Us Congress 2025-2026 Regular Session

Us Congress House Bill HB730 Compare Versions

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Old	New		Differences
	1	+	I
1	2		119THCONGRESS
2	3		1
3	4		STSESSION H. R. 730
4		-	AN ACT
	5	+	To coordinate Federal research and development efforts focused on modern-
	6	+	izing mathematics in STEM education through mathematical and statis-
	7	+	tical modeling, including data-driven and computational thinking, prob-
	8	+	lem, project, and performance-based learning and assessment, inter-
	9	+	disciplinary exploration, and career connections, and for other purposes.
	10	+	IN THE HOUSE OF REPRESENTATIVES
	11	+	JANUARY24, 2025
	12	+	Ms. H
	13	+	OULAHAN(for herself and Mr. BAIRD) introduced the following bill;
	14	+	which was referred to the Committee on Science, Space, and Technology
	15	+	A BILL
5	16		To coordinate Federal research and development efforts fo-
6	17		cused on modernizing mathematics in STEM education
7	18		through mathematical and statistical modeling, including
8	19		data-driven and computational thinking, problem,
9	20		project, and performance-based learning and assessment,
10	21		interdisciplinary exploration, and career connections, and
11		-	for other purposes. 2
12		-	•HR 730 EH
	22	+	for other purposes.
13	23		Be it enacted by the Senate and House of Representa-1
14	24		tives of the United States of America in Congress assembled, 2
15	25		SECTION 1. SHORT TITLE. 3
16	26		This Act may be cited as the ‘‘Mathematical and Sta-4
17	27		tistical Modeling Education Act’’. 5
18		-	SEC. 2. MATHEMATICAL AND STATISTICAL MODELING EDU-6
19		-	CATION. 7
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	30	+	•HR 730 IH
	31	+	SEC. 2. MATHEMATICAL AND STATISTICAL MODELING EDU-1
	32	+	CATION. 2
20	33		(a) F
21		-	INDINGS.—Congress finds the following: 8
22		-	(1) The mathematics taught in schools, includ-9
23		-	ing statistical problem solving and data science, is 10
24		-	not keeping pace with the rapidly evolving needs of 11
25		-	the public and private sector, resulting in a STEM 12
26		-	skills shortage and employers needing to expend re-13
27		-	sources to train and upskill employees. 14
28		-	(2) According to the Bureau of Labor Statis-15
29		-	tics, the United States will need 1,000,000 addi-16
30		-	tional STEM professionals than it is on track to 17
31		-	produce in the coming decade. 18
32		-	(3) The field of data science, which is relevant 19
33		-	in almost every workplace, relies on the ability to 20
34		-	work in teams and use computational tools to do 21
35		-	mathematical and statistical problem solving. 22
36		-	(4) Many STEM occupations offer higher 23
37		-	wages, more opportunities for advancement, and a 24
38		-	higher degree of job security than non-STEM jobs. 25 3
39		-	•HR 730 EH
40		-	(5) The STEM workforce relies on computa-1
41		-	tional and data-driven discovery, decision making, 2
42		-	and predictions, from models that often must quan-3
43		-	tify uncertainty, as in weather predictions, spread of 4
44		-	disease, or financial forecasting. 5
45		-	(6) Most fields, including analytics, science, eco-6
46		-	nomics, publishing, marketing, actuarial science, op-7
47		-	erations research, engineering, and medicine, require 8
48		-	data savvy, including the ability to select reliable 9
49		-	sources of data, identify and remove errors in data, 10
50		-	recognize and quantify uncertainty in data, visualize 11
51		-	and analyze data, and use data to develop under-12
52		-	standing or make predictions. 13
53		-	(7) Rapidly emerging fields, such as artificial 14
54		-	intelligence, machine learning, quantum computing 15
55		-	and quantum information, all rely on mathematical 16
56		-	and statistical concepts, which are critical to prove 17
57		-	under what circumstances an algorithm or experi-18
58		-	ment will work and when it will fail. 19
59		-	(8) Military academies have a long tradition in 20
60		-	teaching mathematical modeling and would benefit 21
61		-	from the ability to recruit students with this exper-22
62		-	tise from their other school experiences. 23
63		-	(9) Mathematical modeling has been a strong 24
64		-	educational priority globally, especially in China, 25 4
65		-	•HR 730 EH
66		-	where participation in United States mathematical 1
67		-	modeling challenges in high school and higher edu-2
68		-	cation is orders of magnitude higher than in the 3
69		-	United States, and Chinese teams are taking a ma-4
70		-	jority of the prizes. 5
71		-	(10) Girls participate in mathematical modeling 6
72		-	challenges at all levels at similar levels as boys, while 7
73		-	in traditional mathematical competitions girls par-8
74		-	ticipate less and drop out at every stage. Students 9
75		-	cite opportunity for teamwork, using mathematics 10
76		-	and statistics in meaningful contexts, ability to use 11
77		-	computation, and emphasis on communication as 12
78		-	reasons for continued participation in modeling chal-13
79		-	lenges. 14
	34	+	INDINGS.—Congress finds the following: 3
	35	+	(1) The mathematics taught in schools, includ-4
	36	+	ing statistical problem solving and data science, is 5
	37	+	not keeping pace with the rapidly evolving needs of 6
	38	+	the public and private sector, resulting in a STEM 7
