Teach like a chimp! The validity-transportability paradox in teaching

validity-transportability-paradoxA paradox of attempting to apply ideas from research into the real world is that the simplified environments of scientific experiments allow for the formation of extremely complex explanations, whilst the application of those ideas into the more complicated real world often require that they are somewhat simplified. The ideal conditions required for creating validity, and those required for creating transportability (the easy transmission of an idea into the real world, to borrow a phrase from Jack Schneider’s 2014 book ‘From the ivory tower to the school house’), are almost completely opposing. This clearly creates a dilemma: how much erosion of validity do we accept in order to allow a theory to become transportable?

‘The Chimp Paradox’… Paradox

Until recently I was something of a validity purist on this matter. I remember a seminar I attended last year with Vincent Walsh, a neuroscientist at UCL who studies sporting performance and decision-making under pressure and works with various GB sports teams. At one point, mention was made of Steve Peters, the psychiatrist who has also made a name working with some of the biggest names in UK sport such as Chris Hoy, Victoria Pendleton, Steven Gerrard and Ronnie O’Sullivan, as well as a lucrative consultancy side-arm with hundreds of companies. Peters’ work, detailed in his book ‘The Chimp Paradox’ involves dividing the mind into two competing parts; a primitive “Chimp” brain (the limbic area), which deals with emotions, and a more rational “Human” brain (the frontal cortex). In Peters’ formulation the chimp brain works 5 times faster than the human brain. In some of his work with sportspeople a third region is introduced: the “Computer” brain, which is even faster (20 times as fast as the human and 4 times faster than the chimp!)

Peters’ clients are taught to recognise their mental states and to govern nerves, pressures and insecurities according to these three brain labels. Now, from a purely neuroscientific perspective, Peters’ ideas are at best a severe oversimplification, and at worst outright inaccurate. I won’t spend time here covering the reasons for this (though this page is a decent introduction to the difficulties of dividing the brain into regions according to their ‘development’). However (and this was the point made to me when I voiced these concerns), when you have Chris Hoy crediting Peters with his gold medals, you can’t really argue with his results. Sometimes an idea can be a ‘useful simplification’ (or even a ‘useful fiction’, depending on how stringent your criteria are), containing enough accurate information to help people whilst remaining widely transportable. The success of ‘The Chimp Paradox’, then, is precisely because the complicated science behind Peters’ claims have been simplified enough to have broad accessibility and appeal to people’s everyday lives – ‘The Chimp Paradox’ Paradox, if you will.

Validity vs transportability in teaching

Whilst I’m sure this observation is far from new, it has struck an interesting chord with me recently in thinking about applications of research to teaching. I was reminded of it last week when I inevitably stumbled across yet another ‘Edu-Twitter’ debate about the chosen methods of a particular North-West London school. I know I shouldn’t, but, like a fire in a carpet warehouse, it’s hard not to slow down and watch the carnage unfold. This particular debate centred on the school’s use of certain principles of cognitive psychology (notably interleaving and spacing) as a justification for some of their methods. Some comments on the thread accused the school of oversimplifying complex theories (and implied that this therefore made them worthless). I might previously have agreed with this position, but as we have seen it is clear that some simplified scientific ideas, properly packaged, can be enormously useful to some people. If we are to embed evidence-based practice in school, then the first step is surely to embrace it in any form initially, and work out the finer details from there.

The difficulty is that there are no clear indicators as to where to draw the line between validity and transportability. Indeed, the ‘Goldilocks zone’ may be different for each idea anyway, depending, for example, on the transportability of the original idea and the extent to which it can be simplified whilst still retaining a coherent message. The downside of this process is that more complex theories (which may well resist simplification for very good reasons) will lack transportability, limiting the extent to which they are able to be widely adopted. As an example from another Twitter feed last week:
screen-shot-2017-01-30-at-16-11-17

Whilst the post was widely appreciated in certain circles, I was struck by how Cognitive Load Theory, an idea that is so central to much educational scholarship (and which is potentially an extremely helpful concept for educators) has, in my experience at least, never really caught on in classrooms. I would argue that this might be because its rather nuanced division of cognitive load into three different types is not the sort of thing that is easily transported in 140 characters or casual break-time conversation. The validity/transportability balance for CLT is an interesting story in itself; this essay from Michael Pershan charts Sweller’s attempts to balance the complexity and validity of his theory with its transportability. It is hard to see how CLT could be further simplified without losing its essential essence, but equally in its current form I’m not convinced it’s that transportable.

Teach Like a Chimp

teach-like-a-champion
With apologies to Doug Lemov…

So what are the ‘useful simplifications’ in teaching? Which academic ideas can be easily simplified into transportable forms without losing their validity? I might suggest the following:

– Applied memory strategies (e.g. spacing, interleaving, testing etc)
– Elaboration (linking to previous knowledge)
– Encouraging metacognition
I would previously have suggested feedback, but following the EEF review into marking it’s clear that this issue is rather more complicated (or less well researched) than we might imagine.

What other ideas would people suggest?

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Teach like a chimp! The validity-transportability paradox in teaching

The ‘transfer’ problem is not a surprise. It’s central to how the brain operates

One of my favourite storylines in series 4 of The Wire followed the initially calamitous attempts of Prez, the recently disgraced cop turned high-school teacher, to get his maths classes learning anything (it’s tragic that in a drama about drug gangs I still find the bits set in a school the most interesting, but I can’t help myself). Prez’s breakthrough comes when he realises that the probability theories his students are failing to absorb in class are the same ones required for success in the sidewalk dice games that they often play after hours. He begins to present the problems in the context of the dice games, and sees their understanding take a leap forward. The implication (though from memory it is never explicitly stated in the series) is that once the students have executed the strategies in this relevant real-world context, they will also be able to demonstrate that understanding back on the paper and textbook tasks on which they were originally so stuck. This storyline is a great dramatisation of the problem of transfer, the ability to apply knowledge learned in one context into another.

