16 years ago, SSA included in its initial (2003 – 2007) Strategic Plan something called Strategic Objective 8: 

Promote the development and adoption of a [national] statistics course for Years 11 and 12 at school, based on the best teaching practices that can be utilised, together with appropriate training programs for teachers.

16 years later, some basis has been provided for this. 

The International Data Science in Schools Project (IDSSP, www.idssp.org) is a cross-disciplinary project involving an international team of computer scientists and statisticians from the leading professional organizations for both disciplines. Its purpose is to promote and support the teaching of Introductory Data Science, particularly in the final years of schooling, by developing

• a framework for introducing data science including topics, learning outcomes, and sample lesson plans
• excellent modular teaching and learning resources and associated assessment rubrics
• a moderated portal for ongoing sharing of materials and experience
• professional development services for teachers and teacher trainers

The project comprises two phases:

Phase 1. Develop a curriculum framework as the basis for development of resources to support teaching students a pre-calculus course on Introductory Data Science;
and
a corresponding framework to teach teachers how to teach students Introductory Data Science.

Phase 2. Develop the resources to support courses based on the curriculum frameworks, and devise and implement a course aimed at prospective teachers of Data Science.

The online report, Curriculum Frameworks for Introductory Data Science, sets out the frameworks developed under Phase 1.

The impetus for this project was a high-profile workshop, STEMS2016, held in response to the critical shortage of data scientists entering the workforce. It was initiated by the Statistical Society of Australia and involved academia, government and industry.  As a consequence, the SSA collaborated with the NZSA to scope an activity targeting school students and their teachers.  At first it was confined to Statistics education, but it rapidly became apparent that the great Data Science tidal wave was about to overwhelm everything, hence the broadened scope, and the strong representation of computer scientists, not to mention the strong support of the ACM, the world’s leading Computer Science society.

It is envisaged the Frameworks developed to date will be used not just in schools, but also as a valuable source of information for data science courses in community colleges and universities and for private study.

The supporting societies are now pondering how to build on this work.  The most ambitious option is to seek the funding to support a major international project to complete Phase 2.

For further information please send email to idssp.info@gmail.com, or visit www.idssp.org.

Nicholas Fisher