For a few years now I’ve owned a characterful Mini Cooper. I don’t drive it as much as I used to, but its red and white livery turns heads, especially when I drove it in a charity event alongside over a hundred other Minis!
With a bit of a soft spot for these cars, I went to visit the Mini factory in Oxford, UK to see how they’re made. The process of assembling Minis is a masterpiece of programmable predictability. Principles like continuous flow and ‘just-in-time’ production made the whole factory run like clockwork.
The factory achieved this because, in spite of the myriad of different models and options available, the fundamental processes were standardised. I watched as cars were built in the exact order customers purchased them; even though they might be assembling a green Mini Cooper followed by a blue Mini Clubman, each combination was of a finite set of ‘templates’ made possible through that same standardisation of parts and processes.
I was impressed as I watched the carefully choreographed process. Robotic machinery performed precise spot welds on the assembly line while other fully automated ‘trolleys’ delivered windscreens and dashboards from one station to another. When I stepped in front of one of these (because I’m like that), the robot stopped and waited for me to move before continuing its journey, no doubt silently judging me…
We call this whole approach the “Factory Model” for very obvious reasons! But what happens when we apply that same standardised approach to a school?
Instead of moving a car through the logical sequence of the Mini factory, we move around a thousand students simultaneously from Maths to Geography to a game of football then into an hour of learning a foreign language, then a bit of Shakespeare. Super logical, right?
The problem is that instead of precisely manufactured car components, we have children and young adults in all their unpredictable, creative, messy, and strongly opinionated glory. In the factory model, we don’t worry much about varying ability, level of interest, modes of learning, or cognitive overload.
For nearly a century, schools have been influenced by Frederick Taylor’s ‘Scientific Management Theory’. This ‘Taylorism’ is rooted in the idea that academic performance is entirely quantifiable. While this model has allowed us to scale education for a growing workforce, it might have come at a significant pedagogical cost.
We see the echoes of Taylorism today both in the classroom and in the exam hall. Factors such as ‘learning by rote’, narrowing of curricula, and assessing students within a finite time window, regardless of readiness, all come at the expense of breadth and individualisation.
Instead of "Tailored Learning," we got "Taylored Learning".
Many believe AI might redress this. We’re already seeing examples of AI used to augment lesson planning, evaluation, and marking. But the real question is: how ‘deep’ into the classroom should the technology go?
We must avoid using AI simply to make the old factory model ‘more efficient’ or ‘faster’, but at the same time avoid swapping one flawed model for another.
Standardisation makes so much sense for my Mini Cooper. It ensures that every bolt is in the right place (at least until I get the socket set out), and that every car is ‘programmably predictable’. But our students aren’t built from a finite set of templates, and they definitely don’t run as predictably as clockwork!
AI could be the opportunity to move away from the assembly line of ‘Taylored Learning’. If the technology that we put into our classrooms can be as patient as the robotic trolley in the Mini factory, pausing and adapting its pace for the human in front of it, we might finally stop treating students like car components!
This theme is explored in an upcoming paper, titled 'Lineage and Legacy - AI’s Place in the Evolution of Education Technology' - watch this space for more information.