As David Didau pointed out in an excellent recent blog post, transfer is pretty much the point of education itself. Despite this, learning can often remain defiantly, and surprisingly, context-specific. Didau recounts a number of studies which clearly demonstrate that the transfer of knowledge is actually much more complicated and less efficient than we expect it to be, including an example very similar to that fictionalised in The Wire, involving children working in Brazilian markets being able to demonstrate mathematical strategies on their stalls that they could not do in the classroom.

Although there is lots of excellent coverage (both academically and in blogs, e.g. here, here, here and here) on what the problem is and where it occurs, I realised that I hadn’t ever read much on why it occurs. I thought it might be interesting for those interested in these problems to provide some small insight into the neuroscience of transfer, to explain why it is about the way that the brain operates which means that transfer is so difficult to produce.

One of the reasons why we expect knowledge to transfer between contexts lies in our natural intuition that information in our brains is stored in a way that is fairly stable, so that it can be called up as often and whenever it is needed. Unfortunately this is an illusion. In actual fact, the development of our brains and the storage of information in them is hugely context-dependent, so that even in maturity we are still only ever dealing with ‘partial representations’; representations of the world which capture some, but not all of it. Partial representations are, by their very nature, completely context-dependent; that is they reflect of the features of the world (and of the brain) which were the case when the information was originally stored. What follows, taking the theory of ‘Neuroconstructivism’ by Mareschal et al (2007) as my guide, are four different levels on which the activity of the brain is constrained by the context in which it occurs, and why this context-dependence is relevant to the transfer problem.

  1. Neural context – ‘encellment

The cellular neighbours of a neuron exert a large influence over its eventual function as a processor of information. The characteristics of its response and the way in which it connects and influences other neurons is in turn dependent on the type and amount of activity that the neuron itself receives. On a simple level this can be demonstrated by the foundational principle of neuroscience, paraphrasing Donald Hebb, that “cells that wire together fire together”. The more that cells communicate with each other, the more that their connections are strengthened, and the greater influence that a preceding cell exerts over the activity of subsequent cell. However, the context-dependence of neural activity is not limited to the simple co-operative strengthening of connections. They can also compete. Many areas of the brain show competition between different neurons within the same region. Competition between cells is thought to be crucial to creating specialisation (such as cells which respond only to particular orientations in visual cortex), but it can also have more drastic effects. A famous example comes from Hubel and Wiesel’s Nobel Prize-winning work on the cat visual cortex. They found that newborn cats who had one eye occluded for a time (and then reopened) showed reduced space dedicated to processing information from the occluded eye and increased space processing that from the uncovered eye. As other structures earlier in the visual system still functioned normally after the re-opening (e.g. retinal ganglion cells and the lateral geniculate nucleus – the relay station to the visual cortex), the conclusion was that these changes were the result of activity-based competition between neurons; with the diminished input from the eye at a competitive disadvantage to input from other sources. This disadvantage eventually leads to visual processing being outcompeted, and other functions expanding to occupy the territory.

What does this mean for transfer?

How any neuron responds to an input is constrained by a number of different factors: the ever-changing strengths of connections to potentially thousands of other inputs (both excitatory and inhibitory), competition (or co-operation) between neighbouring cells, or a progressive specialisation of the cell’s function. This means that a signal from a neuron can only be interpreted as representing that cell’s response to a particular set of circumstances at that specific time; the neural context, if you will.

Another consequence of the reliance of each neuron’s activity on so many of its neighbours is that this means that any information that is encoded by the neuron is likely to be done so in a distributed fashion, across large groups of neurons. Such ‘distributed representations’, whilst more robust on the face of damage and brain changes, are also far more likely to be ‘partial representations’, relying as they do on numerous small contributions from different neural sources. They will never capture a concept or an idea in its entirety. Instead, they record a blurred snapshot of some of the key details approximating the concept, a partial representation.

2. Network context – ‘embrainment’

Just as individual neurons can be affected by the context in which they find themselves, so entire brain areas can co-operate, compete and change function as a result of their context within the brain as a whole. On a larger scale than that noticed by Hubel and Wiesel, Cohen et al (1997) found that in people who have been blind from an early age, visual cortex begins to take over other functions entirely, such as touch when reading braille. Similarly, if you re-route visual information into a ferret auditory cortex, the area will begin to respond to different orientation patterns from the visual scene outside (Sur and Leamey, 2001), as normally happens in visual cortex. In less drastic fashion, maturation in the brain involves the progressive specialisation of many different brain areas, which gradually take over sole control of functions which initially call upon wider networks of regions. Again this process can be categorised by competition, with one area gradually coming to exert a dominant influence over a particular kind of processing. Good examples of these sorts of processes have been found in the pre-frontal cortex (PFC) during adolescence, such as the inferior frontal gyrus for response inhibition or the rostrolateral PFC for relational reasoning (see Dumontheil, 2016 for a review of these and others).

What does this mean for transfer?

Most formal education is taking place during periods of rapid brain development and maturation. Brain areas are progressively specialising and refining their functions, dependent on their relationship to other brain areas and input from the outside world. In this context, the distributed and partial representations that we build of the world are likely to be highly context-dependent, not only on the particular pattern of inputs, but also on the time and stage of development in which the information was learned.

