Learning Science: #WorkingOutLoud on Philosophical Approaches and Science

Today, i am continuing the work i shared yesterday, as part of the body of work i’m creating for the ‘Modern Learning Capability Framework’. This module covers Learning Science, with a view to helping people define their discipline and curate their professional space. Today we explore ‘Reductionism, Constructivism, and Emergentism’. Please note that this is shared as part of #WorkingOutLoud, and is incomplete at this stage: also, it’s part of a year long programme, so an extract may lack context e.g please be kind!

It’s probably fair to observe that approaches to Organisational learning can be characterised according to three core philosophical beliefs:

  • Reductionism is a belief that complex phenomena can be reduced to ever more simple constructs, and that ultimately we will discover the underlying building blocks. Reductionist approaches to learning seek to understand complexity by breaking it down, and typically leads to constructivist learning design. The scientific method is reductionist in nature, seeking to reframe magic as interaction which can be understood. Reductionism leads us to believe, for example, that capability frameworks are a valid approach to envisaging the development of capability, based on the premise that we have uncovered the building blocks.
  • Constructivism is, itself, a philosophical belief which holds that scientists ‘construct’ scientific knowledge, models, and ideas, which represent underlying reality. A constructivist would therefore believe that our understanding of the world is always a human construct, and, furthermore, that a range of varied constructs may hold true, including philosophical (belief based), as much as scientific (empirical, evidence based). Constructivism is represented in Learning Science typically through ‘Constructionism’ (note the typological distinction): this (broadly) builds out of Piaget’s work on knowledge and learning, and supposes that learners will create (construct) their own models of reality. One could argue that any approach to Social Learning is constructivism in nature, although i may personally hold back slightly from that view, as i prefer to consider that what we seek in Social Learning is ‘meaning’. In my understanding, it’s a rather more practical and applied activity.
  • Emergentism is a philosophical belief that, given the right circumstances, some form of meta-property may ‘emerge’. If we hold this belief in our approach to learning, then we inherently believe that the fire is lit within the learner: we create the space, conditions, knowledge, and opportunity, and capability just emerges. Much leadership development probably falls into this space, although it may BELIEVE that it is being constructivist, success is probably accidental or incidental (that view may not be widely held. I may be overly cynical in this respect.)

Beliefs in practice

Let’s just consider how these three principles may be expressed in Organisational Learning: the following statements may, or may not, be true. Part of building your own philosophy of learning (which may inform your discipline as a Learning Scientist), it to consider what you believe.

When learning follows reductionist approaches, we constantly seek to break down the observed phenomena into constituent parts, and to understand the sequencing of those to build capability.

For example, we would observe that some people are better at sales than others, and would seek to understand why (reductionism). We may determine that they hold specific knowledge, that they use specific scripts, that they have high emotional intelligence, that they are charismatic: there is literally no end to the number of ways that we may slice and subdivide the observed behaviour.

Having done so, we may consider how to ‘train’ that behaviour: for example, we may note that successful sales people only hold two meetings, instead of three, so we might script what they cover and train this into the sub-performing sales people, in the belief that we can get them to hold two meetings too, hence being more efficient and saving money and time.

We may build out complex maps of connected (or seemingly connected) behaviours, knowledge, skills, and even ‘mindsets’ that deliver success. Indeed, we may even come to believe that ‘mindset’ (emergentism) is key.

Perhaps we will build learning solutions that include space to play or explore the material, Scaffolded Social Learning spaces, simulations, or playgrounds, to try things out (rehearsal spaces: constructionist), and assess what we see.

All these approaches are valid: in my own work, i often start with reductionist thinking e.g. what makes a person fair, or humble, or effective? How does a particular thing ‘work’?

I also think about sequencing a great deal: what do you need to know first, before you can ‘understand’ the next thing. E.g. do you need to have empathy for different views before you can be an effective Social Leader? Do you need to know how to format a Word document well before you can be a great writer.

Reductionism drives us down this path, and Constructionism has a core appeal in that it is tidy: if you are trying to build complex capability, it’s convenient if the solution is tidy. Yet logic tells us that the systems we create may be of limited success:

  • Compliance led organisations are rarely fully compliant, no matter how much compliance training they do.
  • Organisations that focus on leadership development do not have uniformly excellent leadership.
  • Organisations that worry about, and invest in, innovation, are not uniformly innovative.

Many of the subjects we are concerned with in learning, at least beyond basic knowledge, are complex subjects, and in all truth we probably rely on emergence more than we care to believe.

Constructionism means that my mental models and modes of understanding may be different from yours. Hence my own reductionist approaches may give me a different sequence of understanding than yours. And your construction of ‘meaning’ may draw on a very broad range of different mental constructs than mine.

In summary, i’ll share words i often use within Organisations, which may be deeply unfair, but i hold to be largely true (and you can construct your own view): many of our most successful, effective, and good Organisations are successful largely despite, not because of, much of the development work that they do.

The excellence we seek is very often an emergent feature of broadly permissive systems, or sometimes emerges directly in opposition to overly oppressive ones.

