I 

118TH CONGRESS 

1ST SESSION 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. 

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 

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. 

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’’. 


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1 SEC. 2. MATHEMATICAL AND STATISTICAL MODELING EDU2 CATION. 

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

4 (1) The mathematics taught in schools, includ5 ing statistical problem solving and data science, is 

6 not keeping pace with the rapidly evolving needs of 

7 the public and private sector, resulting in a STEM 

8 skills shortage and employers needing to expend re9 sources to train and upskill employees. 

10 (2) According to the Bureau of Labor Statis11 tics, the United States will need 1,000,000 addi12 tional STEM professionals than it is on track to 

13 produce in the coming decade. 

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

15 in almost every workplace, relies on the ability to 

16 work in teams and use computational tools to do 

17 mathematical and statistical problem solving. 

18 (4) Many STEM occupations offer higher 

19 wages, more opportunities for advancement, and a 

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

21 (5) The STEM workforce relies on computa22 tional and data-driven discovery, decision making, 

23 and predictions, from models that often must quan24 tify uncertainty, as in weather predictions, spread of 

25 disease, or financial forecasting. 


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1 (6) Most fields, including analytics, science, eco2 nomics, publishing, marketing, actuarial science, op3 erations research, engineering, and medicine, require 

4 data savvy, including the ability to select reliable 

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

6 recognize and quantify uncertainty in data, visualize 

7 and analyze data, and use data to develop under8 standing or make predictions. 

9 (7) Rapidly emerging fields, such as artificial 

10 intelligence, machine learning, quantum computing 

11 and quantum information, all rely on mathematical 

12 and statistical concepts, which are critical to prove 

13 under what circumstances an algorithm or experi14 ment will work and when it will fail. 

15 (8) Military academies have a long tradition in 

16 teaching mathematical modeling and would benefit 

17 from the ability to recruit students with this exper18 tise from their other school experiences. 

19 (9) Mathematical modeling has been a strong 

20 educational priority globally, especially in China, 

21 where participation in United States mathematical 

22 modeling challenges in high school and higher edu23 cation is orders of magnitude higher than in the 

24 United States, and Chinese teams are taking a ma25 jority of the prizes. 


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1 (10) Girls participate in mathematical modeling 

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

3 in traditional mathematical competitions girls par4 ticipate less and drop out at every stage. Students 

5 cite opportunity for teamwork, using mathematics 

6 and statistics in meaningful contexts, ability to use 

7 computation, and emphasis on communication as 

8 reasons for continued participation in modeling chal9 lenges. 

10 (b) DEFINITIONS.—In this section: 

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

12 the Director of the National Science Foundation. 

13 (2) FEDERAL LABORATORY.—The term ‘‘Fed14 eral laboratory’’ has the meaning given such term in 

15 section 4 of the Stevenson-Wydler Technology Inno16 vation Act of 1980 (15 U.S.C. 3703). 

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

18 means the National Science Foundation. 

19 (4) INSTITUTION OF HIGHER EDUCATION.—The 

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

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

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

23 (5) MATHEMATICAL MODELING.—The term 

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

25 term in the 2019 Guidelines to Assessment and InVerDate Sep 11 2014 01:02 Mar 24, 2023 Jkt 039200 PO 00000 Frm 00004 Fmt 6652 Sfmt 6201 E:\BILLS\H1735.IH H1735

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1 struction in Mathematical Modeling Education 

2 (GAIMME) report, 2nd edition. 

3 (6) OPERATIONS RESEARCH.—The term ‘‘oper4 ations research’’ means the application of scientific 

5 methods to the management and administration of 

6 organized military, governmental, commercial, and 

7 industrial processes to maximize operational effi8 ciency. 

9 (7) STATISTICAL MODELING.—The term ‘‘sta10 tistical modeling’’ has the meaning given the term in 

11 the 2021 Guidelines to Assessment and Instruction 

12 in Statistical Education (GAISE II) report. 

13 (8) STEM.—The term ‘‘STEM’’ means the aca14 demic and professional disciplines of science, tech15 nology, engineering, and mathematics. 

16 (c) PREPARING EDUCATORS TO ENGAGE STUDENTS

17 IN MATHEMATICAL AND STATISTICAL MODELING.—The 

18 Director shall provide grants on a merit-reviewed, com19 petitive basis to institutions of higher education, and non20 profit organizations (or a consortium thereof) for research 

21 and development to advance innovative approaches to sup22 port and sustain high-quality mathematical modeling edu23 cation in schools operated by local education agencies, in24 cluding statistical modeling, data science, operations re25 search, and computational thinking. The Director shall enVerDate Sep 11 2014 01:02 Mar 24, 2023 Jkt 039200 PO 00000 Frm 00005 Fmt 6652 Sfmt 6201 E:\BILLS\H1735.IH H1735

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1 courage applicants to form partnerships to address critical 

2 transitions, such as middle school to high school, high 

3 school to college, and school to internships and jobs. 