3. Bodily context – ‘embodiment

The brain does not sit in glorious isolation from the rest of the body. Some hard-wired nervous behaviours, such as reflexes, can in fact form the basis for the beginnings of brain development. Infants make spontaneous reaching movements from an early age and even new-born infants will move their limbs to block a light beam (Van der Meer et al, 1995). These kinds of behaviour initiate the beginnings of feedback mechanisms between the visual and motor areas of the brain and eventually allow for the development of complex visually-guided behaviour. Of equal importance, the design of some parts of the body can constrain brain development by ensuring that it does not need to develop certain skills; cricket ears are designed to respond preferentially to male phonotaxis (a sound made by rubbing one wing against the other). The cricket brain has no such specialisation for making this distinction, because the job has already been done (Thelen et al., 1996). In human cognition, examples of ‘embodiment’ might include state-dependent memory; the finding that we recall information more successfully in a similar ‘state’ to when we learned it, for example after exercise (Miles and Hardman, 1984) or even when drunk (Goodwin et al., 1969).

What does this mean for transfer?

The development of our brains is constrained and uniquely differentiated by our nervous systems and by the body in which we find ourselves. Again, this is not just the case between individuals but also within individuals as they develop over time, and as they pass through the myriad different internal states which characterise our existence. The representations that we have of the world will reflect these changing embodiments, and will be ‘partial representations’ in that they are formed, and linked to, this embodied context. This therefore provides further scope for learning to be constrained by the situation (in the widest possible sense) in which the information was initially encountered. The Goodwin et al. paper is particularly relevant here, as it tested two outcomes; recognition and transfer. They found that, whilst recognition memory was not significantly affected by the a change in states between learning and recall, the ability to transfer the information was. Transfer, as a more complicated cognitive procedure than simple recall, is as a result even more susceptible to being restricted by the context in which it occurs.

4. Social context – ‘ensocialment

The concept of ensocialment, the idea that the social context for any act of learning is crucial to shaping the learning that takes place, will be the most familiar of these four levels of analysis to educators. Vygotsky’s social constructivist theories are probably the most famous educational application of this sort of idea. People learn from others with more skills than them; with the more knowledgeable mentors using language and guidance to ‘scaffold’ the learner’s interactions with the world in the most productive manner. The concept of scaffolding; a supportive structure which is gradually removed as the learner gains in ability, is used to one degree or another by almost every major educational approach.

What does this mean for transfer?

The type of scaffolding that is used may become inextricably linked to the solution that is produced, to the point where the ‘partial representation’ that we have of the solution is not accessed when the problem is framed differently. Think of Prez’s dice-rollers on the street corner or the Brazilian market-children, still struggling when trying to solve the same problems back in the classroom.

It might be a problem… but it shouldn’t be a surprise

It seems eminently sensible that if we know how to do something, we should be able to reproduce that skill regardless of the changing context. No doubt it seemed obvious to the writers of The Wire that the dice-rolling students would be able to solve the probability exam questions in their next test. What I have tried to show here is that actually there is good reason for suspecting that this natural intuition is flawed. Context-specificity is built into even the most basic levels of our brain function, and it operates right through from the cellular level to the societal. It is therefore hardly surprising that we also see it occurring at the higher levels of cognition focused on by education, given that it occurs pretty much everywhere else. Even the most seemingly simplistic acts such as learning a sequence of movements does not transfer into improved learning of a sequence of the same movements in a different order (Karni et al., 1995), so the idea that we might be able to teach a problem solving technique in Geography and expect it to be used in Biology suddenly looks very optimistic indeed. Even strategies normally taken to be clearly domain general, such as some kinds of study skills, may actually be quite context-dependent (although there is evidence that some other skills, such as metacognition, may improve performance across domains). In fact the potential scale of this problem is something that I think many in education are simply in denial of, as to consider just how ‘partial’ are our representations of the world can seem to be the first step on a slippery slope into educational nihilism.

What the transfer problem means for education

Not that I think such pessimism is justified. None of this is to say that transfer is not possible or does not happen. Barnett and Ceci (2002) provide examples of how transfer can be made more likely. Indeed, as Didau points out, if the conditions are right then transfer could indeed become the norm. This would be especially true if we focus on problems of ‘near’ transfer with more modest goals, such as transferring strategies between different exam questions, or different classrooms etc. I agree with Didau’s prescription that explicit teaching of knowledge plus practice in applying the knowledge to different contexts is the approach most likely to bear fruit in educational terms. From the perspective of ‘partial representations’ this strategy is likely to lead to multiple, overlapping partial representations which are strengthened through repeated access, increasing the likelihood of them being more easily accessed subsequently. To take a contrasting educational perspective, such as discovery learning, this would only lead to the (time-consuming) creation of a single partial representation, which would be far more susceptible to context-dependency. From this perspective, it is not the discovery of the strategy which is important for subsequent success, but the practice of accessing the strategy multiple times and in multiple different ways. Perhaps ironically, then, the theory of neuroconstructivism can shine a light on why many ‘constructivist’ approaches in education fail. Constructivist learning theories tend to emphasise the importance of the construction of knowledge and the placement of knowledge into a concrete context from the very start. However, this prioritises the discovery of the strategy in a single context over the practice of a strategy in multiple contexts. It argues for the formation of a single representation over multiple representations. What I have tried to show above is that our representations of the world, by their very nature, are only ever ‘partial’ representations. Given that, it makes sense for educators to work to create as many of them, and to strengthen them, wherever possible.

References:

Barnett, S. M., & Ceci, S. J. (2002). When and where do we apply what we learn?: A taxonomy for far transfer. Psychological bulletin128(4), 612.

