Education is the Cuckoo in the Nest

Today, we have no learning programmes. We have no learning methods, no learning systems. There are no learning professionals.

Instead, we have education programmes, education methods. We have education systems and education professionals.

We have entirely forgotten learning and in its place we have become attached to an impostor – education. Education is the cuckoo in the nest. It grows, insatiable, pushing learning aside – starving it, smothering it.

Education is the astrology to learning’s astronomy. Today everybody wants to talk about astrology and has entirely forgotten that there was ever such a thing as astronomy.

And so it is almost impossible today for me to talk about learning, because to begin that conversation I would have to start by introducing some uncertainty in your mind about beliefs that you have held dear for a lifetime. I would have to introduce doubt – a doubt that perhaps what you believed learning to be is in fact not learning, but an impostor – education. When people talk today about ‘learning’ they are really only talking about ‘education’; they have nothing to say about learning.

Though I can express the answers to these questions simply, you may struggle to accept them  – so deep has our attachment to the educational waxwork become.

So what is this educational impostor, and what is the truth about learning?

The mirage is the idea that learning is knowledge transfer. This paradigm has led us to believe that human minds store information much as a book or computer stores information, and that it can be transferred from one person to another by being stated. So, for example, a person stands in front of a group and says ‘A lion is a dangerous animal’ and they store this information in their heads. And we imagine variations of this process (elearning, MOOCs, modules and micro-learning etc.) and we call it ‘learning’ – but really we should call it ‘content dumping’.

So what is learning, really?

Learning describes our ability to store our (emotional) reactions to experiences, and to adjust our behaviour based on those reactions. A person tells a story about being attacked by a lion, and the story moves us. Our emotional reactions are stored, and it affects how we behave. Furthermore we can use these reactions to conjure up a reconstruction of the experience.

This mechanism has been the essence of learning since learning first existed. It is an elaboration of a simple response – homeostasis. With homeostasis an organism tries to optimize its environment – for example heading away from environments that are too hot or cold. With learning, an organism encodes the reaction it had to different environments – representing them internally – and gains considerable survival advantage. It can say ‘when I stayed here before, I felt cold’.

In his book, ‘Affective Neuroscience’ Jaak Panksepp writes “efficient learning may be conceptually achieved through the generation of subjectively experienced neuroemotional states that provide simple internalized codes of biological value that correspond to major life priorities for the animal.”[1]

Human learning is quantitatively but not qualitatively different. We have emotional reactions to hot and cold, but also more complex things – clothing, smartphones and the sound of insects buzzing. Our reactions are initially hard-wired from birth, but our neurological plasticity gives us the ability to develop sophisticated and unique affective responses to all manner of things.

Probably as soon as I described learning as an emotional reaction, it made you feel uncomfortable. You have been led to believe that emotional reactions are unsophisticated and unsuitable for serious study.

We have grown so used to thinking of emotions as gross states – such as ‘happy’, ‘sad’ and so forth, that we struggle to comprehend the fundamental role they play in cognition. But consider, for a second, the sound of a bumblebee and that of a mosquito. I don’t doubt you have distinct emotional reactions – though you would find them impossible to articulate clearly.

In 1949 Donald Hebb made an important discovery. He discovered that as you experience the world your neurons – your brain cells – rewire themselves. More specifically ‘neurons that fire together, wire together’. You brain somehow reconfigures itself as you experience things, forming new connections to reflect the pattern of firing.

But what is it doing? What are these new connections? Is it storing the way things look, is it storing the way things sound – maybe it is storing the meaning of things (schema)? The verdict is now clear: it is not storing any of those things; our memories are far too unreliable.

Instead, it is storing how things make you feel. Your reactions. Your ‘neuroemotional states’. These affective responses are more subtle and malleable than you can imagine. You have different emotional reactions to different haircuts, different colours. Some people care about architecture, some care about football scores. You store these reactions and use them to conjure up a memory. You don’t store information or episodes, you store how those things make you feel. What matters to you – what you have an emotional reaction to you – determines what you see, what you remember.

