Below are the notes and slides from my talk yesterday at Columbia University.
Data, we're told, will allow us to address our most pressing questions in education. But as the uses I've just detailed suggest, it matters who asks those questions, what constitutes those questions. These questions are what shape the algorithms that we build to answer them. And I'll add too that the metaphors we use shape the models we build as well. What does it mean if we decide student data "the new oil"? What does it mean if we view students (and their data) as a resource to be mined and extracted? What's gained? What's lost? What's depleted? Who profits? Who benefits?