My Father

My father died yesterday. A peaceful end to a long and eventful journey. I am overwhelmingly sad, tempered by a gratitude for what he gave us, and how we were able to be together at the end. Writing about it is the only way i know to make sense of the story: sometimes you just have to write, no matter how hard it is.

Of course, i feel a certain pressure to write something good: i can sense the look he would give me if i resorted to sloppy eulogy or, worse, poor grammar.

To know my father is probably to know me: i have been fortunate to inherit some of his better qualities, and a fair few of his worse or more annoying ones.

When i say ‘better’ qualities, i mean those things he did as I was growing up that drove me to distraction: questioning, probing, and generally embarrassing me in front of my friends by demanding clarity and detail. In other words, the questions i ask myself now, the questions that make my own work occasionally strong, are the questions he instilled into me.

Not, i should say, through any formal teaching: i am for the life of me at a loss to think of a single time when my father taught me how to do anything well. His approach to parenting appears to have been to give me enough space to learn, and enough safety to trip up as I did so. Whichever direction we turned, our parents just gave us an open door (and often a taxi service to get us through it).

Of course, in the other column (and possibly an explanation for why they gave so much space) is that i am as stubborn as my father was. And as annoyingly opinionated at times. Although doubtless we would both claim that by ‘opinionated’, what you really mean is that we stick carefully to a well thought out position.

My father was a man of strong faith, as well as an accomplished academic, and i remember once having a lengthy conversation about the Anglican church’s view of homosexuality. The next time i visited, i saw that he had been reading a book about it. That’s another habit i have picked up from him: to be curious and i hope rigorous, and open to change. I feel sure you can find plenty of times when both of us were wrong, but few times when we were unwilling to change position if the argument was good.

Growing up, all of our shopping lists were written out on strange little rectangular cards: i did not know it at the time, but these things (boxes of which remained with us for decades, and still occasionally turn up as the bookmark in an old book) were punch cards for the giant mainframe computer in the basement of City Hall, that he had learned to programme and used for statistical analysis of his PhD, and then later to support other research.

I’m still unclear how father surfed his way into sitting at the heart of IT in his academic institution, but i suspect by seeing the mountain of the future and then climbing it. Because his first and, i suspect, enduring, love was of the outdoors.

Our standard family joke when growing up was to go on a long drive somewhere, only to hear father proclaim “i’ve canoed there!”

Before he was a father, and before he was an academic, he was an Outward Bound instructor, and his tales of camping, hiking, sailing, and kayaking, were doubtless what inspired me to find my own love of the outdoors. I only told him recently, but on all of my biggest adventures and expeditions, i carried the compass that he gave me.

When i hiked coast to coast at age 30, a fairly epic adventure that saw my friend Paul and i covering twenty five miles a day for two weeks solid, we got to the distant shore, waded in to the sea, then made for the nearest payphone. Back in the days when you had to carry coins, i had several five pence pieces ready for occasion, and i remember clearly when, over the crackling line, he told me that he was proud of me.

I grew up thinking that my father was an ‘old father’, as he had been slightly older than the parents of some of my classmates. So it was with considerable surprise that i realise i was a full twelve years older than he had been when i became a father myself. And more surprising still when i realised how totally unprepared i was. Not in the practical details, but in terms of the responsibility to create those open spaces, to instil those values, and to be the person who says that they are proud, not just of the big things, but the little things too.

As i try to find my own role, i will try to carry forward those things he taught me, not by teaching, but by being.

I suspect that my father was sometimes surprised by how different we were, but if he looked closely, i am sure would see what i guess i will see in my own son: that we are born in the shadow of our parents, but find our own light, that we are an accumulation of the things we are given by our parents, and the space we have to grow beyond them. We are all different, and yet recognisably the same.

As our own son reaches four months old, i feel acutely the responsibility to stand over him, to protect him. At this age, it is visceral: i ache when i am not with him, or able to comfort him. But the lesson i hope i can carry forward is that this responsibility changes and evolves over time. Perhaps at first we have to hold our children safely, but then later we just have to stand aside and let them find their own path. But what would i know: i am at the start of this journey.

I will be forever grateful that my father was able to meet, to hold, and to smile with, my son: whilst i feel loss, and great sadness, i also feel that this is the journey that we make.