Cohen, L. G., Celnik, P., Pascual-Leone, A., Corwell, B., Faiz, L., Dambrosia, J., … & Hallett, M. (1997). Functional relevance of cross-modal plasticity in blind humans. Nature, 389(6647), 180-183.

Dumontheil, I. (2016). Adolescent brain development. Current Opinion in Behavioral Sciences, 10, 39–44. http://doi.org/10.1016/j.cobeha.2016.04.012

Goodwin, D. W., Powell, B., Bremer, D., Hoine, H., & Stern, J. (1969). Alcohol and recall: State-dependent effects in man. Science, 163(3873), 1358-1360.

Karni, A., Meyer, G., Rey-Hipolito, C., Jezzard, P., Adams, M. M., Turner, R., & Ungerleider, L. G. (1998). The acquisition of skilled motor performance: fast and slow experience-driven changes in primary motor cortex. Proceedings of the National Academy of Sciences, 95(3), 861-868.

Mareschal, D., Johnson, M. H., Sirois, S., Spratling, M., Thomas, M. S. C., & Westerman, G. (2007). Neuroconstructivism. Oxford University Press.

Miles, C., & Hardman, E. (1998). State-dependent memory produced by aerobic exercise. Ergonomics, 41(1), 20-28.

Sur, M., & Leamey, C. A. (2001). Development and plasticity of cortical areas and networks. Nature Reviews Neuroscience, 2(4), 251-262.

Thelen, E., Corbetta, D., & Spencer, J. P. (1996). Development of reaching during the first year: role of movement speed. Journal of experimental psychology: human perception and performance, 22(5), 1059.

Van der Meer, A. L. H., Van der Weel, F. R., & Lee, D. N. (1995). The functional significance of arm movements in neonates. Science, 267(5198), 693.

Veenman, M. V., & Verheij, J. (2001). Technical students’ metacognitive skills: Relating general vs. specific metacognitive skills to study success. Learning and Individual differences, 13(3), 259-272.

Wiesel, T. N., & Hubel, D. H. (1963). Single-Cell Responses in Striate Cortex of Kittens Deprived of Vision in One Eye. Journal of Neurophysiology, 26, 1003–1017. http://doi.org/citeulike-article-id:7746240

The ‘transfer’ problem is not a surprise. It’s central to how the brain operates

This confused ‘neuro-educationalist’ claptrap won’t help educational neuroscience. 

The notion of a ‘brain-friendly’ education always reminds me of ‘pet-friendly’ hotels, and I think the comparison actually bears some scrutiny. Arriving in even the most ‘pet-friendly’ of hotels, for example, you would not be surprised to find out that you were still expected to exercise some degree of control over your pet. Pet-friendly hotels do not expect the dog to be in charge; they don’t lay sheep carcasses around the lobby for them (and you) to roll in, and the decision to be ‘pet-friendly’ wouldn’t necessitate a complete redesign of the hotel layout and operating system. It is still a hotel, with some allowances made. ‘Brain-friendly education’, on the other hand, seems to often suggest that educational systems need to be subjected to a root and branch overhaul in order to accommodate learners who are entirely subjugated by a ‘developing brain’ which is in-charge, capricious, and requiring of special allowances. It seems less about being ‘friendly’ towards a brain, as much as desperately trying to appease its dictatorial authority.

If you will allow me to coin a few terms here, this ‘despotic-brain’ vision of adolescence assumes what we might call “neuro-determinism” – the primacy of a neuroscientific level of explanation over and above other levels of explanation such as the cognitive and the behavioural. This assumption is central to the claims of an increasing number of ‘neuro-educationalists’, who advocate educational reforms based on recent insights into the developing adolescent brain. It was at the heart of an article in the Washington Post today, which seemed to encapsulate many of the claims and argument techniques of those in the field: ‘Brain-hostile’ education: how schools are failing adolescents. As someone working in the intersection of neuroscience, psychology and education, what irritates me most about articles such as this is that potentially very good ideas are being badly used, with a handful of sensible propositions being swept along in a flood of premature, excessive or unwarranted extrapolations into real life. Some suggestions are deeply impractical, others ignore effective insights from other psychological disciplines which can be far more easily integrated into educational settings. Here is my reaction to some of the points made in the article, and why I think dealing with this sort of misinformation is crucial for the emerging academic field of educational neuroscience.

  1. Brain-friendly”, “brain-hostile”, “brain-ignorant

As I have said any phrase like this sets alarm bells ringing, hinting as it does at an unwarranted primacy of neural level explanations over other levels. This creates a false impression that we are nothing more than a slave to our neural wiring, which is simply untrue. See here for a good summary of the recent trend towards excessive neuro-hype.

2. “ A large-scale national survey of middle and high school students revealed that more than half of all 10th grade students were bored in class and less than half enjoyed being at school… “If we were doing right by our students and our future,” says Brandon Busteed, executive director of Gallup Education, “these numbers would be the absolute opposite. For each year a student progresses in school, they should be more engaged, not less.’’ 

Why? And why does this support anything ‘brain’ related? If teenagers are often bored in school, this is not automatic evidence of a’brain-hostile’ curriculum. If I find a topic boring, I don’t automatically conclude that the topic was at fault for not being sufficiently ‘friendly’ to my brain. Is it realistic that, as they get closer to the major summative exams which will end their school careers, students should also be expected to be enjoying themselves more and more? On a separate note, as people such as Greg Ashman have pointed out, engagement is a poor proxy for learning, so reduced enthusiasm does not necessarily translate into reduced learning.

3. “At a time when adolescents’ emotional brains are jacked up to the max, the middle and high school curriculum suddenly “gets down to business” and becomes emotionally flat in tone.”

