“Wait for it!” – Problems using predictions to instigate COVID 19 lockdowns

The reaction time of a typical human being is apparently 250 miliseconds. In other words, it takes us about quarter of a second to get out of the way of a speeding snowball, or catch the dropped vase. That stuff's easy - 1. Danger - 2. React - 3. Try not to look embarrassed when our response …

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Minimising Risk vs Maximising Success: learning analytics intervention strategies

At the other end of the phone is a student. Your learning analytics tool has predicted that they may be at risk of early departure. Under the circumstances they are likely to benefit from a supportive, sympathetic conversation, or perhaps they need a nudge or a jolt to make them realise they need to re-engage. …

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Onwards from Learning Analytics (OfLA)

At the time of writing, we are entering the final year of our latest Erasmus+ collaborative project. Onwards from Learning Analytics (OfLA) is a learning analytics project interested in supporting students at risk of leaving university early or failing to achieve their potential. We don't take the view that students ought to be retained no …

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Black Box Thinking – a review and a challenge to universities

This post is a piece of procrastination. And I'm partly writing it because Matthew Syed brilliantly describes a form of procrastination in his excellent book Black Box Thinking, but truthfully I'm just procrastinating because I'm putting off a task that I'm finding difficult. 🙂 The book deserves a better review than this, because I think it's …

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Six essentials institutions need to get right to implement learning analytics

Between 2015 & 2018, we worked alongside some brilliant colleagues in KU Leuven and Leiden University on the ABLE Erasmus+ Project. I think that we spent longer on learning analytics infrastructure and operations than we would have liked. However, doing so gave us really interesting insights into the challenges of implementing learning analytics. By the …

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The effectiveness of learning analytics for identifying at-risk students in higher education – an extra titbit

I've recently published a paper with a colleague Dr Rebecca Siddle for a special edition of Assessment and Evaluation in Higher Education, The paper explored the impact of 'no-engagement' alerts for identifying students in need of further support and contrasted it with using background characteristics. In this paper, we used widening participation status as a …

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Grab bag of papers on Student Success Early Warning Alerts

I'm working on a research project with one of our academic Schools. We already have a process where we use data from our learning analytics resource to conduct mid-term reviews. The idea of the review is that we identify students most at risk of dropping out and the School contacts them. We've always run this …

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Male Access and Success in Higher Education

In 2011, we wrote a short chapter for the then Higher Education Academy about one aspect of our HERE Project work: male student retention. It was probably far from ground-breaking, but it was quite important for helping us to think about some of the issues associated with student success. The data we looked at appeared …

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