As I reflect on yesterday's meetup, there's one topic that I don't think came up in the conversation. That's segmentation of students. We kept talking about "students" as if it was a homogenous entity. Is analytics good for students? What do we measure about students? What are the ethics around student data? I'd argue that many of these questions have different answers based on what type of students we are talking about.
For context, here's my background: B.S. in mathematics at a stereotypical 'small liberal arts college' (2,000 students, small classes, collegial campus). MBA at an R1 institution, and then taught as an adjunct for 10 years at a large open admissions school for non-traditional adult learners (U. of Phoenix). The proposition about analytics is different for all three..and DRASTICALLY different for the non-traditional adult segment. I had little to no exposure to the third group until I started teaching there in 2002, but I realize that it's a significant portion of "students" these days.
My point is that we need to acknowledge that there are different segments and we need to be a little more clear as to which group we're talking about since a single analytics solution might benefit one segment while simultaneously hindering another.