It’s true that emotional processing may exercise disproportionate influence in the adolescent brain (see previous post here), but it doesn’t follow from this that we need some sort of tempestuous, emotionally-charged curriculum for them. Admittedly, I don’t know what an ’emotionally-charged curriculum’ would look like, but then I don’t know what an “emotionally-flat” one looks like either.

4. “At a time when the adolescent’s brain increasingly craves stimulation from peers, education becomes more teacher-centered, offering less small-group interaction and cooperative learning than elementary classrooms.” 

Again this suggests an excessive level of neuro-determinism. Also, just because of the (accepted) fact that adolescents brains respond to social interaction differently (see e.g. Chein et al., 2011 or Somerville, 2013), why does this lead to the conclusion that we must place them in these situations more? Adolescent brains also have increased sensitivity and neural responses to risk taking and rewards (e.g. Fryt & Czernecka, 2015) but I can’t imagine the author complaining that “at a time when the adolescent’s brain craves stimulation, society increasingly makes an effort to prevent them from driving too fast or taking large quantities of recreational drugs.

On a more educational note, the idea that more collaborative work would lead to improved learning in teenagers (or any age groups) is generally pretty flawed, for reasons that are well documented by Tom Bennett here.

5. “In addition, teachers promote student embarrassment by posting students’ grades and test results for everyone to see, and ban or restrict social media that could facilitate interpersonal learning in the classroom.”

When does this happen? It certainly isn’t standard practice anywhere I’ve ever worked or heard about. This seems to be a descent into simple misinformation and inaccuracy. Also, with regards to the ‘social media’ point, it should be noted that the use of technology to assist learning is often met with mixed success, especially social media (see e.g. McCoy, 2013;  Sana, Weston & Cepeda, 2013; Junco & Cotten, 2012)

6. “At a point when students’ decision-making skills are at a critical stage of development and the prefrontal cortex is going through a process of fine-tuning, zero-tolerance discipline policies run roughshod over students’ capacities to learn from their mistakes.” 

I’ve written about the adolescent brain’s ability to learn from feedback, and it is true that rewards seem to need to be more salient to produce the same level of response in adolescents as in adults (see e.g. Galvan, 2013)… but is the suggestion here that there should be some sort of brain-differentiation of discipline systems in a school? “Pupil A can have one more warning than pupil B on account of her more immature frontal cortex”? Nonsense. Adolescents are not idiots. They understand right and wrong. The fact that they may push boundaries, break rules and respond slowly to feedback will indeed have neuroscientific roots (as well as partly resulting from increased social freedoms to be able to do these things), but this in no way means that they should be exempted from our normal societal (or school) rules. If anything it makes it more important that they aren’t. Again, this is unwarranted neuro-determinism.

7. “In addition, schools heap required courses on students to prepare them for college, some actually requiring students to declare a major or course of study in ninth grade or even earlier. This approach deprives students of opportunities to take electives that are interesting to them and that might lead to a vocation in adulthood.” 

The make-up of the school curriculum is always a contentious issue. No idea what it has to do with neuroscience though.

8. “During a point when students are entering the developmental stage of formal operational thinking and are able to engage more deeply in metacognition, the curriculum begins to devote more attention to lower-order skills, such as recall of facts, formulas, and details.”

Once we’ve cut through the jargon salad here, we’re left with a point that is a) not about neuroscience, and b) incorrect, creating as it does a false dichotomy between ‘lower-order’ and ‘higher-order’ skills which does not exist. ‘Lower-order’ facts and ‘higher-order’ problem-solving are not rivals; indeed ‘lower-order’ knowledge is a necessary condition for higher-order problem-solving. They are inseparably linked. E.D. Hirsch has spent 50 years trying to get this message out.

9. “Finally, at a time when adolescents have a huge appetite for rewards, teachers start employing higher standards in judging student competence and tend to give lower grades than elementary school teachers.” 

Now I happen to think that the well-documented changes in the processing of reward stimuli in adolescents might be something which could be relevantly exploited in educational settings… but imagine if the ‘solution’ that a school came up with was to simply increase teenagers’ grades (to what? ‘A++’? ‘A****’? ‘A^^^!!@^^”’?). Quite apart from the the obvious stupidity in the idea of an arbitrary increase in teenage grades (and the small problem of looming external examinations, which presumably would not be so inflated), this again falls foul of the fallacy of neuro-determinism. It treats adolescents (or anyone) as drooling idiots, helplessly controlled by their all-powerful developing ‘brain’ and therefore unable to display any skill unless it is in a ‘brain-friendly’ setting. It also ignores the fact that rewards are context-dependent. Getting a ‘C’ grade can feel like a Nobel prize in some contexts, and an ‘A’ grade would be a kick in the teeth if everyone else was getting A****.

10. “The sensation-seeking behavior that can lead adolescents to drug abuse could alternatively be directed toward a highly engaging student-centered learning project. The reward-seeking behaviors that might lure teens into Internet addiction could be tapped through a game-based learning experience in the classroom.” 

