Coalition members Emmanuel Schnazer (Bootstrap World) and Dan Schneider (Code.org) have collaborated with DS4E staff to develop an in depth specification guide that offers a pathway for individuals to find, clean, document, and upload datasets that can be used in K-12 data science tools. DS4E will support implementation of this work through creating a centralized and open hub of datasets with these guidelines.

TERC, Concord Consortium and NetApp share insights and discoveries from their collaboration around the NetApp's Data Explorers Program. Read this report on how to teach data science starting at a young age and learn about the potential of out-of-school data education experiences.

‘Teach Data Literacy: a guide for primary teachers’ is a resource developed by the Data Education in Schools team to support teachers to enhance opportunities for all to build the skills and habits of mind relevant to data problem-solving. The guide offers practical guidance, links to resources and a poster to support teaching data literacy skills and concepts across the primary curriculum.

This interactive map gives each state a letter grade for its level of progress in implementing data science education. Each state has a summary, links to curriculum standards, and suggestions for change. Interested parties can also follow links to Center for RISC resources for taking action.

Developing claims from data is different than from prose. We have developed a framework to think about key components that users need to integrate (Content, Visuals, and Data) to arrive at a Claim. Additionally we think through what are the cognitive steps that we take as we integrate these different components, and thus what are questions we can use to scaffold our learners ability to do this themselves.

This guide breaks down the reasons why data science education is important for student success in school and in their careers. It provides information on a decade of research & development on data science education programs by the National Science Foundation (NSF) and Institute of Education Sciences (IES). It also overviews recommended next steps by IES.

The Research on Data Science issue contains multiple articles centered on implementing data science education. Some of these topics include data science projects in school, teaching and learning data-driven machine learning, integrating humanities and data science, and many more.

This report entails recommendations and best practices to support AI and data science education in primary schools through graduate school. It considers the current landscape of efforts, access, and participation gaps experienced by historically marginalized youth and young women, as well as challenges and successes they have observed in their own settings, to provide key recommendations for policymakers and implementers to achieve the goal.

The Transforming Education Report shares the views of over 37,000 of the world’s students from 150 countries. It aims to show how including young people in conversations about education can help to achieve Global Goal 4 and prepare this generation of learners for their future.

DS4E coalition member, Victor Lee, and colleague Victoria Delaney, share an overview of the two most common Data Science curriculum; Intro to Data Science, and Bootstrap: Data Science.