	39	+	skills shortage and employers needing to expend re-8
	40	+	sources to train and upskill employees. 9
	41	+	(2) According to the Bureau of Labor Statis-10
	42	+	tics, the United States will need 1,000,000 addi-11
	43	+	tional STEM professionals than it is on track to 12
	44	+	produce in the coming decade. 13
	45	+	(3) The field of data science, which is relevant 14
	46	+	in almost every workplace, relies on the ability to 15
	47	+	work in teams and use computational tools to do 16
	48	+	mathematical and statistical problem solving. 17
	49	+	(4) Many STEM occupations offer higher 18
	50	+	wages, more opportunities for advancement, and a 19
	51	+	higher degree of job security than non-STEM jobs. 20
	52	+	(5) The STEM workforce relies on computa-21
	53	+	tional and data-driven discovery, decision making, 22
	54	+	and predictions, from models that often must quan-23
	55	+	tify uncertainty, as in weather predictions, spread of 24
	56	+	disease, or financial forecasting. 25
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	59	+	•HR 730 IH
	60	+	(6) Most fields, including analytics, science, eco-1
	61	+	nomics, publishing, marketing, actuarial science, op-2
	62	+	erations research, engineering, and medicine, require 3
	63	+	data savvy, including the ability to select reliable 4
	64	+	sources of data, identify and remove errors in data, 5
	65	+	recognize and quantify uncertainty in data, visualize 6
	66	+	and analyze data, and use data to develop under-7
	67	+	standing or make predictions. 8
	68	+	(7) Rapidly emerging fields, such as artificial 9
	69	+	intelligence, machine learning, quantum computing 10
	70	+	and quantum information, all rely on mathematical 11
	71	+	and statistical concepts, which are critical to prove 12
	72	+	under what circumstances an algorithm or experi-13
	73	+	ment will work and when it will fail. 14
	74	+	(8) Military academies have a long tradition in 15
	75	+	teaching mathematical modeling and would benefit 16
	76	+	from the ability to recruit students with this exper-17
	77	+	tise from their other school experiences. 18
	78	+	(9) Mathematical modeling has been a strong 19
	79	+	educational priority globally, especially in China, 20
	80	+	where participation in United States mathematical 21
	81	+	modeling challenges in high school and higher edu-22
	82	+	cation is orders of magnitude higher than in the 23
	83	+	United States, and Chinese teams are taking a ma-24
	84	+	jority of the prizes. 25
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	87	+	•HR 730 IH
	88	+	(10) Girls participate in mathematical modeling 1
	89	+	challenges at all levels at similar levels as boys, while 2
	90	+	in traditional mathematical competitions girls par-3
	91	+	ticipate less and drop out at every stage. Students 4
	92	+	cite opportunity for teamwork, using mathematics 5
	93	+	and statistics in meaningful contexts, ability to use 6
	94	+	computation, and emphasis on communication as 7
	95	+	reasons for continued participation in modeling chal-8
	96	+	lenges. 9
80	97		(b) D
81		-	EFINITIONS.—In this section: 15
	98	+	EFINITIONS.—In this section: 10
82	99		(1) D
83		-	IRECTOR.—The term ‘‘Director’’ means 16
84		-	the Director of the National Science Foundation. 17
	100	+	IRECTOR.—The term ‘‘Director’’ means 11
	101	+	the Director of the National Science Foundation. 12
85	102		(2) F
86		-	EDERAL LABORATORY .—The term ‘‘Fed-18
87		-	eral laboratory’’ has the meaning given such term in 19
88		-	section 4 of the Stevenson-Wydler Technology Inno-20
89		-	vation Act of 1980 (15 U.S.C. 3703). 21
	103	+	EDERAL LABORATORY .—The term ‘‘Fed-13
	104	+	eral laboratory’’ has the meaning given such term in 14
	105	+	section 4 of the Stevenson-Wydler Technology Inno-15
	106	+	vation Act of 1980 (15 U.S.C. 3703). 16
90	107		(3) F
91		-	OUNDATION.—The term ‘‘Foundation’’ 22
92		-	means the National Science Foundation. 23
	108	+	OUNDATION.—The term ‘‘Foundation’’ 17
	109	+	means the National Science Foundation. 18
93	110		(4) I
94		-	NSTITUTION OF HIGHER EDUCATION .—The 24
95		-	term ‘‘institution of higher education’’ has the 25 5
96		-	•HR 730 EH
97		-	meaning given such term in section 101(a) of the 1
98		-	Higher Education Act of 1965 (20 U.S.C. 1001(a)). 2
	111	+	NSTITUTION OF HIGHER EDUCATION .—The 19
	112	+	term ‘‘institution of higher education’’ has the 20
	113	+	meaning given such term in section 101(a) of the 21
	114	+	Higher Education Act of 1965 (20 U.S.C. 1001(a)). 22
99	115		(5) M
100		-	ATHEMATICAL MODELING .—The term 3
101		-	‘‘mathematical modeling’’ has the meaning given 4
102		-	such term in the 2019 Guidelines to Assessment and 5
103		-	Instruction in Mathematical Modeling Education 6
104		-	(GAIMME) report, 2nd edition. 7
	116	+	ATHEMATICAL MODELING .—The term 23
	117	+	‘‘mathematical modeling’’ has the meaning given 24
	118	+	such term in the 2019 Guidelines to Assessment and 25
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	121	+	•HR 730 IH
	122	+	Instruction in Mathematical Modeling Education 1
	123	+	(GAIMME) report, 2nd edition. 2
105	124		(6) O
106		-	PERATIONS RESEARCH .—The term ‘‘oper-8
107		-	ations research’’ means the application of scientific 9
108		-	methods to the management and administration of 10
