Building K-12 Data Science: A Call to Action for Statisticians

Music City Center 

Room: CC-211 

With rapid advances of technology in our ever increasingly data-driven world, the standard curriculum of K-12 education must evolve to stay relevant and impactful for students. The foundations of statistics can help students – regardless of their future life paths or career interests – navigate the information era and tackle AI with confidence. Statisticians are uniquely positioned to help drive the transformation we need in our school system, ensure a high school diploma is high-value, and help more students pursue the knowledge, careers, and habits that will enable success in 2040 or 2100.

The movement for K-12 data science education is trying to bring about this reality, but there are both opportunities and challenges. Statisticians play a crucial role in this process, and their leadership can drive significant advancements in how this work is designed, applied, and implemented. Come learn about efforts on behalf of national policy organizations, NSF-funded networks for teacher training, research by the National Academies, and how the ASA is supporting this work.

Objective: This presentation aims to emphasize the need for modernization within the field of mathematics and to mobilize statisticians to lead this change. We will explore the current limitations, the benefits of modernization, and actionable steps that statisticians can take to advance and refine mathematical practices.

Key Points:
1. State of the field of K-12 Data Science education
a. Scale and spread of data science programs around the country
b. Examples of diverse K-12 models
c. State-level initiatives (Virginia)
2. Research efforts to build student competency progressions
a. National Academies Consensus study on Computing & Data Foundations for K-12
b. Data Science 4 Everyone National Learning Progression
c. UT Austin Dana Center Course Framework
d. SETS II Committee Work
3. Actionable Steps for Statisticians: How can Higher-Ed Support K-12?
a. Adopt and Advocate for New Technologies: Embrace advanced software, machine learning, and computational tools in research and practice.
b. Provide Input On Updates to Educational Curricula: Integrate modern methodologies and technologies into K-12 educational programs, standards development, and training.
c. Promote Interdisciplinary Collaboration: Collaborate with professionals from other fields, including Colleges of Education, to incorporate diverse perspectives and innovative approaches.
d. Lead by Example: Demonstrate the benefits of modernization through their work and actively share successes and best practices with the broader community.

Call to Action: We call upon all statisticians to take proactive steps towards supporting the creation of K-12 data science education. Whether collaborating with your graduate schools of education, hosting summer workshops for K-12 educators, or collaborating with other faculty to design accessible and thoughtful pathways into higher-education – statisticians are uniquely positioned to champion this work.

Yes

ASA/NCTM Joint Comm on Curriculum in Stats and Probability

Caucus for Women in Statistics

History of Statistics Interest Group

Section on Statistical Learning and Data Science

Section on Statistics and Data Science Education