Living the interface between learning analytics and actual change in a HE setting
This has corrupted twice, so I'm just going to post quick links to the stories Check your photo - inbuilt bias? https://twitter.com/CatHallam1/status/1114590857397788673 Class Care System My children's secondary school has a behaviour system that sends me updates about their (mostly brilliant) behaviour. The data isn't terribly useful and I have grave concerns about their …
Continue reading Big data/AI: examples of concerning practice unintended consequences
In the first term of my first year, I skipped a seminar on DH Lawrence. My tutor, Dr Mara Kalnins, pulled me up at the start of the next seminar and politely expressed her disappointment. She also asked me to make up what I'd missed by reading about Carl Jung. I'm not sure that what …
Continue reading Five questions about learning analytics ethics
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
A few years ago a colleague attended an event with a company of data specialists. The company was experimenting with personalised learning for professionals. As I understand it they had lots of interesting ideas about personalising online learning. For example, if you got an answer wrong about marketing, you'd be routed to an easier set …
I love this photo. It is of the Boulevard du Temple, taken by Louis Daguerre in 1838. It's possibly the first ever photo showing a human being. In the bottom left of the picture, there's a man having his shoes polished and the bootblack polishing them. They appear because they were standing long enough to …
Continue reading The first ever photo to feature a human being
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
There are many articles that I wish I had written This is one of them Joi Ito dives into the, hopefully, by now familiar argument that even if the maths is right it can still be discriminatory.
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)
