Living the interface between learning analytics and actual change in a HE setting
I have just taken part in a panel discussion at the Jisc Digifest 2019 event. The session was called Excellence from Analytics. I know that, as a panel, we all worried about whether we'd been informative (or excellent), but I found it really interesting to listen to the other panellists talk (perhaps not the point). …
Continue reading Excellence from Analytics: Panel Discussion at Digifest, 12th March 2019
One of the benefits of learning analytics is the capacity to not just automatically analyse data, but also to automate some or all of the next steps. I'm primarily interested in learning analytics for student success, for me the automatic alert when a student is potentially at risk of failure is key. Whether red flags …
Continue reading Issues using data-based alerts in learning analytics
In November 2018, the UK Parliamentary All Party Group on Data Ethics launched a call for evidence about the use of data and machine learning in four areas: Education Healthcare Autonomous vehicles Policing With the help of some excellent colleagues, I submitted a paper on behalf of the institution (Nottingham Trent University) outlining our great …
Continue reading Submission to the All-Party Group on Data Ethics
I hate writing policy. I agonise over the words that feel so important at the time and know damn well that almost no-one's going to read it. But imperfect as it is, it's a framework/agreed set of standards that we can work towards. This piece is a work in progress, a public draft if you …
I've spent the past week thinking (probably overthinking) about this. So I've written up a modified learning analytics cycle. Obviously it starts with Doug Clow's model as discussed in the last entry. However, I've added details about the institutional infrastructure and decision-making needed to actually enable learning analytics to happen. Each of the branching arms …
Continue reading A modified learning analytics cycle (I really need to write more exciting titles)
One of my first jobs after graduating was training students in transferrable skills. I read an enormous amount of training theory, text books on time management, systems-thinking, NLP, public-speaking etc. Certain keystone ideas stuck. One was of course David A Kolb's (1984) experiential learning cycle. I can remember explaining it by modelling the process of …
Okay the title (and the whole page actually) is a little passive aggressive, but I'm reading lots of retention literature at the moment and I'll be honest, I'm sick of reading "Student retention has been a concern for some time now". A couple of smart colleagues have pointed out that the language used has changed(*) …
Continue reading Student Retention Research: A History Lesson
One of my many failings is my inability to live tweet conference sessions. I mean that I just about manage to quote profound micro statements with an out-of-focus picture of a slide, but I generally have no idea what it meant two weeks later. Let's see if I can make anything better from my 35 …
I'm most of the way through Nate Silver's "The Signal and the Noise: the art and science of prediction" I'm really struck by the fact that as I'm reading, I'm learning new tools and reference points to critique our learning analytics work. It's quite possible that if I'd a background in social sciences, mathematics or computer …
Student Engagement drives the learning analytics resource we use. That is, we count students' use of various electronic proxies that are associated with participation on a course. However, before discussing those, I want to explore the concept of student engagement. In the UK there are broadly three definitions of student engagement: Students engaging with the …
