Ready for anything
What do students (and people) need to be ready for digitalisation?
Hello friends,
I’ve been back in Singapore nearly a month. (Today, August 9, is our annual National Day, commemorating Singapore’s 1965 separation from what is now Malaysia.) During this time, for #reasons, I’ve been thinking about the type of education system in which students learn how to detect, make sense of, and adapt to, continual and unpredictable change — the kind of change that happens when societies digitalise. My provisional conclusion is that developing digital proficiency will probably require letting go of our obsession with stable, legible ways of approaching teaching.
People tell me the first half of the year was unseasonably cool here. But it has been blazing heat since I got back in mid-July, interspersed with a few enormous tropical downpours. Plants grow fast in this abundance of light, heat, and water.
By design, the island’s urban fabric is interwoven with green things that want to grow and are well-placed to do it. Most days here, I walk by a jungly patch in the middle of an orderly, legible estate of high-rise apartments — a reminder of how quickly wildness would return if we stopped investing energy in keeping it at bay.
If you care to look, it’s easy to see humans continually labouring everywhere at maintenance: cutting grass, trimming shrubs, pruning trees. Singapore has learned how to become good at stabilising things and making them legible. This becomes a handicap in situations where stability and legibility are counterproductive.
Educating for digital proficiency is a good example of this.
Ready for anything
Educators in Singapore (and many other countries) are thinking about how to prepare students for a future where digitalisation touches even more parts of work and life than it already does. This after many decades during which success in pre-university education has often been measured in how well students acquire easily testable subject matter content.
New knowledge is always being created at the margins of mathematics, biology, history, languages, etc, but the core subject matter changes slowly or rarely. Singapore has built a stable, legible national infrastructure — curricula, teacher training programmes, a professional corps of teachers — that’s extraordinarily good at teaching stable, legible subject matter. We’re justifiably pleased with how effective it has been.
Being good at teaching stable subject matter will continue to be important, but it’s the wrong approach to preparing students for digitalisation. This is because digitalisation is neither stable nor a subject.
Digitalisation is an ongoing process involving a wide and growing range of technologies (e.g., machine learning, online card payments, programming languages, AR/VR), and a wide and growing range of mechanisms by which technologies affect life (e.g., interactions with information, social exchange, governance, business models, the nature of work).
The key feature of digitalisation as a process is continual and largely unpredictable change.
Digital technologies themselves are continually changing (e.g., programming languages or chip architectures) and the range of technologies is continually changing (e.g., the emergence of quantum computing or digital payment platforms).
As these technologies change or emerge, the mechanisms by which they affect life continually change too (e.g., how independent retailers’ cashflow management is affected by increasing digital payments, or how graphic artists’ jobs are affected by availability of generative AI tools, or what new business models emerge as a result of mobile coordination for physical services).
Because the technologies and mechanisms of digitalisation are continually changing, it’s a strategic error to think of digital proficiency as competency in specific technologies. It follows that it’s a tactical error to address digital proficiency with programmes for teaching specific technologies and their associated tools (e.g., courses in coding or using ChatGPT or whatever). This approach to teaching digital proficiency might be stable and legible but it will quickly go stale. Our instinct to stabilise things and make them legible is counterproductive.
It’s much more useful to think about digital proficiency as a capacity. Specifically the capacity to detect, make sense of, and adapt to continual and unpredictable change. My own view is that this capacity requires at least four skills that can be taught and learned:
Problem-finding: Knowing how to query whether a problem is framed correctly, and how to identify problems and validate problem framings.
Epistemological sophistication: Knowing how to identify and evaluate sources of information and frameworks for belief.
Equifinal thinking: Knowing that not all problems have single or already-known solutions, and knowing how to adjudicate between different paths to the same solution that have different characteristics (reliability, speed, cost, etc).
Computational thinking: Knowing how to compose and decompose systems, how to distinguish operations from inputs and outputs of operations, and how to establish scopes of applicability for operations and systems.
These four skills are generally useful for figuring things out, which means they are useful for living in a continually changing world which always needs figuring out. People who have these skills are better equipped to puzzle through a math word problem and solve it, figure out why the light switch isn’t working and fix it, notice when they’ve fallen into a filter bubble and find some new perspectives, or realise when their job is being replaced by computers and find a new job.
Teaching these skills is sometimes done in the form of specific courses built explicitly around them (such as Theory of Knowledge in the IB programme). My own view is that it is much more effective to incorporate these ideas into how individual subjects are taught.
I say this for two reasons. First, few students think critical thinking is valuable or exciting enough to take as a standalone course. Forcing the hard-core science/engineering student to take a course in critical thinking, or to take humanities courses to learn critical thinking, is likely to backfire. (The same might be true of forcing a humanities student to take engineering courses to learn computational thinking.)
Second, learning these skills happens more easily in context of concrete use. I was lucky to have encountered a scattering of rogue teachers during the twelve years I was a student in the Singapore public school system. I realised much later that these teachers had managed to teach equifinal thinking, epistemological sophistication, problem-finding, and computational thinking without using the labels (“equifinal thinking,” “problem-finding,” etc) — they just taught history, math, chemistry, literature differently.
They were rogue teachers in that they were often doing pedagogically unorthodox things. But they didn’t take extra class time to do it, and it happened within the same framework of standardised examinations (the GCE O- and A-Levels). Because they didn’t usually label what they were doing “teaching critical thinking,” it wasn’t synoptically legible that way.
Each of these teachers was using sneaky strategies to infiltrate the Singapore education system and teach content well, but in ways that also built student capacity to sense and adapt to unpredictable change. These sneaky strategies worked for teaching these critical thinking skills because of — not in spite of — their illegibility. And they worked where stable, legible teaching strategies usually fail. I’m pretty sure they would also be more effective in teaching students how to deal with whatever the digitalised world turns out to be.
Analogous to building intentionally malleable organisations that can deal with unpredictably changing demands, you could think of this approach to teaching digital proficiency as another instance of fighting fire with fire.
Other stuff
Next Thursday, 17/8: The eighth episode in an Interintellect series about not-knowing. We’ll talk about why not-knowing about value makes it hard to compare desired outcomes and to choose actions, but also creates space for new ideas of what should be valuable. More information and tickets here.
A few months ago, I spoke to Simon Höher and Andi Pawelke from Protocol about why public sector organisations find it hard to manage not-knowing, and what can be done about it. (Their writeup is in German, but machine translations are pretty good.)
Nolan Myers and Sid Sijbrandij are working on an initiative to develop incentive design as an academic discipline. I spoke to Nolan about some considerations when thinking about disciplines and how they form. Nolan also wrote a short review of the Uncertainty Mindset, which reminded me that concrete subject matter is usually more salient than the general theory that it illustrates.
This essay about a different kind of internet considers a counter-intuitive way personal data is a rate-limiter for the modern economy.
See you next time,
VT
Do you want to share any specific strategies the teachers used? Having a concrete example would be great!
Yes, It's important to teach future generations not so much about how the world is, but to prepare them to be able to change the world for the better. Critical thinking and problem solving skills are key in that.