This week has been very busy with work - we've been going full out on a couple development projects for clients, in addition to preparing for the The Write Stuff in San Francisco next month. As a result, I completely missed the kerfuffle over David Broder's test drive of Tesla Motor's Model S. Fortunately, Audrey Watters wrote a great post that helped me get up to speed (pun intended, and sorry).
Audrey's piece led me to this writeup by Tim Stahmer on interpreting data, and how the same data set can tell different stories to different people. While this is no surprise to people who work with both data and people, there is nothing like life to muck up the illusion of precision that a curated data set can suggest. This is something that I was thinking about earlier this week within the context of the push to collect more student data in the service of what people are calling "personalized" learning.
I left a comment on Tim's post; the crux of it is this:
What would be needed to get an educator and a student voice into the conversation about what data means? Hard drives of data are being collected about schools, teachers, administrators, and students. Largely, the subjects of that data - the teachers and the students - aren't given access to the data, and are being told what it means. Why shouldn't teachers and students be able to look at the data, and participate in the conversations that are defining what people call their performance? I'd be particularly curious to hear about the gaps between what the data measures, and what the learners consider important. Increased access to data could be used a springboard to teacher-driven action research. Student analysis of their data would be, at minimum, an awesome math class.
But, most importantly, why should the subjects of the data collection be cut out of the analysis that is being used to define their growth? What efforts, if any,are underway to guarantee that students and teachers can have full and complete access to the data collected about their work?