A bizarre and slightly threatening conclusion. So are teachers to blame if a student has an internet addiction, because they haven’t game-ified their lessons enough? The sad thing is that, minus the hyperbole, there are relevant and interesting things to say about some of these ideas. Take reward-seeking and game-based learning experiences. As it happens, a large-scale trial of a particular teaching approach derived from neuroscientific evidence about teenage reward processing is currently ongoing in schools. The ‘Sci-napse’ project, lead by Paul Howard-Jones in Bristol, is based on findings about neural responses to uncertain rewards, and involves a ‘gaming’ like system for points scoring within lessons. this is a really exciting and promising project, and I can’t wait to see the results… but we’ll have to wait another year at least for those. Would it really be so boring then, instead of threatening teachers with drug-abusing students if they don’t include enough group work, to have a more measured and sober conclusion? Something like “games involving uncertain rewards in the classroom may allow us to effectively exploit changes in adolescent reward processing for educational benefit, but the tests are ongoing and we’ll know more when they’re done

Ironically, it is the power of ‘neuroplasticity’ – that buzz word of popular neuro-educationalism – which is actually the reason that most of their propositions fail to hold water. Plasticity is precisely what allows us to rise above the ‘determinism’ of our developing (or regressing) cortices. It is what allows us to create behavioural and cognitive strategies which mitigate our weaknesses, be that learning the flute when we’re 80, or revising the Tudors even when we’re bored. These strategies are ‘brain-based’ in the facile sense that pretty much everything that we do is brain-based to some degree, but they are implemented at a level above the neuroscientific. The interplay between these levels is hugely complex and poorly understood, but what is clear is that any developed picture of learning (and so any coherent theory of education) requires all levels to be taken into account. Too often, neuro-educationalists ignore these non-neural levels entirely, creating a neuro-deterministic picture of us (and especially teenagers) as cerebral automatons; slaves to our circuitry without considering the programs that those circuits might be able to run.

The thing which frustrates me most about these sort of articles is that I genuinely believe that neuroscience has a lot to potentially offer to education… just not like this. Hyperbolic depictions of schools as “brain-hostile” dystopias where adolescent dreams go to die (and where the only the only saviour is neuroscience) fly in the face of reality and evidence, and create the impression that educational neuroscience is attempting to circumvent the knowledge and expertise of other established disciplines, such as developmental, cognitive and educational psychology. This is not true at all (certainly it is not true in my mind). I have referred to ‘neuro-educationalists’ in this article to try to differentiate them from ‘educational neuroscientists’, who I see as playing a collaborative role in connecting cognitive theories of learning with the underlying neuroscientific evidence and constraints. Educational neuroscience is struggling for acceptance as a discipline. I briefly covered (and linked to) some of these criticisms in my first ever blog. In a slightly hostile environment it can be tempting to grab onto any show of support, and indeed I first saw this Washington Post article when it was tweeted by a prominent ‘ed neuro’ advocate. But by promoting these articles we only strengthen the case of the detractors and increase the perception of a charlatan enterprise. With friends like these, who needs enemies?

 

References:

Sana, F., Weston, T., & Cepeda, N. J. (2013). Laptop multitasking hinders classroom learning for both users and nearby peers. Computers & Education, 62, 24–31. http://doi.org/10.1016/j.compedu.2012.10.003

Junco, R., & Cotten, S. R. (2012). No A 4 U: The relationship between multitasking and academic performance. Computers & Education, 59, 505–514. http://doi.org/10.1016/j.compedu.2011.12.023

Somerville, L. H. (2013). The Teenage Brain: Sensitivity to Social Evaluation. Current Directions in Psychological Science, 22(2), 121–127. http://doi.org/10.1177/0963721413476512

Galván, A. (2013). Current Directions in Psychological Science The Teenage Brain : Sensitivity to Rewards. Current Directions in Psychological Science, 22(2), 88–93. http://doi.org/10.1177/0963

Fryt, J., & Czernecka, K. (2015). Cognitive control, reward sensitivity and risk-taking in adolescence – research perspectives of the dual systems model. Postępy Psychiatrii I Neurologii, 24, 231–238. http://doi.org/10.1016/j.pin.2015.10.004

Chein, J., Albert, D., O’Brien, L., Uckert, K., & Steinberg, L. (2011). Peers increase adolescent risk taking by enhancing activity in the brain’s reward circuitry. Developmental Science, 14(2), F1–F10. http://doi.org/10.1111/j.1467-7687.2010.01035.x

McCoy, B. R. (2013). Digital Distractions In The Classroom: Student Classroom Use of Digital Devices for Non-Class Related Purposes. Journal of Media Education, 4(4), 5–12. Retrieved from http://en.calameo.com/read/000091789af53ca4e647f

This confused ‘neuro-educationalist’ claptrap won’t help educational neuroscience. 

From the Enlightenment to neurobollocks: The ‘myth of progress’ in teaching

In my last post I looked at recent research which illustrated that brain-training is not as effective as the adverts might make out, as well as reminding us that many of the benefits claimed by brain-training programs are available using existing, often time-honoured and rather mundane methods. This lead me to think about why this bias towards the novel exists, to the point where we may systematically ignore solutions that have been effective for years.

The concept of universal education can be traced back to the Enlightenment, indeed it is one of the most enduring products of the period. In a “post-factual” age when, in the words of Stephen Fry,

the achievements of the enlightenment are questioned, ridiculed, misunderstood and traduced by those who would reverse the progress of mankind

it is notable that the notion of universal education has never been seriously questioned. It was the product of two major Enlightenment advances, one scientific and one philosophical. Firstly, scientific breakthroughs from the likes of Newton, Kepler and Galileo led to an optimistic outlook regarding humans’ ability to comprehend and shape the world around them. Subsequently, John Locke and other figures from the emerging philosophical school of Empiricism began to argue that knowledge could only be gained through the senses; through our interactions with the world and by our subsequent reflections on the impressions that these interactions created. Empiricism led naturally on to ideas of universal education; since we all have pretty similar faculties for the sensation of the world, there seemed no obvious reason why all people should not be able to benefit from educational experiences which had, to that point, only been available to a privileged few. Presumably, then, the more people that were educated, the faster still would be the progress and development of the species. The confluence of these two factors – optimism about our scientific capabilities and an empiricist notion of education for all – created a powerful narrative which persists today: humans are capable of greatness and education is the tool for that greatness to be realised as widely and as effectively as possible. Education as the engine of human progress. So far so good, and I agree…

