Here are the slides from my keynote at Thompson Rivers University’s Teaching Practices Colloquium this morning. I quite like the mediaeval theme (thanks ChatGPT), which I created to provide a constant reminder that the problems we have to solve are the direct result of decisions made 1000 years ago. There was a lot of stuff from my last book in the talk, framed in terms of Faustian Bargains, intrinsic motivation, counter technologies, and adjacent possibles. This was the abstract:

Why is it that educators feel it is necessary to motivate students to learn when love of learning is a defining characteristic of our species? Why do students disengage from education? Why do so many cheat? How can we be better teachers? What does “good teaching” even mean? And what role does technology play in all of this? Drawing on ideas, theories, and models from his book, How Education Works: Teaching, Technology, and Technique, Jon Dron will provide some answers to these and many more questions through a tale that straddles most of a millennium, during which you may encounter a mutilated monk, a man who lost a war, a robot named Claude, part of a monkey, and an unsuccessful Swiss farmer who made a Faustian bargain and changed education forever. Along the way you will learn why most educational science is pointless, why the best teaching methods fail, why the worst succeed, and why you should learn to love learning technologies. There may be singing.

I had a lot of fun –  there was indeed singing, a silicone gorilla hand that turned out to be really useful, and some fun activities from which I learned stuff. I think it worked fine as a hybrid event. It was a sympathetic audience, online and in-person. TRU has a really interesting (and tension-filled, in good and bad ways) mix of online and in-person teaching practices, and I’ve met and listened to some really smart, thoughtful, reflective practitioners today. Almost all cross disciplinary boundaries – who knew you could combine culinary science and nursing? – so there’s a lot of invention going on. Unexpectedly, and far more than from a lot of bigger International conferences,  I’m going to go home armed with a whole bunch of of new ideas.

Dron, J. (2024). Learning: A technological perspective. Journal of Open, Distance, and Digital Education, 1(2), Article 2. https://doi.org/10.25619/dpvg4687

My latest paper, Learning: A technological perspective, was published today in the (open) Journal of Open, Distance, and Digital Education.  Methodologically, it provides a connected series of (I think) reasonable and largely uncontroversial assertions about the nature of technology and, for each assertion, offers some examples of why that matters to educators. In the process it wends its way towards a view of learning that is firmly situated in the field of extended cognition (and related complexivist learning theories such as Connectivism, Rhizomatic Learning, Networks of Practice, etc), with a technological twist that is, I think, pragmatically useful and theoretically interesting. Much of it repeats ideas from How Education Works but it extends and generalizes them further into the realms of intelligence and cognition through what I describe as the technological connectome.

I wrote this paper to align with the themes of the journal so, as a result, it has a greater focus on education than on the technological connectome, but I intend to write more on the subject some time soon. The essence of the idea is that what we recognize as intelligent behaviour consists largely of intracranial technologies like words, symbols, theories, models, procedures, structures, skills, ways of doing things, and so on – our cognitive gadgets – that we largely share with others, and that exist in vastly interconnected, hugely recursive, massively layered assemblies in and beyond our heads. I invoke Reed’s Law to help explain how and why this makes our intracranial cognition so much greater than the neural networks that host it: it’s not just the neural connections but the groups and multi-scaled clusters of technological entities that emerge as a result that can then be a part of the network that embodies them, and of one another, and so on and so on. In passing, I have a vague and hard-to-express hunch that the “and so on” is at least part of the answer to the hard problem: networks that form other networks that themselves become parts of the networks that form them (rinse and repeat) seems like a potential path to self-consciousness to me. However,  the ludicrous levels of intertwingularity implied by this, not to mention an almost total absence of any idea about the underlying mechanism, ties my little mind in knots that I cannot yet and probably will never unravel.

At least as importantly, these private intracranial technologies are in turn parts of even greater assemblies that extend into our bodies, our environments, and above all into the technologies around us, and thence into the minds of others. To a large extent it is our ability to make use of and participate in this extended technological connectome, that is both within us and beyond us, that forms the object, the subject, and the purpose of education. Our technologies as much form a part of our cognition as they enable it. We continuously shape and are shaped by them, assembling and reassembling them as we move into the adjacent possibles that result, creating further adjacent possibles every time we do, for ourselves and others. There is something incredibly awesome about that.