What follows is a summary of Gašević, D., Dawson, S., Rogers, T., & Gasevic, D. (2015). Learning analytics should not promote one size fits all: The effects of instructional conditions in predicating learning success. The Internet and Higher Education, 28, 68–84. doi:doi:10.1016/j.iheduc.2015.10.002 I’ve skimmed it before, but renewed interest is being driven by a local
The first key takeaway from Motz, Teague and Shepard (2015) is Learner-centered approaches to higher education require that instructors have insight into their students’ characteristics, but instructors often prepare their courses long before they have an opportunity to meet the students. The following illustrates one of the problems teaching staff (at least in my institution)
In a bit more than an hour I’ll be talking to @catspyjamasnz trying to nut out some ideas for a project around LX Design and Learning Analytics. The following is me thinking out loud and working through “my issues”. What is LX Design I’ve got some vague ideas which I need to work on. Obviously
I started playing around with what became learning analytics in 2007 or so. Since then every/any time “learning analytics” is mentioned in a university there’s almost an automatic mention of dashboards. So much so I was lead to tweet. @s_palm Well everyone knows that “real” LA requires a dashboard — Don Quixote Jones (@djplaner) June
The Moodlemoot’AU 2015 conference is running working groups one of which is looking at assessment analytics. In essence, trying to think about what can be done in the Moodle LMS code to enhance assessment. As it happens I’m giving a talk during the Moot titled “Four paths for learning analytics: Moving beyond a management fashion”.
The following is a summary and ad hoc thoughts on Macfadyen et al (2014). There’s much to like in the paper. But the basic premise I see in the paper is that to fix the problems of the current inappropriate teleological processes used in institutional strategic planning and policy setting is an enhanced/adaptive teleological process.
The following is a place holder for two presentations that are related. They are: “Four paths for learning analytics: Moving beyond a management fashion”; and, An extension of Beer et al (2014) (e.g. there are four paths now, rather than three) that’s been accepted to Moodlemoot’AU 2015. “The four paths for implementing learning analytics and
Trying to capture some thinking that arose during an institutional meeting re: learning analytics. The meeting was somewhat positive, but – as is not uncommon – there seemed to be some limitations around what learning analytics actually is and what it might look like. Wondering if the following framing might help it draws on points
On Monday I’m off to a rather large meeting to talk about what data might be usefully syndicated into a integrated dashboard. The following is an attempt to think out lod about the (P)IRAC framework (Jones, Beer and Clark, 2013) in the context of this local project. To help prepare me for the meeting, but
In Jones and Clark (2014) we drew on Damien’s (Clark) development of the Moodle Activity Viewer (MAV) as an example of how bricolage, affordances and distribution (the BAD mindset) can add some value to institutional e-learning. My empirical contribution to that paper was talking about how I’d extended MAV so that when I was answering