Near Future Teaching Video Post #4: Data and Automation

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We continue our journey through the future of digital education at the University of Edinburgh via the Near Future Teaching project. Today’s post introduces the themes of data and automation, which are particularly topical for all of us at the University. In our discussions with students and staff, scandals like the Cambridge Analytica/Facebook revelations, increased academic and research emphasis on data ethics, and the planned City Deal work on data skills and citizenship have created an emphasis on the need to educate for a critical understanding of the impact of datafication on our lives.

At the same time, multiple reports on AI, automation and the future of work have driven a wide discussion about the future purpose of education, and its fit-ness for a society where employment, labour and work are radically reconfigured. These two themes emerged strongly from our discussions with students and staff and, while often framed positively, they also present us with important challenges.


In project interviews and discussions, the datafication of society was seen to have implications for education across all sectors and beyond into our daily lives: the data trails we generate as digital citizens, and the surveillance regimes that feed on these; data driven decision making by institutions, governments and corporations; the attendant questions of privacy and ethics; the impact of data on the media and the political sphere; and the concentration of influence in particular algorithms and platforms.

You have all these companies, private companies, and they’re all gathering data and they’re using that for a lot of stuff and we have algorithms and even the makers don’t know what the algorithm is doing anymore. And it’s still making big decisions like how are we gonna get around that and how is that going to affect education?

– Charlotte Rixten, MSc Collections and Curating Practices

This disconnect is echoed in reservations about the permanence or visibility of the data being generated in teaching contexts, how it reshapes the intimacy of educational exchanges, and how it circulates beyond the University:

I do feel it needs to be protected within the university systems because sometimes I’m concerned that stuff…may be distributed through all the various social medias. And to make a lecture more engaging, I will give examples, although they’re anonymous. But I wouldn’t want all these sorts of things, although they’re unidentifiable, to go out into the main domain. So, they keep encouraging us to put more information online, or in other platforms, but sometimes I worry, when I put out there, where does it end up?

–  Gidona Goodman, University Veterinarian

This question of control is seen by many as a fundamental educational issue in itself – alongside data skills, critical understanding of data seen as a priority for the future of our teaching:

Students need to be taught critical thinking and critical approaches to information and data. I see systems will have moved on exponentially. But understanding how these systems came into play, and that it was humans or bots that were programmed by humans, or bots that are programmed by bots that are programmed by humans, that there is always an underlying power structure. And I see that we should be better sociologists of our IT infrastructure.

– Melissa Terras, Professor of Digital Cultural Heritage

Automation and AI

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The research suggests that automation is driving plenty of discussions around educational futures, as the future of work becomes a topic of intense debate. Some of this automation is being increasingly extended to aspects of teaching: how personalisation of learning might be enabled by adaptive learning aided by artificial agents; or how automated assistants might help with the routine administration and delivery of aspects of teaching in at-scale classes. This new kind of hybrid human/machine teaching model, where automated technologies assist teachers with aspects of some, but not all, the teaching function, was emphasised in our discussions:

I don’t think it [technology] will replace teachers soon, I think that what we need to do is to try to make technology and teachers work together.

– Anna Domalga, Course Administrator, School of Economics

The theme of automation – ‘freeing up’ human teacher time to focus on ‘higher level’ tasks – features strongly.  For example, some suggested the role of AI and automation could ease ‘pastoral workload’:

Outsourcing some of that pastoral workload to automated scripts will help to sort of free up the lecturer or the tutor’s time to actually talk to the students about what matters to them. That’s something that I personally am quite excited for, I think it will free up a lot of lecturers’ time.

– Jill Mackay, Research Fellow in Veterinary Medical Education

Also, the task of helping students identify quality academic content could become increasingly automated:

[automation] is going to transfer into higher intellectual realms. Such that a student will be writing an essay, and will literally ask the computer, what did Heidegger say? And the best pieces of content will come right at them, and that’s profound.

–  Brendan Hill, Learning and Engagement Consultant

These questions around data use and automation are contentious as well as highly current and will need to be carefully accounted for as we plan for the future of digital education globally, and locally.

Michael Gallagher

Dr Michael Gallagher is a member of the Centre for Research in Digital Education at Moray House and Director of Panoply Digital, a consultancy dedicated to mobile for development (M4D). His research focus is on mobility, mobile learning, and digital education to support teaching and learning in the humanities in higher education, particularly in the Asia Pacific and sub-Saharan African regions.

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