Multilitteratus Incognitus

It's week 4 of #cfhe12 so it must be time for Big Data and Analytics as the topic of discussion. It's interesting coming back to this topic of discussion because it was the topic of the first MOOC I took part in, LAK11, and it's a topic I've been thinking (or at least keeping on the back burner) since I was in business school. On of th things to keep in mind when talking about Analytics is that there are quite a few definitions out there , so, when talking about learning Analytics it is important to define what we aim to get out of our discussion about Analytics and how we wish to employ the potential insight that we get from this data. There are two topics that have recently come up in my neck of the woods: knowing what sort of data one can get from the various campus systems, and knowing what it means (and accurately representing what the data tells us). First, it's important to know what sort of data you can get out of your systems, like the LMS. As I've...

Yesterday and the day before, the Educause Learning Initiative (ELI) was hosting a spring focus session on learning analytics .  I have to admit that drew me to this talk (in addition to being interested in analytics of course!) was the talk that George Siemens presented at this ELI to kick things off.  The first day was quite productive, but the second day I had too many other commitments to attend to and could not attend for most of it. One of the back-and-forths that I had on twitter my colleagues was about learning analytics and assessment.  A fellow colleague seemed to be very certain that learning analytics could be used for assessment, and I disagreed.  It's hard to carry on a meaningful debate in 140 characters, so I thought I would write a quick blog post about it. And who knows, perhaps I mis-interpreted what my colleague was saying! First I think it's good to start off with a few definitions so that we are all on the same page: Learning An...