109		-	organized military, governmental, commercial, and 11
110		-	industrial processes to maximize operational effi-12
111		-	ciency. 13
	125	+	PERATIONS RESEARCH .—The term ‘‘oper-3
	126	+	ations research’’ means the application of scientific 4
	127	+	methods to the management and administration of 5
	128	+	organized military, governmental, commercial, and 6
	129	+	industrial processes to maximize operational effi-7
	130	+	ciency. 8
112	131		(7) S
113		-	TATISTICAL MODELING .—The term ‘‘sta-14
114		-	tistical modeling’’ has the meaning given such term 15
115		-	in the 2021 Guidelines to Assessment and Instruc-16
116		-	tion in Statistical Education (GAISE II) report. 17
117		-	(8) STEM.—The term ‘‘STEM’’ means the 18
118		-	academic and professional disciplines of science, 19
119		-	technology, engineering, and mathematics, including 20
120		-	computer science. 21
	132	+	TATISTICAL MODELING .—The term ‘‘sta-9
	133	+	tistical modeling’’ has the meaning given such term 10
	134	+	in the 2021 Guidelines to Assessment and Instruc-11
	135	+	tion in Statistical Education (GAISE II) report. 12
	136	+	(8) STEM.—The term ‘‘STEM’’ means the 13
	137	+	academic and professional disciplines of science, 14
	138	+	technology, engineering, and mathematics, including 15
	139	+	computer science. 16
121	140		(c) P
122		-	REPARINGEDUCATORSTOENGAGESTUDENTS 22
123		-	INMATHEMATICAL AND STATISTICALMODELING.—The 23
124		-	Director shall make awards on a merit-reviewed, competi-24
125		-	tive basis to institutions of higher education and nonprofit 25 6
126		-	•HR 730 EH
127		-	organizations (or a consortium thereof) for research and 1
128		-	development to advance innovative approaches to support 2
129		-	and sustain high-quality mathematical modeling education 3
130		-	in schools that are operated by local educational agencies, 4
131		-	including statistical modeling, data science, operations re-5
132		-	search, and computational thinking. The Director shall en-6
133		-	courage applicants to form partnerships to address critical 7
134		-	transitions, such as middle school to high school, high 8
135		-	school to college, and school to internships and jobs. 9
	141	+	REPARINGEDUCATORSTOENGAGESTUDENTS 17
	142	+	INMATHEMATICAL AND STATISTICALMODELING.—The 18
	143	+	Director shall make awards on a merit-reviewed, competi-19
	144	+	tive basis to institutions of higher education and nonprofit 20
	145	+	organizations (or a consortium thereof) for research and 21
	146	+	development to advance innovative approaches to support 22
	147	+	and sustain high-quality mathematical modeling education 23
	148	+	in schools that are operated by local educational agencies, 24
	149	+	including statistical modeling, data science, operations re-25
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	152	+	•HR 730 IH
	153	+	search, and computational thinking. The Director shall en-1
	154	+	courage applicants to form partnerships to address critical 2
	155	+	transitions, such as middle school to high school, high 3
	156	+	school to college, and school to internships and jobs. 4
136	157		(d) A
137		-	PPLICATION.—An entity seeking an award 10
138		-	under subsection (c) shall submit an application at such 11
139		-	time, in such manner, and containing such information as 12
140		-	the Director may require. The application shall include the 13
141		-	following: 14
142		-	(1) A description of the target population to be 15
143		-	served by the research activity for which such an 16
144		-	award is sought, including student subgroups de-17
145		-	scribed in section 1111(b)(2)(B)(xi) of the Elemen-18
146		-	tary and Secondary Education Act of 1965 (20 19
147		-	U.S.C. 6311(b)(2)(B)(xi)), and students experi-20
148		-	encing homelessness and children and youth in fos-21
149		-	ter care. 22
150		-	(2) A description of the process for recruitment 23
151		-	and selection of students, educators, or local edu-24 7
152		-	•HR 730 EH
153		-	cational agencies to participate in such research ac-1
154		-	tivity. 2
155		-	(3) A description of how such research activity 3
156		-	may inform efforts to promote the engagement and 4
157		-	achievement of students, including students from 5
158		-	groups historically underrepresented in STEM, in 6
159		-	prekindergarten through grade 12 in mathematical 7
160		-	modeling and statistical modeling using problem-8
161		-	based learning with contextualized data and com-9
162		-	putational tools. 10
163		-	(4) In the case of a proposal consisting of a 11
164		-	partnership or partnerships with one or more local 12
165		-	educational agencies and one or more researchers, a 13
166		-	plan for establishing a sustained partnership that is 14
167		-	jointly developed and managed, draws from the ca-15
168		-	pacities of each partner, and is mutually beneficial. 16
	158	+	PPLICATION.—An entity seeking an award 5
	159	+	under subsection (c) shall submit an application at such 6
	160	+	time, in such manner, and containing such information as 7
	161	+	the Director may require. The application shall include the 8
	162	+	following: 9
	163	+	(1) A description of the target population to be 10
	164	+	served by the research activity for which such an 11
	165	+	award is sought, including student subgroups de-12