And so there is and never was a distinction between thought and emotion. Plato set us on the wrong path. There are only emotions and more complicated emotions; a reaction you have that you call ‘chair’ and a subtly different reaction you call ‘18’. All your memories, all your thoughts, all your decisions are emotional reactions. You tell stories as a way of stringing these emotions together. Your words refer not to objects, but to what you feel about them. What makes you and I different is the things we care about – the things we react to. Fundamentally, we use the same cognitive process as sea slugs: (emotional) reaction.

Once more, as I write this I know many of you are experiencing an emotional reaction – most probably a rejection, a desire to argue and dispute. This is the reaction that creatures commonly have when their territory is invaded. Dogs bark. Humans have a sort of ‘intellectual territory’; as social creatures they become attached to shared beliefs & conventions and defend these vigorously when challenged. They feel an emotional reaction to their beliefs being challenged, and they form this reaction into sounds which they call ‘counter-argument’ and so forth.

When we listen to radio debates, typically two people who take opposing views argue the case. Almost never do they concede defeat. This would be odd if people really were rational creatures, if they were truly arguing – but instead they merely retrench their existing position. Hence, it is highly unlikely that you will change your position based on what I write here – however compelling my arguments – because fundamentally your positions are held emotionally, not rationally.

But let me return to learning and education: learning is not what you thought it was. When you learn, you store your emotional reactions to a story, a statement, an experience, an observation. You can use these stored reactions to reconstruct that experience, but it will always be a confabulation to some degree.

You might wonder how you can reconstruct all the detail that you do, just by using your emotional reactions. Our mind plays tricks on us. Try this:  draw a five-pound note (or ten dollar bill) from memory. Resist the temptation to look it up, or produce one. Just draw what you remember. Chances are, you will be shocked by how inaccurate your memory is. Try something else with which you are intimately familiar – such as, for example, the front of your house. There is a good chance that you won’t even get the number of windows correct.

In 2016 the company signs.com gave 156 Americans the challenge of drawing famous brand logos from memory – Starbucks for example[2]. Again, you can try it yourself if you like. The results reveal shocking verging on obscene levels of inaccuracy for many of the participants. Pretty much the only thing they consistently got right was the colour green and the presence of a woman.

Researchers including Elizabeth Loftus and Daniel Kahneman have begun cataloguing the ‘inaccuracies’ of the human mind. In essence, they have begun to describe how an affective cognitive system works, exposing cracks in our Platonic paradigm. We do not remember what we think we remember.

But I am not going to go over all that again. If you feel so strongly attached to the conventional view, then no amount of conflicting research will sway you. Instead I am going to talk about the implications for education – by which I mean, what education would look like if we actually understood learning:

The first thing to note is that whilst humans begin life with very similar sets of concerns – things they care about – these will quickly begin to diverge depending on experience. So whilst sexual stimuli are a pretty good bet for an advertising campaign, if you really want to reach me it is better to know that I am more interested in robot hoovers than Kardashians.

Two people on a train journey will remember different things: one may recall the delightful progression of architectural styles, another the flora & fauna. Two students sitting in a class will remember different things depending on what they care about.

So the first principle must be this: new concerns build on existing concerns. If we wish to change what a person cares about, in order that they will react to things they didn’t before (i.e. to learn), then we will need to know what they care about today and use that as a starting point. By the time people enter the educational system, their concerns will already have diverged considerably, and we must take the time to understand precisely how.

For example, as student who doesn’t care about mathematics will have little reaction to a mathematics lecture, and likely describe it as ‘boring’. They will learn next to nothing.

But if we know that they are interested in becoming an entrepreneur, and we can tell stories that place mathematical principles in an affectively significant context, then we can expect the student to remember.

In normal life this process is called ‘conversation’. We take time to understand what another person cares about, then we tell stories that relate to their concerns. An interaction where someone just talks about the things they care about is called a ‘lecture’ and these people are described as a ‘bore’ (or a ‘lecturer’).

Once again: an educational process is one in which we shape the concerns of an individual, typically with a view to aligning their individual concerns with activities that are acceptable or valued by society. A person who delights in cutting the heads of insects may go on to be a surgeon, for example.

We can only construct an effective, affective education system by accurately mapping the things that people care about at the start of the process, then using this as a key on which to build new patterns of concern. This is how digital marketing strategies succeed in selling you stuff – they refine their understanding of what you care about, in order to increase the chance you will acquire products.

