Data Science | K-10

# BIG IDEAS

A Selection of Big Ideas from Data Science – from GAISE II (2021).

### Formulate statistical investigative questions

• Formulate statistical investigative questions
• Students generate ideas and ask questions – creating and refining statistical investigation questions

### Collect/consider data

• Students learn what counts as data (eg visuals, sounds, numbers, categories) and understand that people collect data to answer questions
• Students develop strategies to collect and organize data of various types and from various sources
• Students design studies to answer statistical investigative questions

### Analyze data

• Students develop ways to represent and interrogate data to notice, describe and analyze patterns
• Students recognize variability and use technology to develop models that incorporate statistical measures

### Interpret and communicate

• Students decide key results to include in a data report that answers the statistical investigative question
• Students communicate their results through, for example, a data visual, a poster, a video, a data story
• Students explore and share explanations, paying careful attention to what conclusions the data supports. They consider which alternatives are reasonable given the variability in findings

## What are Data Science K-10 Big Ideas?

Data Science K-10 Big Ideas are descriptions of the most important content in data science through the grades to help focus attention on ways to increase data literacy. Big ideas are those that are central to the discipline of data science, and that link understandings into a coherent whole. (Read Overview)

## How do I use these materials?

Teaching to big ideas in data science means choosing tasks and data talks that give students’ experience inside the big ideas. When teaching to big ideas many different content areas are usually met, as the tasks offer rich learning experiences. (Read Overview)

## With Thanks

With thanks to the people who gave feedback on the big ideas:

Dr. Pip Arnold
Director at Karekare Education, New Zealand

Dr. Denise Spangler
Dean of Mary Frances Early College of Education
University of Georgia, USA

## Woodside School Video and Lesson Plan

Our thanks to the teachers from Woodside school for their help with the ideas.

## References

Arnold, P., & Franklin, C. (2021). What Makes a Good Statistical Question?. Journal of Statistics and Data Science Education, 29(1), 122-130.

Bargagliotti, A., Franklin, C., Arnold, P., Gould, R., Johnson, S., Perez, L., & Spangler, D., (2020). Pre-K – 12 Guidelines for Assessment and Instruction in Statistics Education II (GAISE II): A Framework for Statistics and Data Science Education. Retrieved from: https://www.amstat.org/asa/files/pdfs/GAISE/GAISEIIPreK-12_Full.pdf

K-12 Computer Science Framework Steering Committee. (2016). K-12 Computer Science Framework. ACM. Retrieved from: https://k12cs.org/

Seehorn, D., & Clayborn, L. (2017, March). CSTA K-12 CS Standards for All. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (pp. 730-730).