	166	+	scribed in section 1111(b)(2)(B)(xi) of the Elemen-13
	167	+	tary and Secondary Education Act of 1965 (20 14
	168	+	U.S.C. 6311(b)(2)(B)(xi)), and students experi-15
	169	+	encing homelessness and children and youth in fos-16
	170	+	ter care. 17
	171	+	(2) A description of the process for recruitment 18
	172	+	and selection of students, educators, or local edu-19
	173	+	cational agencies to participate in such research ac-20
	174	+	tivity. 21
	175	+	(3) A description of how such research activity 22
	176	+	may inform efforts to promote the engagement and 23
	177	+	achievement of students, including students from 24
	178	+	groups historically underrepresented in STEM, in 25
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	181	+	•HR 730 IH
	182	+	prekindergarten through grade 12 in mathematical 1
	183	+	modeling and statistical modeling using problem- 2
	184	+	based learning with contextualized data and com-3
	185	+	putational tools. 4
	186	+	(4) In the case of a proposal consisting of a 5
	187	+	partnership or partnerships with one or more local 6
	188	+	educational agencies and one or more researchers, a 7
	189	+	plan for establishing a sustained partnership that is 8
	190	+	jointly developed and managed, draws from the ca-9
	191	+	pacities of each partner, and is mutually beneficial. 10
169	192		(e) P
170		-	ARTNERSHIPS.—In making awards under sub-17
171		-	section (c), the Director shall encourage applications that 18
172		-	include the following: 19
173		-	(1) Partnership with a nonprofit organization 20
174		-	or an institution of higher education that has exten-21
175		-	sive experience and expertise in increasing the par-22
176		-	ticipation of students in prekindergarten through 23
177		-	grade 12 in mathematical modeling and statistical 24
178		-	modeling. 25 8
179		-	•HR 730 EH
180		-	(2) Partnership with a local educational agency, 1
181		-	a consortium of local educational agencies, or Tribal 2
182		-	educational agencies. 3
183		-	(3) An assurance from school leaders to making 4
184		-	reforms and activities proposed by the applicant a 5
185		-	priority. 6
186		-	(4) Ways to address critical transitions, such as 7
187		-	middle school to high school, high school to college, 8
188		-	and school to internships and jobs. 9
189		-	(5) Input from education researchers and cog-10
190		-	nitive scientists, as well as practitioners in research 11
191		-	and industry, so that what is being taught is up-to-12
192		-	date in terms of content and pedagogy. 13
193		-	(6) A communications strategy for early con-14
194		-	versations with parents, school leaders, school 15
195		-	boards, community members, employers, and other 16
196		-	stakeholders. 17
197		-	(7) Resources for parents, school leaders, school 18
198		-	boards, community members, and other stakeholders 19
199		-	to build skills in modeling and analytics. 20
	193	+	ARTNERSHIPS.—In making awards under sub-11
	194	+	section (c), the Director shall encourage applications that 12
	195	+	include the following: 13
	196	+	(1) Partnership with a nonprofit organization 14
	197	+	or an institution of higher education that has exten-15
	198	+	sive experience and expertise in increasing the par-16
	199	+	ticipation of students in prekindergarten through 17
	200	+	grade 12 in mathematical modeling and statistical 18
	201	+	modeling. 19
	202	+	(2) Partnership with a local educational agency, 20
	203	+	a consortium of local educational agencies, or Tribal 21
	204	+	educational agencies. 22
	205	+	(3) An assurance from school leaders to making 23
	206	+	reforms and activities proposed by the applicant a 24
	207	+	priority. 25
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	210	+	•HR 730 IH
	211	+	(4) Ways to address critical transitions, such as 1
	212	+	middle school to high school, high school to college, 2
	213	+	and school to internships and jobs. 3
	214	+	(5) Input from education researchers and cog-4
	215	+	nitive scientists, as well as practitioners in research 5
	216	+	and industry, so that what is being taught is up-to- 6
	217	+	date in terms of content and pedagogy. 7
	218	+	(6) A communications strategy for early con-8
	219	+	versations with parents, school leaders, school 9
	220	+	boards, community members, employers, and other 10
	221	+	stakeholders. 11
	222	+	(7) Resources for parents, school leaders, school 12
	223	+	boards, community members, and other stakeholders 13
	224	+	to build skills in modeling and analytics. 14
200	225		(f) U
201		-	SE OFFUNDS.—An entity that receives an 21
202		-	award under this section shall use the award for research 22
203		-	and development activities to advance innovative ap-23
204		-	proaches to support and sustain high-quality mathe-24
205		-	matical modeling education in public schools, including 25 9
206		-	•HR 730 EH
207		-	statistical modeling, data science, operations research, and 1
208		-	computational thinking, which may include the following: 2
209		-	(1) Engaging prekindergarten through grade 12 3
210		-	educators in professional learning opportunities to 4
211		-	enhance mathematical modeling and statistical prob-5
212		-	lem solving knowledge, and developing training and 6
213		-	best practices to provide more interdisciplinary 7