What students are concerned about is important, since it determines what they react to – which in turn decides how experiences are encoded. So we should never have a ‘curriculum’, nor ‘topics’ instead (and much as Piaget described) people should be allowed to explore challenges and types of activity to which they respond[3].

In a well-formed educational system, a child who is interested in, say, tackling famine in Africa might draw in information from a range of areas – language, history, economics, agriculture, geography, design and so on – but only in service of the overriding concern. To just spray people with information cannot be a good approach. Obviously, good teachers make an effort to bring these subjects to life for people – but today’s model is inherently topsy-turvy.

The second principle is this: an educational process will correctly employ ‘push’ or ‘pull’ techniques to shape learning. Since an individual’s concerns govern their encoding of experience there are two distinct classes: firstly, those where an individual is already concerned about something (the ‘pull’ condition). In this case, they will have a strong reaction to related experiences. For example, someone who works in learning and cares deeply about learning will find a paper on learning theory memorable and moving, whilst someone else may find it boring and forgettable. This ‘pull’ condition is typical when we are Googling information. Typically we Google things that we care about – our search is a response to some pressing concern. This is why it matters very little that the response is simply text. We never Google an elearning module for example.

In a corporate context, this principle accounts for the significance of user-centred design and the ‘resources not courses’ approach. Generally the most effective way to drive learning and performance improvement will be to take time to find out what concerns people have, and develop simple resources to help address them. For example if a leader is concerned about levels of engagement within their team, a simple resource titled ’15 Ways to Boost Team Engagement’ will likely be welcomed.

In the second condition – ‘push’ we must create new concerns by building on the existing ones, so that learning can take place. It is worth pointing out that we are not trying to ‘force knowledge into a person’s head’ (which is the conventional educational paradigm) but instead creating the sets of concerns that will cause them to encode experience. People are resourceful learners when sufficiently concerned – everyone is capable of ‘self-directed’ learning (note that ‘concerns’ and ‘motivations’ are not at all the same – if you were to suffer a nosebleed I would likely remember it, though it would be odd to describe that as a ‘motivation’).

Here we may use the time-honoured techniques; play, storytelling, observation, and practical experience to shape what people care about. Each of these techniques is effective because – and only because – of their affective dimension. ‘Learning by doing’ is effective because the consequences of our actions impact us emotionally, storytelling because it carries the emotional significance, observation because we mirror the emotions of those we observe and so on. Play is a condition where we deliberately attenuate the emotional consequences in order to promote learning – you may feel upset that you have crashed the flight simulator, but nobody has died.

It is sometimes said that we learn best from mistakes – but this is not strictly true: we learn from mistakes whose consequences we feel (many mistakes go unnoticed after all).

We should not test people on what they know, but instead what they can do. The human mind is not designed to memorise facts (for reasons outlined above). Getting young people to do this involves abusing cognitive systems quite horribly – for example using rote learning or threatening people with beatings or tests. This barbaric ‘educational’ activity will more often than not dramatically reduce the appetite for learning, rendering people inflexible as adults and fearful of learning contexts. For example, when employees are told that they must undertake some learning their first question is most commonly ‘will there be a test?’.

We must take the time to understand what matters to people, and allow them to explore challenges of increasing complexity, in order that their concerns may develop and diverge in ways which ensure that their life will be experienced as purposeful - as doing something that matters.

The Future of Learning:

It should come as no surprise that since people have the wrong idea about learning, they have the wrong idea about the future of learning: ‘we will all need to learn more in future!’ they say – but it is already clear that the future is set on a course of learning elimination.

The most significant advancement in learning that one can imagine is for future education systems to support rather than suppress learning. That this would be a revolution, is an understatement. But it may already be too late for such a revolution to take place: all around us learning is already being eliminated. Take, for example, the role of the London Taxi driver who, until recently, was required to memorise every street in London (a process typically taking several years) before being certified to drive a cab. Then came GPS – a system that externalized that knowledge, allowing almost anyone capable of driving a vehicle to be a taxi driver. Soon we will not even need to learn how to drive a car. Fewer people know how to cook with each passing year.

