S. 1602: Mathematical and Statistical Modeling Education Act

The bill titled the **Mathematical and Statistical Modeling Education Act** aims to enhance mathematics and statistics education in the United States, particularly within the science, technology, engineering, and mathematics (STEM) fields. Here’s a breakdown of its key components:

Findings

The bill outlines several findings regarding the current state of mathematics education:

• The education provided in schools, particularly in statistical problem solving and data science, does not meet the rapidly changing needs of the workforce, leading to a shortage of STEM-skilled professionals.
• The U.S. may fall short of producing 1 million additional STEM professionals required in the next decade.
• Core competencies in data science are crucial as many sectors require teamwork and the use of computational tools for problem solving.
• STEM careers typically offer better salaries, advancement opportunities, and job security.
• Fields such as analytics, economics, and medicine require proficiency in handling and understanding data.
• Emerging technologies like AI and machine learning rely on robust mathematical and statistical understanding.
• International competition, particularly from countries like China, in mathematical modeling has seen superior participation and success in competitions.
• Girls participate in modeling challenges at rates comparable to boys, which could encourage more inclusive approaches in competitions compared to traditional math settings.

Definitions

The bill provides definitions for several terms relevant to its provisions, including:

• Director: Refers to the Director of the National Science Foundation.
• Foundation: Refers to the National Science Foundation.
• Mathematical modeling and Statistical modeling: Defined per existing guidelines ensuring they align with current educational standards.

Support for Educators

The bill proposes that the Director of the National Science Foundation create merit-based grants for higher education institutions and nonprofit organizations. These grants would focus on:

• Developing innovative teaching methods in mathematical and statistical modeling.
• Supporting partnerships between educational institutions and local agencies to help students transition from school to the workforce.
• Encouraging applications that consider diverse student populations, including underrepresented groups in STEM.

Use of Funds

Entities receiving funding would be required to utilize the resources primarily for:

• Training educators to improve mathematical modeling education.
• Conducting research on effective curricula and teaching practices.
• Engaging students with real-world data and providing relevant resources.
• Addressing smooth transitions from middle to high school, high school to college, and into careers.

Evaluations and Accountability

The bill mandates that each proposal include an evaluation plan to assess the effectiveness of funded projects. Results from these evaluations will be reported annually and contribute to accountability measures ensuring results are publicly available for review.

Funding Provisions

The bill authorizes funding of $10 million per year from 2026 through 2030 for the foundation's efforts in implementing this educational initiative.

Study and Report by NASEM

Within 180 days of the bill’s enactment, the National Academies of Sciences, Engineering, and Medicine (NASEM) would conduct a study on the barriers and opportunities in implementing mathematical modeling and statistical modeling in K-12 education. This would include:

• Identifying factors that help or hinder the implementation of such education.
• Exploring teacher education programs that effectively prepare educators.
• Recommending best practices and legislative changes to enhance educational outcomes.

Limitations

The bill specifies that the funding for its initiatives will be sourced from appropriated amounts available to the National Science Foundation. Furthermore, the authorization for awards under this act will expire on September 30, 2029.

Relevant Companies

• MSFT (Microsoft Corporation): Might be impacted due to their emphasis on data science and educational tools that could benefit from a stronger emphasis on data modeling in education.
• ADBE (Adobe Inc.): Could see changes in demand for their educational software solutions as schools adopt new curricula focused on data analysis and modeling.
• AAPL (Apple Inc.): May experience increased sales in educational technology due to a focus on enhancing computer science education as part of STEM efforts.