Posts on the use of data to understand and improve teaching and learning processes. This may include activities otherwise known as “curriculum analytics” etc.
Earlier this week I did a presentation to a group from Dutch Universities on the ethics work that Jisc has done alongside its studies, pilots and services on the use of data. This covered the development of our Learning Analytics Code of Practice, as well as our plans to apply that Code to wellbeing applications, […]
With the GDPR having now been in force for more than six months, my talk at this week’s EUNIS workshop looked at some of the less familiar corners of the GDPR map. In particular, since EUNIS provided an international audience, I was looking for opportunities to find common, or at least compatible, approaches across the […]
An interesting observation made by a Dutch colleague earlier this week. The arrows in my standard model of learning analytics (here rearranged and recoloured to match the “swimlane” visualisation of the learning process) all mark “gatekeeper” points where information flow is filtered and reduced. Between Collection and Analysis there’s a necessity/relevance filter so that not […]
Recently I’ve been presenting our suggested legal framework for learning analytics to audiences involved in teaching, rather than legal people. For that I’ve been trying out a different visualisation, which considers the teaching process as involving three layers: Teaching itself (red): during which we process the personal data that’s needed to help students learn. The […]
Since there was a lot of interest in my keynote presentation at the EUNIS 2018 conference last week, this post collects together the slides and the blog posts that provide further analysis and discussion of the ideas: Slides LA and GDPR v0-07 How to do Learning Analytics under the GDPR The role(s) of Consent Incorporating […]
Learning analytics dashboards, like the class mark books that long preceded them, show tutors a lot of information about their students. That could be pretty intrusive, so should universities and colleges be asking students to consent before tutors look at their data? I don’t think so, both because the students most likely to benefit are […]
In thinking about the legal arrangements for Jisc’s learning analytics services we consciously postponed incorporating medical and other information that Article 9(1) of the General Data Protection Regulation (GDPR) classifies as Special Category Data (SCD): “personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, or trade union membership, and the processing […]
Reflecting on the scope chosen by Blackboard for our working group – “Ethical use of AI in Education” – it’s worth considering what, if anything, makes education different as a venue for artificial intelligence. Education is, I think, different from commercial businesses because our measure of success should be what pupils/students achieve. Educational institutions should […]
Last week I was invited to a fascinating discussion on ethical use of artificial intelligence in higher education, hosted by Blackboard. Obviously that’s a huge topic, so I’ve been trying to come up with a way to divide it into smaller ones without too many overlaps. So far, it seems a division into three may […]
One of the concerns commonly raised for Artificial Intelligence is that it may not be clear how a system reached its conclusion from the input data. The same could well be said of human decision makers: AI at least lets us choose an approach based on the kind of explainability we want. Discussions at last […]