4 (d) APPLICATION.—An entity seeking a grant under 

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

6 in such manner, and containing such information as the 

7 Director may require. The application shall include the fol8 lowing: 

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

10 served by the research activity for which such grant 

11 is sought, including student subgroups described in 

12 section 1111(b)(2)(B)(xi) of the Elementary and 

13 Secondary Education Act of 1965 (20 U.S.C. 

14 6311(b)(2)(B)(xi)), and students experiencing home15 lessness and children and youth in foster care. 

16 (2) A description of the process for recruitment 

17 and selection of students, educators, or local edu18 cational agencies to participate in such research ac19 tivity. 

20 (3) A description of how such research activity 

21 may inform efforts to promote the engagement and 

22 achievement of students in prekindergarten through 

23 grade 12 in mathematical modeling and statistical 

24 modeling using problem-based learning with contex25 tualized data and computational tools. 


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

2 partnership or partnerships with 1 or more local 

3 educational agencies and 1 or more researchers, a 

4 plan for establishing a sustained partnership that is 

5 jointly developed and managed, draws from the ca6 pacities of each partner, and is mutually beneficial. 

7 (e) PARTNERSHIPS.—In awarding grants under sub8 section (c), the Director shall encourage applications that 

9 include— 

10 (1) partnership with a nonprofit organization or 

11 an institution of higher education that has extensive 

12 experience and expertise in increasing the participa13 tion of students in prekindergarten through grade 

14 12 in mathematical modeling and statistical mod15 eling; 

16 (2) partnership with a local educational agency, 

17 a consortium of local educational agencies, or Tribal 

18 educational agencies; 

19 (3) an assurance from school leaders to making 

20 reforms and activities proposed by the applicant a 

21 priority; 

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

23 middle school to high school, high school to college, 

24 and school to internships and jobs; 


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1 (5) input from education researchers and cog2 nitive scientists, as well as practitioners in research 

3 and industry, so that what is being taught is up-to4 date in terms of content and pedagogy; 

5 (6) a communications strategy for early con6 versations with parents, school leaders, school 

7 boards, community members, employers, and other 

8 stakeholders; and 

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

10 boards, community members, and other stakeholders 

11 to build skills in modeling and analytics. 

12 (f) USE OF FUNDS.—An entity that receives a grant 

13 under this section shall use the grant funds for research 

14 and development activities to advance innovative ap15 proaches to support and sustain high-quality mathe16 matical modeling education in public schools, including 

17 statistical modeling, data science, operations research, and 

18 computational thinking, which may include— 

19 (1) engaging prekindergarten through grade 12 

20 educators in professional learning opportunities to 

21 enhance mathematical modeling and statistical prob22 lem solving knowledge, and developing training and 

23 best practices to provide more interdisciplinary 

24 learning opportunities; 


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1 (2) conducting research on curricula and teach2 ing practices that empower students to choose the 

3 mathematical, statistical, computational, and techno4 logical tools that they will apply to a problem, as is 

5 required in life and the workplace, rather than pre6 scribing a particular approach or method; 

7 (3) providing students with opportunities to ex8 plore and analyze real data sets from contexts that 

9 are meaningful to the students, which may include— 

10 (A) missing or incorrect values; 

11 (B) quantities of data that require choice 

12 and use of appropriate technology; 

13 (C) multiple data sets that require choices 

14 about which data are relevant to the current 

15 problem; and 

16 (D) data of various types including quan17 tities, words, and images; 

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

19 professional development in mathematical modeling 

20 and statistical modeling; 

21 (5) engaging rural local agencies; 

22 (6) supporting research on effective mathe23 matical modeling and statistical modeling teaching 

24 practices, including problem- and project-based 

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1 brics and mastery-based grading practices to assess 

2 student performance; 

3 (7) designing and developing pre-service and in4 service training resources to assist educators in 

5 adopting transdisciplinary teaching practices within 

6 mathematics and statistics courses; 

7 (8) coordinating with local partners to adapt 

8 mathematics and statistics teaching practices to le9 verage local natural, business, industry, and commu10 nity assets in order to support community-based 

11 learning; 

12 (9) providing hands-on training and research 

13 opportunities for mathematics and statistics edu14 cators at Federal laboratories, institutions of higher 

15 education, or in industry; 

16 (10) developing mechanisms for partnerships 

17 between educators and employers to help educators 

18 and students make connections between their mathe19 matics and statistics projects and topics of relevance 

20 in today’s world; 

21 (11) designing and implementing professional 

22 development courses and experiences, including men23 toring for educators, that combine face-to-face and 

24 online experiences; 


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1 (12) addressing critical transitions, such as 

2 middle school to high school, high school to college, 

3 and school to internships and jobs; and 

4 (13) any other activity the Director determines 

5 will accomplish the goals of this section. 

