[comte7092]

> Every high school student should learn how to grapple with uncertainty, how to evaluate statistical claims and experiments, how to interpret graphs and charts, understand how machine learning models work (at a high level), and internalize concepts like "significance", "error bars", and "expected value."

Pet peeve: can we just go back to calling these things statistics?

While I agree with you that statistics should be more heavily emphasized at the high school level, the issue goes much deeper within American math education that the one class.

[roddylindsay]

I would assume that a data science class is mostly "good old statistics." But if "data science" is the phrase that gets education boards to put more student butts in seats in stats class, I'm all for it.

[xtiansimon]

Wouldn’t a data science curriculum be more multi-disciplinary than a ‘statistics’ course?

Visualization, scripting, data collection, models, simulation. EDx had a great course by Guttag and Grimson. Add to this Scott E Page’s Model Thinking. Add EDx Data Analytics and Learning From UT Arlington. And some Tufte.

I say these because i work in the accounting field and brought scripting to my firm from my own self-study. It’s been a super power for me, and solved several problems which my colleagues had tackled using Excel alone.

I’ve also studied statistics, but found it less generally useful.

[comte7092]

>Wouldn’t a data science curriculum be more multi-disciplinary than a ‘statistics’ course?

I would say yes, however, the items listed in the comment I quoted fall squarely within the realm of statistics. I don’t have a problem with calling a curriculum of statistics + data manipulation tools “data science” but that’s not what’s realistically being covered in these high school programs.

[xtiansimon]

> concepts like "significance", "error bars", and "expected value."

Yes. I see what you're responding to--these are squarely in the statistics domain.

> not what’s realistically being covered in these high school programs.

Yes. Where the rubber meets the road. Who exiting from higher education now will have the skills to teach this imagined hybrid course? Realistically, they have to be vetted and hired by the mathematics department and satisfy some state and/or federal standards of education, which are currently staffed by educators who themselves are following standards of their office.

I was responding to the OP's premise:

> "data science" course, if designed properly, will be far more useful to students and beneficial to society than calculus.

Whether or not that objective is "realistic" given the current boundaries perscribed for high school education is another matter.

There is hope; there are modern thinkers in education out there. I referenced the UT Arlington course students and instructors referred to as DALMOOC (google it). I took this course thinking it was another data science course, and found a course taught by teachers for teachers. I hung in because their ideas were so fresh and interesting.

DALMOOC's ambition was to train teachers to encourage students to use social media to communicate their learning results, and in turn produce the data that the teachers were being traind in the course to analyze using social media analysis techniques. DALMOOC professors encouraged participants to generate social media responses to DALMOOC coursework. Very modern. Not sure how long before professors like George Siemens, whose brainchild DALMOOC was, get into state and federal positions of authority and influence to see their modern ideas at the high school level.

https://en.wikipedia.org/wiki/George_Siemens