And perhaps also something more: i think that i had always looked at the end of life with a fear of it’s finality. Certainly, i had rehearsed the first words of this piece in my head, time after time, as we felt the end draw near, with sadness. But i realise, with some surprise, that this is the last gift that my father has given me. The knowledge that a long life, lived humbly, and lived well, a life dedicated to family, to community, and to the search for knowledge and meaning, is a life well lived. And that, if we live that life, there is little to be afraid of at the end.

For now, i just want to focus my time on our family, to be together. But as we move forward, i still have my compass. Not that one that sits in my desk drawer, but the one who lives on in my heart and my head.

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What Different Disciplines Can Contribute To Our Learning Science: a #WorkingOutLoud post

This is a #WorkingOutLoud post, sharing a section of the work i’m doing on the ‘Learning Science’ module of the ‘Modern Learning Capability Programme’. In this section, i will share an overview of different scientific disciplines which may form part of ‘Learning Science’, and consider what, and how, they contribute. This is very early stage work, so very full of holes, but i hope you can see the emerging structure.

As we curate our personal discipline of Learning Science, we can consider the different buckets that things sit within.

Some fields of science explore the individual: how we work, how our brains and bodies develop, and the different ways we learn to operate at each stage. Also the ‘software’, exploring consciousness, and everything it means to be a functioning, conscious being.

Some fields explore the physical context of learning: environmental factors, as well as broader cognitive aspects of culture.

Some fields explore the social context: communities, teams, interpersonal dynamics, networks etc.

The Personal Bucket: How We Individually Learn

This may include:

  • Structural understanding of learning: neuroscience, physiology, anatomy, etc which let us understand memory, retrieval, reinforcement, practice, building manual dexterity and fine motor skills, physical prowess, refined skills etc. Also let’s us consider different modalities e.g. video, audio. Let’s us understand building blocks such as repetition, manipulation, practice, as well as differing ability and loss of function.
  • Emergent understanding of learning: consciousness and ideas, intelligence, bias, thinking, creativity, imagination, storytelling etc. Essentially anything that cannot be directly observed, but must be articulated or experienced. Let’s us understand belief, discrimination, motivation, engagement etc

The Context Bucket: The Environment We Learn Within

This may include:

  • Environmental factors: heat, cold, noise, distraction, etc, may help us to understand or plan for utilisation, rehearsal, experience etc
  • Cognitive or Cultural factors: complexity, risk, consequence, opportunity reward, will help us to understand engagement, confusion, adoption, adaptation, subversion, spread and amplification etc

The Community Bucket: The People We Learn With

This may include:

  • Sociological factors: trust, pride, respect, empathy, recognition etc, helps us to understand conformity, control and structures of power, consequence etc
  • Linguistic factors: language, jargon, dialect etc let’s us understand tribes, teams, conformity, efficiency, identity etc
  • Cultural factors: difference, exclusion, permission, curiosity etc which let us understand framing and perception, wilful blindness, change etc

Let’s take a tour through some of the relevant scientific disciplines, and consider what each can contribute to our overall approach.

Structural Sciences: Looking at the Brain and the biological basis of learning

When relating to learning, these sciences are typically described under the broad discipline of Neuroscience, although they can relate to the broader functioning of living organisms too.


A branch of biology that looks at the normal functioning of the human body, and it’s constituent parts.

Why is this of interest to Learning Science?

Our physiology is our spaceship: the vehicle in which our minds navigate the universe. So it gives us both capability and constraint. There are a range of areas or key learning which may be relevant. For example:

  • How strong or dextrous you are will impact your ability to use tools. Tool use and manipulation of objects has a feedback loop to learning.
  • The size, and structure, of various organs (like the brain, stomach, muscles) will impact on their efficiency or capability, which can all impact on physical disciplines, from endurance to cognition (the brain needs energy and security).
  • People get seasick in VR environments because of the way their peripheral vision is processed: understanding this will help us to create useable learning environments.
  • There may be a correlation between movement, and empathy: this will impact effectiveness of learning design, especially between e.g. passive experiences, such as eLearning, or video, interactive ones (scenario based) or VR ones (experience based with movement).
  • Height and success are correlated: and if taller people are more confident and successful, then VR allow us to engage in a ‘body’ that is taller.