214		-	learning opportunities. 8
215		-	(2) Conducting research on curricula and teach-9
216		-	ing practices that empower students to choose the 10
217		-	mathematical, statistical, computational, and techno-11
218		-	logical tools they will apply to a problem, as is re-12
219		-	quired in life and the workplace, rather than pre-13
220		-	scribing a particular approach or method. 14
221		-	(3) Providing students with opportunities to ex-15
222		-	plore and analyze real data sets from contexts that 16
223		-	are meaningful to the students, which may include 17
224		-	the following: 18
225		-	(A) Missing or incorrect values. 19
226		-	(B) Quantities of data that require choice 20
227		-	and use of appropriate technology. 21
228		-	(C) Multiple data sets that require choices 22
229		-	about which data are relevant to the current 23
230		-	problem. 24 10
231		-	•HR 730 EH
232		-	(D) Data of various types including quan-1
233		-	tities, words, and images. 2
234		-	(4) Taking a school or district-wide approach to 3
235		-	professional development in mathematical modeling 4
236		-	and statistical modeling. 5
237		-	(5) Engaging rural local agencies. 6
238		-	(6) Supporting research on effective mathe-7
239		-	matical modeling and statistical modeling teaching 8
240		-	practices, including problem- and project-based 9
241		-	learning, universal design for accessibility, and ru-10
242		-	brics and mastery-based grading practices to assess 11
243		-	student performance. 12
244		-	(7) Designing and developing pre-service and 13
245		-	in-service training resources to assist educators in 14
246		-	adopting transdisciplinary teaching practices within 15
247		-	mathematics and statistics courses. 16
248		-	(8) Coordinating with local partners to adapt 17
249		-	mathematics and statistics teaching practices to le-18
250		-	verage local natural, business, industry, and commu-19
251		-	nity assets in order to support community-based 20
252		-	learning. 21
253		-	(9) Providing hands-on training and research 22
254		-	opportunities for mathematics and statistics edu-23
255		-	cators at Federal laboratories, institutions of higher 24
256		-	education, or in industry. 25 11
257		-	•HR 730 EH
258		-	(10) Developing mechanisms for partnerships 1
259		-	between educators and employers to help educators 2
260		-	and students make connections between their mathe-3
261		-	matics and statistics projects and topics of relevance 4
262		-	in today’s world. 5
263		-	(11) Designing and implementing professional 6
264		-	development courses and experiences, including men-7
265		-	toring for educators, that combine face-to-face and 8
266		-	online experiences. 9
267		-	(12) Reducing gaps in access to learning oppor-10
268		-	tunities for students from groups historically under-11
269		-	represented in STEM. 12
270		-	(13) Providing support and resources for stu-13
271		-	dents from groups historically underrepresented in 14
272		-	STEM. 15
273		-	(14) Addressing critical transitions, such as 16
274		-	middle school to high school, high school to college, 17
275		-	and school to internships and jobs. 18
276		-	(15) Researching effective approaches for en-19
277		-	gaging students from groups historically underrep-20
278		-	resented in STEM. 21
279		-	(16) Any other activity the Director determines 22
280		-	will accomplish the goals of this section. 23
	226	+	SE OFFUNDS.—An entity that receives an 15
	227	+	award under this section shall use the award for research 16
	228	+	and development activities to advance innovative ap-17
	229	+	proaches to support and sustain high-quality mathe-18
	230	+	matical modeling education in public schools, including 19
	231	+	statistical modeling, data science, operations research, and 20
	232	+	computational thinking, which may include the following: 21
	233	+	(1) Engaging prekindergarten through grade 12 22
	234	+	educators in professional learning opportunities to 23
	235	+	enhance mathematical modeling and statistical prob-24
	236	+	lem solving knowledge, and developing training and 25
	237	+	VerDate Sep 11 2014 03:05 Feb 20, 2025 Jkt 059200 PO 00000 Frm 00008 Fmt 6652 Sfmt 6201 E:\BILLS\H730.IH H730
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	239	+	•HR 730 IH
	240	+	best practices to provide more interdisciplinary 1
	241	+	learning opportunities. 2
	242	+	(2) Conducting research on curricula and teach-3
	243	+	ing practices that empower students to choose the 4
	244	+	mathematical, statistical, computational, and techno-5
	245	+	logical tools they will apply to a problem, as is re-6
	246	+	quired in life and the workplace, rather than pre-7
	247	+	scribing a particular approach or method. 8
	248	+	(3) Providing students with opportunities to ex-9
	249	+	plore and analyze real data sets from contexts that 10
	250	+	are meaningful to the students, which may include 11
	251	+	the following: 12
	252	+	(A) Missing or incorrect values. 13
	253	+	(B) Quantities of data that require choice 14
	254	+	and use of appropriate technology. 15
	255	+	(C) Multiple data sets that require choices 16
	256	+	about which data are relevant to the current 17
	257	+	problem. 18
	258	+	(D) Data of various types including quan-19
	259	+	tities, words, and images. 20
