to prove 

18 under what circumstances an algorithm or experi19 ment will work and when it will fail. 

20 (8) Military academies have a long tradition in 

21 teaching mathematical modeling and would benefit 

22 from the ability to recruit students with this expertise 

23 from their other school experiences. 

24 (9) Mathematical modeling has been a strong 

25 educational priority globally, especially in China, 


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1 where participation in United States mathematical 

2 modeling challenges in high school and higher edu3 cation is orders of magnitude higher than in the 

4 United States, and Chinese teams are taking a major5 ity of the prizes. 

6 (10) Girls participate in mathematical modeling 

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

8 in traditional mathematical competitions girls par9 ticipate less and drop out at every stage. Students cite 

10 opportunity for teamwork, using mathematics and 

11 statistics in meaningful contexts, ability to use com12 putation, and emphasis on communication as reasons 

13 for continued participation in modeling challenges. 

14 (b) DEFINITIONS.—In this section: 

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

16 Director of the National Science Foundation. 

17 (2) FEDERAL LABORATORY.—The term ‘‘Federal 

18 laboratory’’ has the meaning given such term in sec19 tion 4 of the Stevenson-Wydler Technology Innovation 

20 Act of 1980 (15 U.S.C. 3703). 

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

22 means the National Science Foundation. 

23 (4) INSTITUTION OF HIGHER EDUCATION.—The 

24 term ‘‘institution of higher education’’ has the meanVerDate Sep 11 2014 22:42 May 16, 2023 Jkt 039200 PO 00000 Frm 00005 Fmt 6652 Sfmt 6203 E:\BILLS\H1735.RH H1735

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1 ing given such term in section 101(a) of the Higher 

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

3 (5) MATHEMATICAL MODELING.—The term 

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

5 term in the 2019 Guidelines to Assessment and In6 struction in Mathematical Modeling Education 

7 (GAIMME) report, 2nd edition. 

8 (6) OPERATIONS RESEARCH.—The term ‘‘oper9 ations research’’ means the application of scientific 

10 methods to the management and administration of or11 ganized military, governmental, commercial, and in12 dustrial processes to maximize operational efficiency. 

13 (7) STATISTICAL MODELING.—The term ‘‘statis14 tical modeling’’ has the meaning given the term in the 

15 2021 Guidelines to Assessment and Instruction in 

16 Statistical Education (GAISE II) report. 

17 (8) STEM.—The term ‘‘STEM’’ means the aca18 demic and professional disciplines of science, tech19 nology, engineering, and mathematics, including com20 puter science. 

21 (c) PREPARING EDUCATORS TO ENGAGE STUDENTS IN

22 MATHEMATICAL AND STATISTICAL MODELING.—The Direc23 tor shall make awards on a merit-reviewed, competitive 

24 basis to institutions of higher education, and nonprofit or25 ganizations (or a consortium thereof) for research and deVerDate Sep 11 2014 22:42 May 16, 2023 Jkt 039200 PO 00000 Frm 00006 Fmt 6652 Sfmt 6203 E:\BILLS\H1735.RH H1735

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1 velopment to advance innovative approaches to support and 

2 sustain high-quality mathematical modeling education in 

3 schools that are private, faith-based, or homeschools, or op4 erated by local educational agencies, including statistical 

5 modeling, data science, operations research, and computa6 tional thinking. The Director shall encourage applicants to 

7 form partnerships to address critical transitions, such as 

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

9 school to internships and jobs. 

10 (d) APPLICATION.—An entity seeking an award under 

11 subsection (c) shall submit an application at such time, in 

12 such manner, and containing such information as the Di13 rector may require. The application shall include the fol14 lowing: 

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

16 served by the research activity for which such an 

17 award is sought, including student subgroups de18 scribed in section 1111(b)(2)(B)(xi) of the Elementary 

19 and Secondary Education Act of 1965 (20 U.S.C. 