Myths of physiology:

Persistent myths include: male vs female structural differences and impacts on ability, which persist in dominant cultural narratives

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I am an Island

We share a different story in every direction that we face: we make parts of our journey alone. On our island, we can tend to the land, we can build a house. We can shape the landscape, and look out across the sea. Past the breakers and the reef, we see the other islands: we voyage out, making connections, trading, sharing ideas. We come together to celebrate and reminisce, then return to our island. I am an island, but i am not alone.

My writing this week has explored ways that we understand the world, something i first explored in a book a few years ago about ‘learning, knowledge, and meaning’. Revisiting this area reminded me of how our worldview, our perceptions, our beliefs, are so essentially islands: we can visit, we can see others, but ultimately, our understanding of the world sits as one.

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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.
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Learning Science: a #WorkingOutLoud post

I started work today on the full Modern Learning Capability Programme, with the module on Learning Science. As part of #WorkingOutLoud, i am sharing this work here, although please note that this is still early stage, so not perfect. Specifically, this piece stands at the start, and tries to deconstruct the notion of ‘learning science’ into a view of the varied specific scientific subjects that may contribute to this discipline. It also starts to address what a real science is, and how we find rigour, not hype.


In this module, on Learning Science, i will try to help you set your own foundations for study and understanding. We will deconstruct the term ‘learning science’, to understand the separate disciplines that it draws upon. We will also consider what we mean by ‘science’ and the ways that it may give us strength in our work, as well as ways that that strength may be lacking.

Inevitably, to understand science and the scientific approach, we have to delve into some theory, but our outputs will be practical: finding your own platform for learning and understanding, and giving you the framework through which to judge the things you read and see in the name of ‘learning science’.
What is Learning Science?

Science represents a systematic approach to building knowledge: it is the study of the world through observation and experiment. It is not specifically a book of outcomes, but rather the methodology by which we come to those conclusions: science can provide us with an answer, but typically provides us with further questions too. Science is the journey as much as it is the destination.

When we talk about ‘Learning Science’, we are considering that there is a systematically organised body of knowledge related to the ways that we learn. In common with any scientifically derived knowledge, we assume that there is an evidence base behind it, and both active, and ongoing, work to expand it. Science is never ‘done’.

Science is both an intellectual activity, and a practical one: you can ‘think’ about things, or do them, both under the heading of science. An experiment is exactly that.

Whilst in popular discussion, we talk about ‘good’ and ‘bad’ science, it is not specifically the methodology that is valued judged, but rather the shape of the experiment, or the interpretation of the results. Good scientists can do bad science, because science is typically ‘confounded’.

Imagine you stand on a hill, looking across a valley, in search of the sea (representing the quest for knowledge as a landscape may be a tired metaphor, but i hope will illustrate a point): your view may be clear for thirty or forty miles. You may see mountains to the north, and the sea to the south. Or it may be hazy, your view occluded by the morning mist in the valleys, or by nearby trees, or tall buildings. It may be cloudy, rainy, or simply the landscape may be lost in the dark of night. Or, of course, you may be looking in the wrong direction entirely.

Much of the history of science, in whatever discipline, represents the blind wandering in this landscape: sometimes finding an interesting destination, often lost, sometimes in danger of thinking we are found.

How we know things

Consider this section a foundation piece: it explores how we know things, and sets the context for learning science.

Perhaps surprisingly, we are not entirely sure how we know things at all: the philosophical exploration of this is known as epistemology, and it presents us with a number of perspectives. For our purposes though, i want to consider just two elements: some types of knowledge are derived from ‘what comes before’, and some are founded upon experience and empirical evidence.

These two types of knowledge are called ‘a priori’, and ‘a posteriori’: a priori represents what comes before, and a posteriori represents what we learn (through science and experience).

Maths is a typical example of a priori knowledge: the reasoning that 2+2=4 is independent of personal experience. The field has grown through deduction and pure reason. Consider this ‘theoretical’.

By contrast, a field such as biology, or astronomy, which has grown through experiment and observation, hypothesis and conclusion, is a posteriori. Note that it is within this space, a posteriori, that empiricism sits.

Within this frame of understanding, perhaps most of what we consider to be ‘Learning Science’ will be a form of a posteriori knowledge.