But this optimism can also have a corollary. It can create a general belief that, the occasional blip notwithstanding, we are on something of an inexorable march of ‘progress’. Indeed the notion of ‘progress’ was an important one for many Enlightenment thinkers, who drew a sharp distinction between more ancient voices such as Plato and Aristotle who saw society as a cycle, with periods of progress and development unavoidably followed by decline and disaster. Enlightenment thinkers, especially those armed with the emerging theories of evolution in the late 18th century and beyond, often presented ‘progress’ as an essential part of human nature, with our increasingly successful adaptation to our surroundings reduced to a simple (and inevitable) biological necessity. This narrative of progress is powerful and seductive, but it is also potentially dangerous one. Theories regarding the ‘progression’ of the species have been at the heart of some of the worst of subsequent human thought, justifying eugenics and genocide. In a less serious form, however, a blinkered faith in human ‘progress’ can lead to either a casual over-optimism regarding our current actions, or a tendency to embrace the ‘new’ and to reject the status quo. In both cases, this novelty bias can encourage us to change systems without due scrutiny being applied to their newer replacements.

Teaching, as we have said, is an Enlightenment profession. The nature of teaching means that many of the goals of the Enlightenment are also implicit assumptions of the profession. The belief in improvement through information, that the widest benefits for the world will come from the widest dissemination of knowledge, a passion for the democratisation of learning and so on. It is hard to imagine anyone entering the profession without holding these basic assumptions. In addition, it is not a profession where we can ever conceivably judge that we have done enough, or produced the ‘best possible’ results, so there is always a desire for progress: better exam results, value-added scores, enrolment figures, university entry rates etc etc – something could always be improved. Yet perhaps the same Enlightenment-era zeal which drives us can become something of a double-edged sword, leaving us vulnerable to falling for the ‘myth of progress’. I would argue that, just as it embodies many of the virtues of the Enlightenment, teaching is also prone to demonstrate the occasionally casual over-optimism of the time, and to embrace the novel over the time-honoured too unquestioningly. ‘Change for change’s sake’ is a frequent lament in the classroom in response to yet another management initiative, but teachers also need to critique their own classroom practice in the same spirit. How often do we jump to incorporate trendy new ideas or the latest cultural craze into our lessons (Pokemon Go, Minecraft, iPads etc etc), without really assessing how we are expecting it to make for a more effective learning experience? Another example might be the over-eager and premature adoption of new scientific ideas (gleefully exploited by unscrupulous edu-quacks), which has lead to widespread misinformation about the brain and learning amongst teachers (see e.g. here), and bogus interventions like Brain Gym, the Dore program or inappropriate use of the ‘growth mindset’. We also have explicitly named ‘Progressive’ education movements, which may embody many modern values, some of which have been translated into educational programs without due assessment of the relevance or efficacy of this translation. Changes in conceptions of individual rights and freedoms have metamorphosed into doctrines of student choice or ‘personalised learning’, which in turn have engendered such ineffective educational enterprises as ‘free-schools’ or learning styles.

I should be clear here that I don’t think that these problems are unique to teaching as a profession; I am sure that a good deal of this novelty bias is a natural human tendency shared by us all. But I do think that the aims of the profession, along with the inherent difficulty in ever defining or measuring ‘success’, make it especially vulnerable to a headlong search for the next new magic idea. Sometimes, however, what we’ve got already may actually work pretty effectively. Let’s try to remember that for when the next bandwagon rolls into town.

References:

Dekker, S., Lee, N. C., Howard-Jones, P., & Jolles, J. (2012). Neuromyths in Education: Prevalence and Predictors of Misconceptions among Teachers. Frontiers in Psychology, 3, 429. http://doi.org/10.3389/fpsyg.2012.00429

Howard-Jones, P. (2014). Neuroscience and education: myths and messages. Nature Reviews. Neuroscience, (October). http://doi.org/10.1038/nrn3817

From the Enlightenment to neurobollocks: The ‘myth of progress’ in teaching

The silver bullets we already have

The recent finding (following a detailed review of all available evidence on the subject) that brain-training games are not effective (nicely summarised here if you don’t fancy all 80 pages worth) is the latest in a line of setbacks for the idea that repeated training of a particular mental function can have wide-ranging benefits for cognitive functioning and health (e.g. see here and here). This is not to say that brain-training is dead; it is possible that further research or new techniques (such as neurofeedback) could still allow for more effective forms of cognitive training which transfer over to other skills and domains. So the research should continue… but the hype should stop.

The Simons et al. article was published in the journal ‘Psychological Science in the Public Interest’, and it came with a fascinating commentary, which provided a delightful counterpoint to the main article. The basic thrust of ‘Brain-Training Pessimism, but Applied-Memory Optimism’, by McCabe et al. was that many of the purported benefits that are so desperately being sought by the proponents of ‘brain-training’ are already available to us, and in some case have been so for a hundred years or more, through the application of years of cognitive psychology research into memory. They give the example of three related memory strategies which have been consistently found to improve recall: elaboration, testing and spacing.