	260	+	(4) Taking a school or district-wide approach to 21
	261	+	professional development in mathematical modeling 22
	262	+	and statistical modeling. 23
	263	+	(5) Engaging rural local agencies. 24
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	266	+	•HR 730 IH
	267	+	(6) Supporting research on effective mathe-1
	268	+	matical modeling and statistical modeling teaching 2
	269	+	practices, including problem- and project-based 3
	270	+	learning, universal design for accessibility, and ru-4
	271	+	brics and mastery-based grading practices to assess 5
	272	+	student performance. 6
	273	+	(7) Designing and developing pre-service and 7
	274	+	in-service training resources to assist educators in 8
	275	+	adopting transdisciplinary teaching practices within 9
	276	+	mathematics and statistics courses. 10
	277	+	(8) Coordinating with local partners to adapt 11
	278	+	mathematics and statistics teaching practices to le-12
	279	+	verage local natural, business, industry, and commu-13
	280	+	nity assets in order to support community-based 14
	281	+	learning. 15
	282	+	(9) Providing hands-on training and research 16
	283	+	opportunities for mathematics and statistics edu-17
	284	+	cators at Federal laboratories, institutions of higher 18
	285	+	education, or in industry. 19
	286	+	(10) Developing mechanisms for partnerships 20
	287	+	between educators and employers to help educators 21
	288	+	and students make connections between their mathe-22
	289	+	matics and statistics projects and topics of relevance 23
	290	+	in today’s world. 24
	291	+	VerDate Sep 11 2014 03:05 Feb 20, 2025 Jkt 059200 PO 00000 Frm 00010 Fmt 6652 Sfmt 6201 E:\BILLS\H730.IH H730
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	293	+	•HR 730 IH
	294	+	(11) Designing and implementing professional 1
	295	+	development courses and experiences, including men-2
	296	+	toring for educators, that combine face-to-face and 3
	297	+	online experiences. 4
	298	+	(12) Reducing gaps in access to learning oppor-5
	299	+	tunities for students from groups historically under-6
	300	+	represented in STEM. 7
	301	+	(13) Providing support and resources for stu-8
	302	+	dents from groups historically underrepresented in 9
	303	+	STEM. 10
	304	+	(14) Addressing critical transitions, such as 11
	305	+	middle school to high school, high school to college, 12
	306	+	and school to internships and jobs. 13
	307	+	(15) Researching effective approaches for en-14
	308	+	gaging students from groups historically underrep-15
	309	+	resented in STEM. 16
	310	+	(16) Any other activity the Director determines 17
	311	+	will accomplish the goals of this section. 18
281	312		(g) E
282		-	VALUATIONS.—All proposals for awards under 24
283		-	this section shall include an evaluation plan that includes 25 12
284		-	•HR 730 EH
285		-	the use of outcome oriented measures to assess the impact 1
286		-	and efficacy of the award. Each recipient of an award 2
287		-	under this section shall include results from such evalua-3
288		-	tive activities in annual and final project reports. 4
	313	+	VALUATIONS.—All proposals for awards under 19
	314	+	this section shall include an evaluation plan that includes 20
	315	+	the use of outcome oriented measures to assess the impact 21
	316	+	and efficacy of the award. Each recipient of an award 22
	317	+	under this section shall include results from such evalua-23
	318	+	tive activities in annual and final project reports. 24
289	319		(h) A
290		-	CCOUNTABILITY AND DISSEMINATION.—5
291		-	(1) E
292		-	VALUATION REQUIRED .—The Director 6
293		-	shall evaluate the portfolio of awards made under 7
294		-	this section. Such evaluation shall—8
295		-	(A) use a common set of benchmarks and 9
296		-	tools to assess the results of research conducted 10
297		-	under such awards and identify best practices; 11
298		-	and 12
299		-	(B) to the extent practicable, integrate the 13
300		-	findings of research resulting from the activities 14
301		-	funded through such awards with the findings 15
302		-	of other research on student’s pursuit of de-16
303		-	grees or careers in STEM. 17
	320	+	CCOUNTABILITY AND DISSEMINATION.— 25
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	323	+	•HR 730 IH
	324	+	(1) EVALUATION REQUIRED .—The Director 1
	325	+	shall evaluate the portfolio of awards made under 2
	326	+	this section. Such evaluation shall— 3
	327	+	(A) use a common set of benchmarks and 4
	328	+	tools to assess the results of research conducted 5
	329	+	under such awards and identify best practices; 6
	330	+	and 7
	331	+	(B) to the extent practicable, integrate the 8
	332	+	findings of research resulting from the activities 9
	333	+	funded through such awards with the findings 10
	334	+	of other research on student’s pursuit of de-11
	335	+	grees or careers in STEM. 12
304	336		(2) R
305		-	EPORT ON EVALUATIONS .—Not later than 18
306		-	180 days after the completion of the evaluation 19
307		-	under paragraph (1), the Director shall submit to 20
308		-	Congress and make widely available to the public a 21
309		-	report that includes the following: 22
310		-	(A) The results of the evaluation. 23
311		-	(B) Any recommendations for administra-24
312		-	tive and legislative action that could optimize 25 13