In my understanding, this is important, because it speaks to how we will learn more about learning: not through pure reason and induction alone, but rather through experimentation and experience. Learning is a very human science.

Types of science

Consider this section as setting up the different ‘boxes’ we will explore further. So it sets more context, but also introduces some specialist topics that we need to explore.

Considering ‘Learning Science’, our focus will be on the empirical sciences, which can typically be split into three areas:

  • The Physical science – chemistry, astronomy, metallurgy, etc which concern the science of the material world.
  • The Biological Sciences – zoology, genetics, palaeontology, molecular biology, physiology etc, which concern living things.
  • The Psychological Sciences (sometimes called ‘Social Sciences’, or even ‘soft sciences’) – psychology, sociology, anthropology etc. Sometimes economics is included in this, although there is debate as to whether it is a science at all.

You should note that there are about as many different taxonomies of science as there are people writing about the taxonomy of science, but this gives a flavour.

A related description is worth noting too, which considers the cognitive nature of these in approach: the physical sciences can be described as building remote types of knowledge, whilst both biological and psychological sciences are said to build an intimate type.

Types of Science relevant to learning

Here, we consider which types of science are relevant to ‘learning’, and deconstruct the idea that ‘learning science’ is a separate discipline in it’s own right.

When we consider ‘Learning’, we may not actually mean one field of science in it’s entirety, but rather a programme that draws upon a number of different fields of science and, hence, different approaches.

To explore modern learning science, we should start by looking in some of the following areas, starting with the psychological sciences:

  • Psychology – which is the science of behaviour and the mind. This is a very broad discipline that we shall delve into much further. We may draw upon psychology in a wide number of ways, for example, to understand how we think about things and construct our understanding of the world, how bias is held, personality structure, concentration and engagement, resilience, relationships, even communication and motivation (and many more!).
  • Sociology – the science of social relationships and interaction. Culture sits within this space as a study of the individuals and collective behaviours.
  • Anthropology – the scientific study of humans, human behaviour, and society. A lot of work on cultural meaning sits here, in particular how ‘norms’ are established.
  • Linguistics – the study of language is relevant to understand meaning, and the ways that we share it (e.g. learning). For example, many of the social forces such as ‘trust’, ‘pride’, ‘respect’, ‘empathy’, etc, have underlying cultural contexts which can vary by region.
  • Economics – my own work is increasingly influenced by aspects of economic theory: it’s a field of science that explores the production, distribution, and consumption of goods (including knowledge goods, hence learning).

We could also have included some more distant social sciences that bring a perspective to learning (and i will try to indicate why they are relevant):

  • History – can be considered a social science, and it relevant in the context of learning in global organisations, where we discuss cultural differences, social norms of groups (e.g. views on how people in different regions learn), motivation and drivers etc.
  • Political Science – which may provide a lens for considering the flows of power, and social forces of difference, as well as a lens through which to understand change.

Alongside these social sciences, there are aspects of the biological sciences that may concern us (and again i will try to indicate why):

  • Neuroscience – the structural scientific study of the nervous systems, and our earliest attempts to understand how it works.
  • Anatomy – any exploration of movement in learning, as well as understanding virtual reality, may involve understanding of anatomy.
  • Ethology – a study of animal behaviour, which includes all sorts of work on stimulus and response, hence reward mechanisms.

Beyond this, if we were being technical, we could even consider the sciences that drive specific learning technologies: artificial intelligence, machine learning, headsets and handsets, but here we are focussed more specifically on learning design and behaviour (and will explore some of these other areas in other modules).

Before we disappear down the rabbit hold of the taxonomy of sciences any further, i would encourage you to try to draw out two key themes:

  • Firstly, what will you include in your own ‘Learning Science’: if you include neuroscience, but neglect cognitive science, where will that leave you?
  • Secondly, what will you leave out: to understand science, we have to understand that failure often comes from our own blindness to confounding, or contributing, factors. So being deliberate about what we are NOT studying can be as important as considering what we are.

Empirical Knowledge

When we make a hypothesis, we are making a (hopefully informed) statement about how the world is. We then carry out research, and shape an experiment, to verify, or repudiate, that claim. In that context, ‘empirical’ evidence is what we see that either validates a truth (what we hypothesised), or falsifies it.

Primary evidence is that we we directly observe, and publish. Secondary evidence is an exploration of that which has been published, and analysed, by others.