20 6311(b)(2)(B)(xi)), and students experiencing home21 lessness and children and youth in foster 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 part10 nership or partnerships with 1 or more local edu11 cational agencies and 1 or more researchers, a plan 

12 for establishing a sustained partnership that is joint13 ly developed and managed, draws from the capacities 

14 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 12 

22 in mathematical modeling and statistical modeling; 

23 (2) partnership with a local educational agency, 

24 a consortium of local educational agencies, or Tribal 

25 educational agencies; 


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1 (3) an assurance from school leaders to making 

2 reforms and activities proposed by the applicant a 

3 priority; 

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

5 middle school to high school, high school to college, 

6 and school to internships and jobs; 

7 (5) input from education researchers and cog8 nitive scientists, as well as practitioners in research 

9 and industry, so that what is being taught is up-to10 date in terms of content and pedagogy; 

11 (6) a communications strategy for early con12 versations with parents, school leaders, school boards, 

13 community members, employers, and other stake14 holders; and 

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

16 boards, community members, and other stakeholders 

17 to build skills in modeling and analytics. 

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

19 under this section shall use the award for research and de20 velopment activities to advance innovative approaches to 

21 support and sustain high-quality mathematical modeling 

22 education in public schools, private schools (including faith23 based schools), or homeschools, including statistical mod24 eling, data science, operations research, and computational 

25 thinking, which may include— 


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1 (1) engaging prekindergarten through grade 12 

2 educators in professional learning opportunities to 

3 enhance mathematical modeling and statistical prob4 lem solving knowledge, and developing training and 

5 best practices to provide more interdisciplinary learn6 ing opportunities; 

7 (2) conducting research on curricula and teach8 ing practices that empower students to choose the 

9 mathematical, statistical, computational, and techno10 logical tools that they will apply to a problem, as is 

11 required in life and the workplace, rather than pre12 scribing a particular approach or method; 

13 (3) providing students with opportunities to ex14 plore and analyze real data sets from contexts that 

15 are meaningful to the students, which may include— 

16 (A) missing or incorrect values; 

17 (B) quantities of data that require choice 

18 and use of appropriate technology; 

19 (C) multiple data sets that require choices 

20 about which data are relevant to the current 

21 problem; and 

22 (D) data of various types including quan23 tities, words, and images; 


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

2 professional development in mathematical modeling 

3 and statistical modeling; 

4 (5) engaging rural local agencies; 

5 (6) supporting research on effective mathematical 

6 modeling and statistical modeling teaching practices, 

7 including problem- and project-based learning, uni8 versal design for accessibility, and rubrics and mas9 tery-based grading practices to assess student per10 formance; 

11 (7) designing and developing pre-service and in12 service training resources to assist educators in adopt13 ing transdisciplinary teaching practices within math14 ematics and statistics courses; 

15 (8) coordinating with local partners to adapt 

16 mathematics and statistics teaching practices to lever17 age local natural, business, industry, and community 

18 assets in order to support community-based learning; 

19 (9) providing hands-on training and research 

20 opportunities for mathematics and statistics educators 

21 at Federal laboratories, institutions of higher edu22 cation, or in industry; 

23 (10) developing mechanisms for partnerships be24 tween educators and employers to help educators and 

25 students make connections between their mathematics 


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1 and statistics projects and topics of relevance in to2 day’s world; 

3 (11) designing and implementing professional 

4 development courses and experiences, including men5 toring for educators, that combine face-to-face and on6 line experiences; 

7 (12) reduce gaps in access to learning opportuni8 ties for students from groups historically underrep9 resented in STEM; 

10 (13) provide support and resources for students 

11 from groups historically underrepresented in STEM; 

12 (14) addressing critical transitions, such as mid13 dle school to high school, high school to college, and 

14 school to internships and jobs; 

15 (15) researching effective approaches for engag16 ing students from groups historically underrep17 resented in STEM; and 

18 (16) any other activity the Director determines 

19 will accomplish the goals of this section. 

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

21 this section shall include an evaluation plan that includes 

22 the use of outcome oriented measures to assess the impact 

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

24 under this section shall include results from these evaluative 

25 activities in annual and final projects. 


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1 (h) ACCOUNTABILITY AND DISSEMINATION.— 

2 (1) EVALUATION REQUIRED.—The Director shall 

3 evaluate the portfolio of awards made under this sec4 tion. Such evaluation shall— 

5 (A) use a common set of benchmarks and 

6 tools to assess the results of research conducted 

7 under such awards and identify best practices; 

8 and 

9 (B) to the extent practicable, integrate the 

10 findings of research resulting from the activities 

11 funded through such awards with the findings of 

12 other research on student’s pursuit of degrees or 

13 careers in STEM. 