What’s really interesting about the McCabe et al. article is just how refreshingly low-key the authors’ solutions are. No novel tricks, or creative new strategies for their use – merely a reminder that before we go out searching for new silver bullets, we should check the ammunition store that we already have. The tragedy is that, for whatever reason, this does seem to happen; McCabe at al. cite a number of studies demonstrating that students still report not knowing how to study effectively. Another great champion of applied memory strategies, the Learning Scientists, have recently taken to re-tweeting students lamenting their lack of study skills as an illustration of the problem.

how-to-study

The great advantage of these applied memory approaches over brain-training type interventions is that they work on the level of strategies, rather than on abilities. Abilities are specific, hence the problem of transferring the development on one into the development of another (becoming very good at doing crosswords won’t necessarily make you better at Sudoku). Strategies can be used across multiple different abilities; I can self-test on geography and on history, and gain benefit in both. This is not to say that any strategy can be used regardless of the domain – the type of self-testing that works best in music may be different from that in maths – but the general principle of testing leading to effective learning does seem to hold across different areas (for excellent recent examples see Dunlosky et al, 2013 and Roediger & Pyc, 2012).

Assessment of the utility of learning techniques, from Dunlosky et al. (2013):dunlosky

Perhaps it is simply natural human nature to be a chronological snob, and to search for newer, shiner solutions to problems than the ones we already have. I suspect, actually, that teachers are unusual in their desire for ‘new’ solutions to problems, something that I will try to explore in my next post. In any event, the lesson that I felt was elegantly made by McCabe et al. is that sometimes finding new solutions can be less important than making sure that everyone knows about what we already have.

Other links for practical suggestions to apply memory strategies to their classroom (or to direct students towards):

References:

Dunlosky, J., Rawson, K. a., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology. Psychological Science in the Public Interest, 14(1), 4–58. http://doi.org/10.1177/1529100612453266

McCabe, J. A., Redick, T. S., & Engle, R. W. (2016). Brain-Training Pessimism, but Applied-Memory Optimism. Psychological Science in the Public Interest, 17(3), 187–191. http://doi.org/10.1177/1529100616664716

Roediger, H. L., & Pyc, M. A. (2012). Inexpensive techniques to improve education: Applying cognitive psychology to enhance educational practice. Journal of Applied Research in Memory and Cognition, 1(4), 242–248. http://doi.org/10.1016/j.jarmac.2012.09.002

Shipstead, Z., Redick, T. S., & Engle, R. W. (2012). Is working memory training effective? Psychological Bulletin, 138(4), 628–54. http://doi.org/10.1037/a0027473

Simons, D. J., Boot, W. R., Charness, N., Gathercole, S. E., Chabris, C. F., Hambrick, D. Z., & Stine-Morrow, E. A. L. (2016). Do “Brain-Training” Programs Work? Psychological Science in the Public Interest, 17(3), 103–186. http://doi.org/10.1177/1529100616661983

The silver bullets we already have

Psychology for teachers

There are many superb blogs on teaching, and some which focus specifically on the links between teaching and the psychology of learning. What I feel is sometimes not available to teachers are short and accessible introductions to some key ideas regarding how we learn.

This section consists of a series of short blogs designed to introduce teachers to research findings about how students learn, with suggestions for how these ideas could influence practice and links etc for further reading. I hope that you enjoy reading them and find them useful. If anyone has any suggestions for other topics which could be added, please let me know!

It is important to realise that none of these strategies is a magic ticket on their own! Instead, they are a foundation, from which each teacher can experiment and adjust their practice as best suits their teaching style and their school environment. The ‘suggestions for practice’ are simply that – suggestions. You may be able to think of much more effective ways of incorporating a particular piece psychology into your lessons. Feel free to try out new things and to experiment, but use these evidence-based ideas as a starting point. Why not use one or more of these as the basis for a new scheme of work or learning policy at your school? Or arrange an internal CPD day to share ideas and resources?

If you find a particularly effective method that seems to improve student progress, why not contact a Psychology or Education department at a university and see if you can arrange for a larger scale trial of the idea. In fact I would encourage all teachers and schools to take part in research projects into what works in education. The more teachers and schools that can become the driving force behind research (and key partners in it), the more progress we will make in discovering what techniques really work in schools.

The ‘Psychology for Teachers’ section currently contains introductions to (in alphabetical order):

Psychology for teachers

Working memory

Basic idea:

Any time you are ‘holding something in your mind’, such as calculating a bill, remembering a new phone number or a set of directions you’ve just been given, you are using working memory – it’s the name given to our ability to hold (and also manipulate) information in our minds over short periods of time.

In adults, famous experiments from the 1950s suggested that the capacity of this memory store was ‘7 plus or minus 2’ items – in other words between 5 and 9 items, depending on the individual. We can increase this capacity with clever strategies or if the information is in different forms… but it’s still a useful guide.

Children’s working memory capacity is still developing until their mid-teens in most cases, and approximately 10% of children in any one class may display impaired working memory. This means that in a class of 9 year olds, we might expect at least 3 or so to have a WM capacity of not much more than 2-3 items. This is important, as teachers may quite often give instructions which consist of a number of steps (e.g. “Cut out the shape from the piece of paper and stick it in your, books, then finish the exercises from yesterday”). This might exceed the WM capacity of some children, leading to organisational difficulties.

Suggestions for practice:

  • Reduce the number of steps in instructions that are given at one time, or breaking down tasks into chunks.
  • Provide instructions in written forms, or some other form that can be referred back to.

Team this idea also with ‘load theory of attention’ – aim to produce activities which have high attentional load but low working memory load. Also with ‘cognitive load theory’, which helps to clarify the sorts of activities which influence working memory.

Further reading:

The WM bottleneck… https://evidenceintopractice.wordpress.com/2014/05/07/the-working-memory-model-a-brief-guide-for-teachers/

http://www.mrc-cbu.cam.ac.uk/wp-content/uploads/2013/01/WM-classroom-guide.pdf

Turn it off! Working memory limitations explain why music and learning don’t often go together…

http://www.edutopia.org/blog/dont-listen-music-while-studying-david-cutler

Working memory