There are some key aspects of this which are important to consider:

  • When we formulate a hypothesis, we are making a statement, based upon our current understanding, of how something is. BUT we are not stating a truth just yet.
  • We test that hypothesis, and the validity of our science lies in how we carry out that test. One way to consider this is to think about an annual service that you carry out on your car: it tests and verifies a number of factors that are important to safety and longevity (oil levels, filters, emissions etc). But the test is only valid (as a measure of safety) if, for example, it checks the wear on the tyres. A badly designed experiment would fail to do this.
  • We interpret the evidence that we have gathered, and on the back of the hypothesis, and experimentation, we draw out the meaning, and make our conclusions.
  • We submit these to peer review, and publish them. Peer review, the value free critique by our peers, is the foundation of quality here: they ensure we have designed our study well.

Where ‘Learning Science’ fails

As should be clear, there are hence a number of ways that we can fail, not least of which:

  • We may formulate a hypothesis that fails to account for an entire field of existing knowledge.
  • We may design a poor experiment, or there may be a fundamental inductive flaw in our reasoning for the outcomes we observe. For example, i may decide that engagement in compliance training is a feature of reward, but if i have not tested that assumption, it is simply supposition.
  • We may introduce personal knowledge bias, or even Organisational political bias, into our interpretation.
  • Without peer review, we lack the external moderation of our efforts.
  • Without publication, we fail to contribute to the broader discipline, and also lack opportunities for feedback.
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Illustrating Apollo #3

This rather strange looking machine is the Lunar Landing Research Vehicle: it was used by the Apollo Crews to practice final approach to the moon. It had a set of jets that were permanently lit, which supported 80% of it’s weight, meaning that they could use the positioning thrusters to move the rest of the ‘weight’, and it would feel something like the lander would behave in the low gravity of the moon.

Or at least that was the theory: as with much of the simulation for Apollo, nobody really know. They didn’t even know for sure that the surface of the moon would support the weight of the lander: maybe it was like a soft powder into which the astronauts would sink without trace.

This is one of the final illustrations for the ‘Leadership Reflections from Apollo’ book. I still have some small pieces to illustrate, and the conclusion to write, as well as some general proofing and editing, but it is well on the way.

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Making Up Stories

At three months, i’m able to have a conversation with my son: truthfully, not a very purposeful one, but certainly enjoyable. So far we have steered clear of Brexit and religion, focussing instead on the adventures of a small, but disproportionately kind, elephant, and a penguin who wishes she was an astronaut (spoiler alert: she makes it in the end).

A Sad Bear

Our relationship has reached new heights: he reliably recognises me as a human being, and is seemingly very content to squeak or squeal at me at key moments of the story. This has been a positive developmental stage: communication is now a thing, it runs two ways, and we both seem very happy about it. Writ large on his little face is a real joy in connections: indeed, he is so enamoured of them that he seeks them everywhere, smiling on demand at any other human, humanoid, or elephant, that smiles in his direction.

Interestingly, he has also worked out that he can use his proto-language to express things other than happiness: sometimes, instead of crying, he will try to articulate his misery with a ‘word’.

Ok, well if you insist, here is the story about the elephant.

One day, Elephant found his friend staring up at the sky, looking sad.

‘Why are you so sad?’, asked Elephant.

‘Because the sun has gone away’, said the Bear. ‘It’s dark and gloomy, and i cannot read my book’.

Elephant looked up at the sky: it was indeed dark. The sun had set, and the moon not yet risen.

‘How does it feel to be sad?’, asked Elephant.

‘It feels cold, and blue in my tummy’, said the Bear.

Elephant thought about his own tummy: it currently held several pieces of liquorice that he had found under the table, and a nice cup of tea. It felt warm and orange.

But Elephant suddenly realised that he felt sad too. Because his friend was sad.

‘I’ll tell you what’, said Elephant, ‘let me put my trunk around you, and we can sit here together until the moon comes up, then we can go and find find come cocoa together’.

So he sat, and put his trunk around Bear, and they both sat there together, staring up at the sky, until the moon came up. Then they went and drank cocoa.

‘Mmm’ said Bear. ‘I feel warm and orange in my tummy’. And Elephant felt warm and orange too.

The end.

I hope that those squeals you are making are happy ones.

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