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

15 180 days after the completion of the evaluation under 

16 paragraph (1), the Director shall submit to Congress 

17 and make widely available to the public a report that 

18 includes— 

19 (A) the results of the evaluation; and 

20 (B) any recommendations for administra21 tive and legislative action that could optimize 

22 the effectiveness of the awards made under this 

23 section. 

24 (i) FUNDING.—From amounts appropriated or other25 wise made available for the Directorate for STEM EduVerDate Sep 11 2014 22:42 May 16, 2023 Jkt 039200 PO 00000 Frm 00013 Fmt 6652 Sfmt 6203 E:\BILLS\H1735.RH H1735

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1 cation of the National Science Foundation, the Director 

2 shall allocate up to $10,000,000 for each of fiscal years 2024 

3 through 2028 to carry out this section. 

4 SEC. 3. NASEM REPORT ON MATHEMATICAL AND STATIS5 TICAL MODELING EDUCATION IN PREKINDER6 GARTEN THROUGH 12TH GRADE. 

7 (a) STUDY.—Not later than 60 days after the date of 

8 enactment of this Act, the Director shall seek to enter into 

9 an agreement with the National Academies of Sciences, En10 gineering and Medicine (in this section referred to as 

11 ‘‘NASEM’’) (or if NASEM declines to enter into such an 

12 agreement, another appropriate entity) under which 

13 NASEM, or such other appropriate entity, agrees to conduct 

14 a study on the following: 

15 (1) Factors that enhance or barriers to the im16 plementation of mathematical modeling and statis17 tical modeling in elementary and secondary edu18 cation, including opportunities for and barriers to use 

19 modeling to integrate mathematical and statistical 

20 ideas across the curriculum, including the following: 

21 (A) Pathways in mathematical modeling 

22 and statistical problem solving from kinder23 garten to the workplace so that students are able 

24 to identify opportunities to use their school 

25 mathematics and statistics in a variety of jobs 


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1 and life situations and so that employers can 

2 benefit from students’ school learning of data 

3 science, computational thinking, mathematics, 

4 statistics, and related subjects. 

5 (B) The role of community-based problems, 

6 service-based learning. and internships for con7 necting students with career preparatory experi8 ences. 

9 (C) Best practices in problem-, project-, per10 formance-based learning and assessment. 

11 (2) Characteristics of teacher education programs 

12 that successfully prepare teachers to engage students 

13 in mathematical modeling and statistical modeling, 

14 as well as gaps and suggestions for building capacity 

15 in the pre-service and in-service teacher workforce. 

16 (3) Mechanisms for communication with stake17 holders, including parents, administrators, and the 

18 public, to promote understanding and knowledge of 

19 the value of mathematical modeling and statistical 

20 modeling in education. 

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

22 of completing the study described in subsection (a), NASEM 

23 or such other appropriate entity shall hold not less than 

24 one public meeting to obtain stakeholder input on the topics 

25 of such study. 


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

2 shall require NASEM, or such other appropriate entity, not 

3 later than 24 months after the effective date of such agree4 ment, to submit to the Secretary of Education and the ap5 propriate committees of jurisdiction of Congress a report 

6 containing— 

7 (1) the results of the study conducted under sub8 section (a); 

9 (2) recommendations to modernize the processes 

10 described in subsection (a)(1); and 

11 (3) recommendations for such legislative and ad12 ministrative action as NASEM, or such other appro13 priate entity, determines appropriate. 

14 (d) FUNDING.—From amounts appropriated or other15 wise made available for the Directorate for STEM Edu16 cation of the National Science Foundation, the Director 

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

18 out this section. 

19 SEC. 4. LIMITATIONS. 

20 (a) LIMITATION ON FUNDING.—Amounts made avail21 able to carry out sections 2 and 3 shall be derived from 

22 amounts appropriated or otherwise made available to the 

23 National Science Foundation. 

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

25 this Act shall expire on September 30, 2028. 


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Union Calendar No. 42 

118TH CONGRESS 

1ST SESSION H. R. 1735 

[Report No. 118–62] 

A BILL 

To coordinate Federal research and development efand for other purposes. disciplinary exploration, and career connections, formance-based learning and assessment, inter- putational thinking, problem, project, and per- tistical modeling, including data-driven and com- STEM education through mathematical and sta- forts focused on modernizing mathematics in 

MAY 16, 2023 

Reported with an amendment, committed to the Comand ordered to be printed mittee of the Whole House on the State of the Union, 


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