313		-	•HR 730 EH
314		-	the effectiveness of the awards made under this 1
315		-	section. 2
	337	+	EPORT ON EVALUATIONS .—Not later than 13
	338	+	180 days after the completion of the evaluation 14
	339	+	under paragraph (1), the Director shall submit to 15
	340	+	Congress and make widely available to the public a 16
	341	+	report that includes the following: 17
	342	+	(A) The results of the evaluation. 18
	343	+	(B) Any recommendations for administra-19
	344	+	tive and legislative action that could optimize 20
	345	+	the effectiveness of the awards made under this 21
	346	+	section. 22
316	347		(i) F
317		-	UNDING.—$10,000,000 for each of the fiscal 3
318		-	years 2026 through 2030 is authorized to be used by the 4
319		-	Directorate for STEM Education of the National Science 5
320		-	Foundation to carry out this section. 6
321		-	SEC. 3. NASEM REPORT ON MATHEMATICAL AND STATIS-7
322		-	TICAL MODELING EDUCATION IN PRE-8
323		-	KINDERGARTEN THROUGH 12TH GRADE. 9
	348	+	UNDING.—From amounts appropriated or other-23
	349	+	wise made available for the Directorate for STEM Edu-24
	350	+	cation of the National Science Foundation, the Director 25
	351	+	VerDate Sep 11 2014 03:05 Feb 20, 2025 Jkt 059200 PO 00000 Frm 00012 Fmt 6652 Sfmt 6201 E:\BILLS\H730.IH H730
	352	+	kjohnson on DSK7ZCZBW3PROD with $$_JOB 13
	353	+	•HR 730 IH
	354	+	shall allocate $10,000,000 for each of the fiscal years 1
	355	+	2026 through 2030 to carry out this section. 2
	356	+	SEC. 3. NASEM REPORT ON MATHEMATICAL AND STATIS-3
	357	+	TICAL MODELING EDUCATION IN PRE-4
	358	+	KINDERGARTEN THROUGH 12TH GRADE. 5
324	359		(a) S
325		-	TUDY.—Not later than 180 days after the date 10
326		-	of the enactment of this Act, the Director of the National 11
327		-	Science Foundation (in this section referred to as the ‘‘Di-12
328		-	rector’’) shall seek to enter into an agreement with the 13
329		-	National Academies of Sciences, Engineering and Medi-14
330		-	cine (in this section referred to as ‘‘NASEM’’) (or if 15
331		-	NASEM declines to enter into such an agreement, another 16
332		-	appropriate entity) under which NASEM, or such other 17
333		-	appropriate entity, agrees to conduct a study on the fol-18
334		-	lowing: 19
335		-	(1) Factors that enhance or barriers to the im-20
336		-	plementation of mathematical modeling and statis-21
337		-	tical modeling in elementary and secondary edu-22
338		-	cation, including opportunities for and barriers to 23
339		-	use modeling to integrate mathematical and statis-24 14
340		-	•HR 730 EH
341		-	tical ideas across the curriculum, including the fol-1
342		-	lowing: 2
343		-	(A) Pathways in mathematical modeling 3
344		-	and statistical problem solving from kinder-4
345		-	garten to the workplace so students are able to 5
346		-	identify opportunities to use their school mathe-6
347		-	matics and statistics in a variety of jobs and 7
348		-	life situations and so employers can benefit 8
349		-	from students’ school learning of data science, 9
350		-	computational thinking, mathematics, statistics, 10
351		-	and related subjects. 11
352		-	(B) The role of community-based prob-12
353		-	lems, service-based learning. and internships for 13
354		-	connecting students with career preparatory ex-14
355		-	periences. 15
356		-	(C) Best practices in problem-, project-, 16
357		-	performance-based learning and assessment. 17
358		-	(2) Characteristics of teacher education pro-18
359		-	grams that successfully prepare teachers to engage 19
360		-	students in mathematical modeling and statistical 20
361		-	modeling, as well as gaps and suggestions for build-21
362		-	ing capacity in the pre-service and in-service teacher 22
363		-	workforce. 23
364		-	(3) Mechanisms for communication with stake-24
365		-	holders, including parents, administrators, and the 25 15
366		-	•HR 730 EH
367		-	public, to promote understanding and knowledge of 1
368		-	the value of mathematical modeling and statistical 2
369		-	modeling in education. 3
	360	+	TUDY.—Not later than 180 days after the date 6
	361	+	of the enactment of this Act, the Director shall seek to 7
	362	+	enter into an agreement with the National Academies of 8
	363	+	Sciences, Engineering and Medicine (in this section re-9
	364	+	ferred to as ‘‘NASEM’’) (or if NASEM declines to enter 10
	365	+	into such an agreement, another appropriate entity) under 11
	366	+	which NASEM, or such other appropriate entity, agrees 12
	367	+	to conduct a study on the following: 13
	368	+	(1) Factors that enhance or barriers to the im-14
	369	+	plementation of mathematical modeling and statis-15
	370	+	tical modeling in elementary and secondary edu-16
	371	+	cation, including opportunities for and barriers to 17
	372	+	use modeling to integrate mathematical and statis-18
	373	+	tical ideas across the curriculum, including the fol-19
	374	+	lowing: 20
	375	+	(A) Pathways in mathematical modeling 21
	376	+	and statistical problem solving from kinder-22
	377	+	garten to the workplace so students are able to 23
	378	+	identify opportunities to use their school mathe-24
	379	+	matics and statistics in a variety of jobs and 25
	380	+	VerDate Sep 11 2014 03:05 Feb 20, 2025 Jkt 059200 PO 00000 Frm 00013 Fmt 6652 Sfmt 6201 E:\BILLS\H730.IH H730