Of course, emergentism is frequently a veil for our own failure to properly deconstruct, or reduce, the whole: magic is only magic until we have the tools (mental, diagnostic, visual) to understand it. We no longer have Gods of Thunder, outside the Marvel Cinematic Universe, because we understand electricity, plasma, and how sounds travels in waves.

An Example of Emergentism: Consciousness

Personally, i find the study of consciousness provides a useful test bed for how all of this fits together. Consider this sequence:

  • From the earliest times, we have been aware that our own consciousness differentiated us from other animals. We have sought to understand it’s roots.
  • Our earliest foundation myths were founded in belief: we were created by a divine entity, our consciousness and free will were gifts.
  • As time passed, we started to deconstruct the physical human body: the age of early science let to understanding how the physical system worked, although it took us quite a while to get that right!
  • We initially focussed on physical and visible structures: famously the Victorians were prone to phrenology, believing that the lumps and bumps on your skull represented different capabilities.
  • The primary early tools for understanding the brain lay in injury: if you poke a hole in this bit, what stops working? Early studies looked at e.g. a minor who had a pit prop blown through this head: still alive, but strangely different, what had changed?
  • This led into a dominant reductionist view: that we could ‘lodge’ specific behaviours, capability, and skills, in different parts of the brain. That was a convenient view, only slightly frustrated by the fact that Einstein had a depressingly ordinary brain, at least at first sight.
  • We started talking about ‘left and right brain’ behaviours.
  • Imaging technology allows us to take ever more detailed views of e.g. blood flow or electrical activity in the brain whilst it is actually working, as opposed to damaged, or deceased. We discover, for example, that taxi drivers in London actually change the physical structure of their brain whilst doing ‘The Knowledge’ (the three years of so of detailed and structured study to do what SatNav does).
  • Tools become more detailed, increasingly real time, until you can wear a skull cap at a conference and see your brain in real time.
  • Elon Musk builds Neuralink, promising to interface the brain direct to emergent AI’s…
    And AIs are built with increasingly complexity, even trying to mimic structures of human learning.
  • And yet we still do not know where consciousness sits. Perhaps we do not yet have high enough resolution in our tools, or perhaps it is an emergent feature of the whole system. Or perhaps it’s magic. We will revisit this when we consider Neuroscience in Learning, as one part of our Learning Science Discipline.

Philosophy and Learning Science

Why have we taken a detour into philosophy in a module about Learning Science?

Largely because the scientific method is a reductionist approach: it is a methodology, a toolset, to let us take apart the mystery, and diagnose the roots of complexity. And in that strength, lies the trap. Consider these points:

  • Neuroscience will let us see how the brain works, at a certain resolution: but it may not yet let us have comprehensive understanding.
  • Cognitive Psychology, or Behavioural approaches, may give us developmental sequences, broad overviews, but will they let us script and develop specific observed behaviours?
  • Anthropology may allow us to understand a historical sequence of cultures through artefact and ritual, but will it let us build a specific culture on demand?
  • Economics may allow us to understand how financial currencies work, but will it provide clarity on reputation based currencies, or the trading of trust?
  • Sociology may let us understand the flows and formation of social structures and tribes, but will it let us understand bias, discrimination, and harassment?
  • The answer to all of these, at one level, will be ‘yes’. It will give us AN understanding, but consider if it shows us the truth, or ‘a’ truth. And consider what you will do with this truth.

For me, the value lies in understanding the underlying philosophical approach, not specifically because it will let us succeed, but because it may be a timely reminder on the limitations of our understanding or action.

You as a Learning Scientist

We will revisit this question time and again: what does all of this mean for you as a Learning Scientist?

  • Consider your underlying philosophy of learning, and be cognisant of how this impacts your approach to learning design, both individually and organisationally.
  • Consider the scientific disciplines, and which ones you believe are relevant for Learning Science: curate your space.
  • Always reiterate your own ignorance: where does the magic still lie, which frontiers can be pushed back, and which are beyond our means.
  • Recognise that in a constructivist approach, we also construct the limitations of our own thinking.
  • Knowledge constrains us as well as liberating us.

About julianstodd

Author, Artist, Researcher, and Founder of Sea Salt Learning. My work explores the context of the Social Age and the intersection of formal and social systems.
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7 Responses to Learning Science: #WorkingOutLoud on Philosophical Approaches and Science

  1. Pingback: I am an Island | Julian Stodd's Learning Blog

  2. Lizzie Twelves says:

    Wow, what a truly beautiful and profound piece of writing on the might and powerlessness of humans. I’ve been exploring for some time what the real-world application of complexity really is, and I think we’ve come to the same conclusion – its a different lens and it calls us to use it alongside other more familiar ones to pause and explore the roads they take us down, which to choose and what, if anything, to do in response. Thank you, that was hugely serendipitous for me.

  3. Pingback: What I’m Thinking About: Domains of Knowledge | Julian Stodd's Learning Blog

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  6. Pingback: A Practical View of Learning Science | Julian Stodd's Learning Blog

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