HR1735-118

Reported

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.

118th Congress Introduced Mar 23, 2023

At a Glance

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Legislative Progress

Reported
Introduced Committee Passed
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 …

Mar 23, 2023

Ms. Houlahan (for herself and Mr. Baird) introduced the following …

Summary

What This Bill Does

Directs federal coordination of research on modernizing mathematics education to include data science, statistical modeling, and computational tools. Addresses STEM workforce skills gap.

Who Benefits and How

Students gain relevant math education including data science. Employers get better-prepared STEM workforce. AI and data science fields gain talent pipeline.

Who Bears the Burden and How

NSF and education agencies must coordinate new research. Math curriculum may require updates. Traditional math education approaches may be disrupted.

Key Provisions

  • Coordinates federal R&D on mathematical modeling education
  • Emphasizes data science and computational problem solving
  • Addresses 1 million STEM professional shortage
Model: claude-opus-4
Generated: Jan 10, 2026 18:47

Evidence Chain:

This summary is derived from the structured analysis below. See "Detailed Analysis" for per-title beneficiaries/burden bearers with clause-level evidence links.

Primary Purpose

Coordinates federal R&D on modernizing mathematics education including data science and statistical modeling

Policy Domains

Education STEM Research Data Science

Legislative Strategy

"Modernize math education for data-driven economy"

Bill Structure & Actor Mappings

Who is "The Secretary" in each section?

Domains
Education STEM Data Science

We use a combination of our own taxonomy and classification in addition to large language models to assess meaning and potential beneficiaries. High confidence means strong textual evidence. Always verify with the original bill text.

Learn more about our methodology