There is a two-day workshop on The Foundations of Data Science for Students in Grades K-12 hosted at the National Academies. The workshop is in-person and online; if you registered (or if you did not!), you can watch a livestream here: https://www.nationalacademies.org/event/09-13-2022/foundations-of-data-science-for-students-in-grades-k-12-a-workshop-days-1-and-2
I’ll keep these short, as I might not otherwise share them (and I’d rather share something rather than nothing!).
I thought the three commissioned papers others wrote (on critical data literacies, the national implementation landscape, and tools to support data science) were … really good and complementary. The tools paper makes clear thoughts around the benefits and drawbacks of different types of tools (particularly: spreadsheets, visual tools, scripting/coding-based tools) that I’d been loosely pondering, but which had not coalesced for me until this point. The critical data literacies paper is a bit of a masterpiece (as was the presentation). The focus on a relatively small set of papers that exemplify what work with students intended to support a critical perspective was helpful; as was the constructive evaluation of the strength of the research evidence we have gained from those papers. The landscape paper helped me to see how there is a high degree of alignment across curricular standards and to understand how (surprisingly!) widespread - yet still limited in absolute terms - data science courses in high schools are.
There are many different perspectives and also values that participants in the workshop bring. This is a strength, especially at this early stage in the development/emergence of data science education. This also made it hard to see what consensus - if any - was growing about what we already know and should do next. Overall, though the variety of voices (and diversity in degrees of experience doing data science, statistics education, or CS Education research - and teaching - was a strength.
The hybrid modality worked well; it was good to see 100s of online participants and to hear their questions and ideas.
I have had the experience several times of hearing someone else say something that I thought or briefly considered; it was humbling and also validating to hear others’ more fleshed out thinking on - to pick out a random example - the importance of tools to support not just data analysis, but also data literacy.
The co-organizers, committee, and program officers and staff have done a great job; it’s a well-organized event.
The second day is - so far - more focused on identifying next steps, and I am keen to hear what others think these are and to try to sum up the latter half of the workshop tomorrow.