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	382	+	•HR 730 IH
	383	+	life situations and so employers can benefit 1
	384	+	from students’ school learning of data science, 2
	385	+	computational thinking, mathematics, statistics, 3
	386	+	and related subjects. 4
	387	+	(B) The role of community-based prob-5
	388	+	lems, service-based learning. and internships for 6
	389	+	connecting students with career preparatory ex-7
	390	+	periences. 8
	391	+	(C) Best practices in problem-, project-, 9
	392	+	performance-based learning and assessment. 10
	393	+	(2) Characteristics of teacher education pro-11
	394	+	grams that successfully prepare teachers to engage 12
	395	+	students in mathematical modeling and statistical 13
	396	+	modeling, as well as gaps and suggestions for build-14
	397	+	ing capacity in the pre-service and in-service teacher 15
	398	+	workforce. 16
	399	+	(3) Mechanisms for communication with stake-17
	400	+	holders, including parents, administrators, and the 18
	401	+	public, to promote understanding and knowledge of 19
	402	+	the value of mathematical modeling and statistical 20
	403	+	modeling in education. 21
370	404		(b) P
371		-	UBLICSTAKEHOLDERMEETING.—In the course 4
372		-	of completing the study described in subsection (a), 5
373		-	NASEM or such other appropriate entity shall hold not 6
374		-	fewer than one public meeting to obtain stakeholder input 7
375		-	on the topics of such study. 8
	405	+	UBLICSTAKEHOLDERMEETING.—In the course 22
	406	+	of completing the study described in subsection (a), 23
	407	+	NASEM or such other appropriate entity shall hold not 24
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	410	+	•HR 730 IH
	411	+	fewer than one public meeting to obtain stakeholder input 1
	412	+	on the topics of such study. 2
376	413		(c) R
377		-	EPORT.—The agreement under subsection (a) 9
378		-	shall require NASEM, or such other appropriate entity, 10
379		-	not later than 24 months after the effective date of such 11
380		-	agreement, to submit to the Director, the Secretary of 12
381		-	Education, and the Congress a report containing the fol-13
382		-	lowing: 14
383		-	(1) The results of the study conducted under 15
384		-	subsection (a). 16
385		-	(2) Recommendations to modernize the proc-17
386		-	esses described in subsection (a)(1). 18
387		-	(3) Recommendations for such legislative and 19
388		-	administrative action as NASEM, or such other ap-20
389		-	propriate entity, determines appropriate. 21
	414	+	EPORT.—The agreement under subsection (a) 3
	415	+	shall require NASEM, or such other appropriate entity, 4
	416	+	not later than 24 months after the effective date of such 5
	417	+	agreement, to submit to the Director, the Secretary of 6
	418	+	Education, and the Congress a report containing the fol-7
	419	+	lowing: 8
	420	+	(1) The results of the study conducted under 9
	421	+	subsection (a). 10
	422	+	(2) Recommendations to modernize the proc-11
	423	+	esses described in subsection (a)(1). 12
	424	+	(3) Recommendations for such legislative and 13
	425	+	administrative action as NASEM, or such other ap-14
	426	+	propriate entity, determines appropriate. 15
390	427		(d) F
391		-	UNDING.—~~$1,000,000 for each of the fiscal 22~~
392		-	~~years 2026 through 2030 is authorized to be used by~~ the 23
393		-	~~Directorate for STEM Education~~ of the National Science 24
394		-	~~Foundation~~ to ~~carry out this section.~~ ~~25 16~~
395		-	~~•HR 730 EH~~
396		-	SEC. 4. LIMITATIONS. 1
	428	+	UNDING.—From amounts appropriated or oth-16
	429	+	erwise made available for the Directorate for STEM Edu-17
	430	+	cation of the National Science Foundation, the Director 18
	431	+	shall allocate up to $1,000,000 for fiscal year 2026 to 19
	432	+	carry out this section. 20
	433	+	SEC. 4. LIMITATIONS. 21
397	434		(a) L
398		-	IMITATION ONFUNDING.—Amounts made avail-2
399		-	able to carry out sections 2 and 3 shall be derived from 3
400		-	amounts appropriated or otherwise made available to the 4
401		-	National Science Foundation. 5
402		-	(b) S
403		-	UNSET.—The authority to provide awards under 6
404		-	this Act shall expire on September 30, 2029. 7
405		-	Passed the House of Representatives March 24,
406		-	2025.
407		-	Attest:
408		-	Clerk. 119
409		-	TH
410		-	CONGRESS
411		-	1
412		-	ST
413		-	S
414		-	ESSION
415		-
416		-	H. R. 730
417		-	AN ACT
418		-
419		-	To coordinate Federal research and development ef-
420		-	forts focused on modernizing mathematics in
421		-	STEM education through mathematical and sta-
422		-	tistical modeling, including data-driven and com-
423		-	putational thinking, problem, project, and per-
424		-	formance-based learning and assessment, inter-
425		-	disciplinary exploration, and career connections,
426		-	and for other purposes.
	435	+	IMITATION ONFUNDING.—Amounts made avail-22
	436	+	able to carry out sections 2 and 3 shall be derived from 23
	437	+	amounts appropriated or otherwise made available to the 24
	438	+	National Science Foundation. 25
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	441	+	•HR 730 IH
	442	+	(b) SUNSET.—The authority to provide awards under 1
	443	+	this Act shall expire on September 30, 2029. 2
	444	+	Æ
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