Dec 09

Supercomputing 2010

Happy national computer science week. That we haven’t heard about it, or don’t much care, is some sign that computing isn’t much on our minds, at least not in popular culture or in the culture of K-12 education. My own antennae have been tuned to the need to develop computational science and engineering literacy first through my years of teaching Engineering Ethics just out of graduate school, but much more recently through my affiliation with the Education Program of the Supercomputing conference series. As technology revolutionizes the ease with which data is gathered and analyzed, it becomes more important to be able to make sense of it, and to appreciate what’s under the hood of the data delivery systems we’ll encounter. Tim Berners-Lee has recently argued that data mining is the new stock in trade even for journalists. Those of us reading what scientists, engineers, or even well-educated journalists pull together have got to be well-enough acquainted with the processes involved that we do not feel alienated from them.

Earlier this month I traveled to New Orleans to attend SC10 to reestablish my connection with colleagues in the education program. (The image set embedded above are just a few slices from that trip.) We are collaborating with some of these folks on a proposal to foster computer literacy in K-12 schools here in Michiana. Whether we’re funded this round or some other, we’ll stay with the effort. We’ve got to. Our experience building integrated STEM community has made it clear that one defining cultural difference separating STEM professionals from K-12 students (and often teachers) can be illumined by one single question: do you have any data that matter to you? STEM professionals typically do, whereas pre-college folks typically don’t. And since they don’t have data that matters to them much, neither do data analysis tools much matter outside of STEM professional circles. They may have some exposure to some of these tools, but few (with exceptions) are much excited about Excel…let alone MATLAB, or C++.

But that can change. Tools for gathering and processing data are becoming widely available and easier to use. Just below is a map of plants gathered by school children in Northern Uganda. There’s something about noticing your world and sharing about it online that increases the value of our surroundings. All of the tools used to generate this map and data associated with it can be assembled by anyone, for any purpose. Watch carefully: data that matters is coming to a venue near you. Citizen science. Citizen journalism. Digital ethnography. Let’s build a community that prepares its citizens for this age of data analysis by helping motivate students to peek under the hood.