Keywords: data science education, high school, tools
Few high schools offer data science — yet. What will it look like, and what should it look like, when they do? Some exceptional high-school programs offer data science with R or Python; but many will probably begin (as we did) using other data-analysis environments in which students engage with large multivariate data sets to address questions of interest. What sorts of “data moves” can these students make? Is what they do really data science? What good can this kind of exposure do? In this brief talk, we’ll take a look at work from real live high-school students exploring public-transportation data from the San Francisco area using CODAP. We’ll pay particular attention to the way the students understand (and do not understand) filtering their data, grouping, and constructing aggregate measures.
Slides can be found here: http://eeps.xyz/sdss19