Learning: Knowledge, Meaning, Capability

Principles of #WorkingOutLoud allow us to revisit topics with which we feel familiar and comfortable – to question ourselves, to explore new facets, to ask ourselves questions, or address the practical things we have learnt whilst ‘in practice’. Today i am reflecting on aspects of learning design, relating to knowledge, the creation (and co-creation) of meaning, and the building of capability. With that in mind, a quick reminder of spaces: the blog is my first reflective space – so i feel no obligation to make this exploration complete or even fully coherent – if you want my ‘well considered’ work in this area, the ‘Social Learning Guidebook’ is the best place to start.

To the matter in hand: to what extent should we ‘teach’ or convey knowledge, to what extent do we create space to discover, and what, precisely, is it that we discover? Let’s start with some pragmatic definitions: considering ‘knowledge’ as discrete ‘truths’ which have been discovered, and validated, considering ‘meaning’ as the conceptual understanding we create, and considering ‘capability’ as the things we can do.

Let me try to illustrate that: i’m sat in a coffee shop – if the coffee machine breaks down, the quickest way to fix it will be through established knowledge – probably the manufacturer wrote a book of this, and people are trained. If that fails, the operators who have to deal with it’s quirks everyday may have some ideas too. A last resort is for me to fix it: i only have theoretical knowledge, no practical experience whatsoever.

Fixing this coffee machine can be achieved in a number of ways: through that formal codified knowledge, through experiential tacit/tribal knowledge, or, at a push, inference from theoretical knowledge, transposed from other fields (e.g. i know about pressure, about oils, organic chemistry etc).

Codified knowledge may be global: the same knowledge may fix this thing in Singapore or Seattle. Tacit/tribal knowledge may be variable: in Seoul a barista may know how to hit the machine on the side in just the right place – something explicitly forbidden by the manufacturer, but workable in practice. Tacit knowledge tends to be hyper local, and hidden, either accidentally, or by design.

Formal training tends to circulate formal knowledge: Social Learning may surface tacit and tribal knowledge, if we earn it, if we create the circumstance.

Now: in this sense, formal knowledge relates pretty closely to structural capability. If i run 3,000 coffee shops around the world, a strong programme of formal knowledge ‘teaching’, or mechanisms, technologies, and structures, of knowledge access, sounds like a good start.

Indeed, we could go further: if we use Social Learning approaches to ‘discover’ or mine the social knowledge, we can categorise it, into that which should be codified, extending our formal knowledge, or that which should be banned (e.g. it turns out that hitting the machine fixes this issue, but breaks the filter more often, overall increasing maintenance costs. This leaves us a secondary issue to ‘train out’, or address the ‘helpful’ local solution (which may be tied into the fact that the local barista may have unearthed a mechanical weakness in the overall system, but has no voice to be heard – it’s an open loop where feedback and potential learning is lost).

Taken as a whole, this rough example illustrates some key concepts: formal knowledge is owned and controlled, hence easy to ‘give’ to people, easy to ‘test’ for retention, even for application. But not necessarily ‘good’ or ‘right’. Scaffolded Social Learning approaches may enable us to enhance or amend this, or loop back to rectifying behaviour, or addressing local needs or issues. And, between these two things, capability may be built.

But coffee machines are one thing: what about e.g. leadership, or even something like ‘sales training’, or ‘strategy’. What about ‘mindfulness’ (if it’s really a thing), or ‘ethics’. Social skills, behaviour, things that are subjective, personal, practice based. Things that are contextual, possibly that do not have a global truth or reach. Probably, in fact, most of what we need to ‘perform’.

A reminder: these are very much a part of capably, but are not traditionally ‘teachable’. But nor are they innate. These are developed truths (philosophers and scientists may both throw up their hands at this) e.g. i find my truth, and you find yours. And then we ‘perform’.

Strengths and weaknesses: highly divergent (although possibly within frameworks or a matrix, if we can discern it), developed over time, not instantly, hard to measure, hard to spread, hard to control etc. But grounded in practice, often effective. Hard to share. This is a common truth: you and i may both ‘perform’ well, but by entirely different means (externally) and within entirely different cognitive and conceptual frameworks (internally).

Social Learning schemas may help us here, with caution: specifically narrative, storytelling approaches, whereby we can share something of that internal framework – because our individual learning may rely on the fracturing and reforming – constant iterative cycles of this – to change our conceptual frame of operation. I’ve written more about this process here.

Whilst Organisations are currently finding it useful to talk about Learning Science, we also have to remember that instructional design happens within a broader social context too: what learners expect.

It’s easy to dismiss that, but in reality it’s a dominant force. If learners expect to be told, and we ask them to explore, we may get lucky, and unleash them, or we may get unlucky, and confuse, annoy, or lose them altogether. I’ve had all three experiences in the last month alone.

It’s not that we need to ‘meet’ expectation, but we must defy it carefully.

Take it back to ‘knowledge’, ‘meaning’, and ‘capability’ – a foundational question we must ask is which one of these we want? Do we just need people to perform within an agreed matrix of capability, and do not care if they ‘believe’ it, or do we need people to construct meaning (from which they may build capability, if we support it), or do we just want to give them knowledge?

And does there always have to be knowledge? I’m struggling with this in a programme right now: i think it need largely to be about ‘meaning’, but i feel obliged to convey knowledge – probably partly to prove my worth, if nothing else. Because we are, of course, bound into the system ourselves.

Perhaps one simple answer is that we need everything: we need to teach, and we need to explore (in case it was not clear, i use ‘explore’ to describe this more socially collaborative model – where we focus on finding meaning).

But what if we cannot do everything – or if people do not want everything?

There is an additional tension to navigate: for global Organisations, the maintenance, validation, and support of, learning, is a long tail. Codified learning tends to have high up front costs, but it persists over time (usually for way too long). Social Learning, perversely in some ways, also has high up front costs – but not in the creation of assets – instead i think design itself is high – and so is facilitation, measurement, and validation, although emergent technologies are potentially impacting on this.

Specifically: we need some aspects of moderation (in some, not all, cases). And we need active connection and interconnection – essentially to find meta narratives and ‘truths’ at global levels. So e.g trends, sentiments, meta-analysis of narratives etc.

There is a risk that we are currently seeing the application of technology to Social Learning from the perspective of formalisation and scale – which are inherently unsocial – so we need to keep a close view on this.

Sharing this reflection as part of my broader work, through last year, and into this one, as i graffiti and rework my core pedagogical theory and work.