6 (g) EVALUATIONS.—All proposals for grants under 

7 this section shall include an evaluation plan that includes 

8 the use of outcome oriented measures to assess the impact 

9 and efficacy of the grant. Each recipient of a grant under 

10 this section shall include results from these evaluative ac11 tivities in annual and final projects. 

12 (h) ACCOUNTABILITY AND DISSEMINATION.— 

13 (1) EVALUATION REQUIRED.—The Director 

14 shall evaluate the portfolio of grants awarded under 

15 this section. Such evaluation shall— 

16 (A) use a common set of benchmarks and 

17 tools to assess the results of research conducted 

18 under such grants and identify best practices; 

19 and 

20 (B) to the extent practicable, integrate the 

21 findings of research resulting from the activities 

22 funded through such grants with the findings of 

23 other research on student’s pursuit of degrees 

24 or careers in STEM. 


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

2 180 days after the completion of the evaluation 

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

4 Congress and make widely available to the public a 

5 report that includes— 

6 (A) the results of the evaluation; and 

7 (B) any recommendations for administra8 tive and legislative action that could optimize 

9 the effectiveness of the grants awarded under 

10 this section. 

11 (i) AUTHORIZATION OF APPROPRIATIONS.—For each 

12 of fiscal years 2024 through 2028, there are authorized 

13 to be appropriated to the National Science Foundation 

14 $10,000,000 to carry out the activities under this section. 

15 SEC. 3. NASEM REPORT ON MATHEMATICAL AND STATIS16 TICAL MODELING EDUCATION IN PRE17 KINDERGARTEN THROUGH 12TH GRADE. 

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

19 of enactment of this Act, the Director shall seek to enter 

20 into an agreement with the National Academies of 

21 Sciences, Engineering and Medicine (in this section re22 ferred to as ‘‘NASEM’’) (or if NASEM declines to enter 

23 into such an agreement, another appropriate entity) under 

24 which NASEM, or such other appropriate entity, agrees 

25 to conduct a study on the following: 


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1 (1) Factors that enhance or barriers to the im2 plementation of mathematical modeling and statis3 tical modeling in elementary and secondary edu4 cation, including opportunities for and barriers to 

5 use modeling to integrate mathematical and statis6 tical ideas across the curriculum, including the fol7 lowing: 

8 (A) Pathways in mathematical modeling 

9 and statistical problem solving from kinder10 garten to the workplace so that students are 

11 able to identify opportunities to use their school 

12 mathematics and statistics in a variety of jobs 

13 and life situations and so that employers can 

14 benefit from students’ school learning of data 

15 science, computational thinking, mathematics, 

16 statistics, and related subjects. 

17 (B) The role of community-based prob18 lems, service-based learning. and internships for 

19 connecting students with career preparatory ex20 periences. 

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

22 performance-based learning and assessment. 

23 (2) Characteristics of teacher education pro24 grams that successfully prepare teachers to engage 

25 students in mathematical modeling and statistical 


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1 modeling, as well as gaps and suggestions for build2 ing capacity in the pre-service and in-service teacher 

3 workforce. 

4 (3) Mechanisms for communication with stake5 holders, including parents, administrators, and the 

6 public, to promote understanding and knowledge of 

7 the value of mathematical modeling and statistical 

8 modeling in education. 

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

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

11 NASEM or such other appropriate entity shall hold not 

12 less than one public meeting to obtain stakeholder input 

13 on the topics of such study. 

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

15 shall require NASEM, or such other appropriate entity, 

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

17 agreement, to submit to the Secretary of Education and 

18 the appropriate committees of jurisdiction of Congress a 

19 report containing— 

20 (1) the results of the study conducted under 

21 subsection (a); 

22 (2) recommendations to modernize the proc23 esses described in subsection (a)(1); and 


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1 (3) recommendations for such legislative and 

2 administrative action as NASEM, or such other ap3 propriate entity, determines appropriate. 

4 (d) AUTHORIZATION OF APPROPRIATIONS.—For fis5 cal year 2024, there are authorized to be appropriated to 

6 the National Science Foundation $1,000,000 to carry out 

7 the activities under this section. 

Æ 


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