Submission to the All-Party Group on Data Ethics

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 …

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A modified learning analytics cycle (I really need to write more exciting titles)

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 …

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Learning Cycles & Feedback Loops

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 …

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Thoughts & lessons from LSAC 2018 (22nd – 23rd October 2018, University of Amsterdam)

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 …

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“Protect us from Newton’s single vision”: or why is a humanities graduate working in big data?

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 …

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Weapons of Math Destruction: How big data increases inequality and threatens democracy

Like the last post ('Everybody Lies'), Weapons of Math Destruction is written by a data scientist. However, there is a significant difference between the tone of the two texts. Seth Stephens-Davidowitz is clearly a bright guy, still fascinated with the potential of big data (although make no mistake, he can see the flaws and potential …

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