That people have not spotted the inevitability or pervasiveness of this trend is due to their fundamental misunderstanding of learning. Learning – as a homeostatic mechanism – seeks to optimize our environment. With technology we have unprecedented ability to transform our environment: we no longer have to grow our own food – first came the supermarket, then home delivery, and now with AI assistants in our homes we have only to speak the name of the food we want and it appears. Instantaneous machine translation will soon remove the need to learn another language. Quite soon we will have no need to learn to read or write. This is not a ‘side effect’ of technology: this is precisely the essence of technological progress – to eliminate learning. This is why a 3-yr old can use an iPad, but not a personal computer from the year 2000.

Our reckless optimists believe that somehow learning is an essential part of the human spirit – forgetting that even Piaget understood that learning takes place principally to achieve equilibrium. The more we externalize learning – the more we create technology that removes the need for learning, the less we will learn. It may be that learning persists only in the form of a leisure pursuit; time will tell.

It should be stated clearly that learning itself does not change. It has not changed for millennia, and will not change for millennia to come – but the environment in which we learn is changing dramatically. Many of us will have lived thorough an era where we could observe people or hear stories from the other side of the world – through television. And whilst the nature of storytelling or observational learning remain unchanged, our exposure to behaviours and stories has grown exponentially. So perhaps it is worth considering some of the interactions between unchanging human learning and ever-changing technology that we are likely to witness in our lifetimes.

In the immediate future, there are some interesting applications of technology aligned to the ‘push’ and ‘pull’ approaches outlined above. Let me first describe  ‘pull’ applications:

When I travel across London, I frequently make use of the London Underground Map – indeed I have done so for many years. This map is a useful resource, removing my need to memorise the entirety of the network. But even better than a map would be guidance, and all that is needed to transition from resource to guidance is contextual information – for example the GPS in your car stores road maps, but also needs information about your current location and destination to offer guidance.

Performance guidance is the future for organisational performance. With performance guidance anyone, of almost any level of capability, can perform any task expertly. Currently many of us use GPS, but employees in future will use technologies such as Amazon’s Alexa or Apple’s Siri to guide their activity. Imagine GPS for everything that you do. For manual tasks the integration of Virtual and augmented reality (such as Microsoft’s Hololens) will enable people to be procedurally guided where a task is not suitable for automation. The benefits for businesses are considerable – a massive reduction in wage costs due to the reduced need for skilled labour, and the near-elimination of learning curves – enabling them to cope with ever-shorter employee tenures coupled with an increase in market volatility and organisational change.

Some of you may have spotted that this trend has more to do with removing the need for human capability rather than building it. So what, if anything will technology offer to enhance learning?

Here, virtual reality and augmented reality are very promising. Many people struggle to understand what it is that makes these technologies significantly better than video. The answer is their affective dimension. When one watches someone doing something on video the affective impact is reduced by virtue of being merely observation. With virtual and augmented reality the mind is tricked into feeling that you are ‘really there’. If we use the flight simulator as an analogy; VR and AR enable us to build a flight simulator for anything – to enable people to practice activities and learn by doing – to play in a space where we are not dependent on imagination alone for affective significance.

Returning to the topic of education (whether state-funded or corporate education) there is tremendous potential for us to realize a virtual, digital, exploratory environment – one in which learners can explore and develop their concerns through direct experience of any challenge we can imagine – from preserving the rainforest to conducting brain surgery.

However, in case it is not obvious, the two approaches outlined above stand in opposition to one another – and it is now fair to say that there is a race, if not a war, between the two. Why develop an education system in which people can develop their capability through challenges and hands-on experience, if our plan is to eliminate the need for this level of capability? It is hard not to envisage a future where only the elite are highly-paid, and where pay-to-learn digital learning opportunities may be open to all – but only the very best can out-compete the machines. This ‘long tail’ marketplace is increasingly commonplace in industries such as music and books.

I wish I had better tidings; but I have always preferred an unpopular truth to a popular impostor.

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[1] Panksepp, J. (1998) Affective Neuroscience: The Foundations of Human and Animal Emotions, p. 55, Oxford University Press.

[2] Branded in memory; 1500 drawings reveal our ability to remember famous logos. https://www.signs.com/branded-in-memory/ (Last Accessed 30/09/2018)

[3] As an aside, Piaget was on the right tracks in describing assimilation and accommodation, underpinned by schemas. His mistake was to assume that these schemas were semantic, rather than affective. It is hard to imagine mice having semantic schemas, after all.

Image: Marianna Mercado