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Clark, J.A. (2015). Early childhood education: Fracture lines of social context and neural development. NZ Research in Early Childhood Education Journal, 18, 80 - 86.
Critical Review Paper
Early childhood education: Fracture lines of social context and neural development
The debate between academics in the Listener about early childhood education raises issues which warrant further critical examination.
One issue concerns the weight to be given to families over schools/ centres when it comes to children’s learning. Too often the matter is considered in terms of within school and beyond school dualism of factors but there are significant problems with this way of seeing things. A better way is to adopt a proximal/distal continuum whereby all factors are taken into account, regardless of their importance.
A second issue centres on what is required to maximise the learning of young children. Given the centrality of their neural development and the links to family circumstances, it is essential that teachers and parents have a sound grasp of the underlying neural structure of learning to underpin successful learning by all children.
Key words: Learning; home-school factors; curriculum, Te Whariki, brain development.
A Listener article (Woulfe, 2014) would not usually elicit an academic response, but when it involves the likes of Professors John Hattie (Auckland/Melbourne), Helen May (Otago) and Richie Poulson (Otago) as well as Dr Sarah Alexander (ChildForum Early Childhood Network) and Dr Ken Blaiklock (Unitec) then you know something is afoot. There are two aspects of the academic disagreement which warrant additional comment.
Beyond the family: Proximal and distal causes
Woulfe (2014) remarks: “Always in education, family factors such as socio-economics, the parents’ education levels and the interest parents take in their child’s learning trump whatever a school can do” (p. 16). A strong case can be made that beyond school/centre factors outweigh the impact of within school/centre ones on student achievement. And the most significant within school/centre influence on student achievement is not the teacher. The single greatest factor having a direct and immediate impact on student achievement is what children have in their brains at the time which can be retrieved and brought to bear on school performances which are assessed. Teachers are, causally, one removed from student achievement, being only one of many influences on what goes on in a child’s head where learning occurs (Clark, 2014). Even in the classroom it is plausible to conjecture that other factors are at work which have greater effect on the learning which goes on in a child’s brain, such as interaction with other children, digital sources of information of various sorts and so on. By comparison, the direct influence of the teacher on learning itself may be less than conjectured.
The stance presented by Woulfe must be significantly revised in two crucial respects. First, the factors beyond the school must be enlarged to sheet home a wider causal set. Certainly, family conditions cannot be ignored for they play a pivotal role in shaping the experiences from which children learn. Plenty of money provides new opportunities for travel, sports and hobbies, books and digital technology and the like. A dire shortage of money invariably leads to poverty, inability to pay for doctor’s visits and pharmacy prescriptions, and so on. However, family life, whether it be rich or poor, does not exist in a social/political/economic vacuum. Rather, family circumstances are very much shaped by forces beyond the control of families, such as government decisions on policy which are translated into things like budget allocations to health, welfare, employment and education and business decisions which increase or decrease commercial activity and concomitantly raise wages or make workers redundant.
The second crucial consideration is this: all too often the debate about the factors influencing learning and school achievement is couched in terms of within and beyond school/centre factors. This dualism is without merit and should be discarded. It falls short in two critical respects. The factors are allocated to one category or the other without recognition that some factors are contained within both. An example of this is when parents talk to teachers at parent/teacher meetings and reach agreement on a joint home/school approach to improving a child’s learning and achievement. A closer inspection of factors would suggest that it is impossible to draw a clear epistemic line between within and beyond school factors. No factor is simply and solely either within or beyond; rather all factors contain both within and beyond elements. Beyond school factors are not left at the gate but are brought right into the classroom while within school factors are taken beyond the school to wherever students go.
But the dualism comes unstuck in another way. It tends to propel adherents to one side of the dualism or the other with the consequence that far too much attention is given to the favoured side and far too little attention is given to that which is opposed. This is evident, for example, in the reluctance of those who favour within school/centre initiatives to consider any action which extends beyond institutions. A better way to map out the complexity of the causal terrain is to adopt the proximal/distal continuum. Take all the possible factors, whatever they may be, and align them along the continuum from those nearest and most immediate, the proximal, such as what a teacher says and whether parents read stories to their children, all the way out to the furthermost reaches of the distal where lie the decisions of government and business. No factor is arbitrarily excluded even if agreement is absent from the weight to be given this factor or that. And for every child, there may be some common factors (poverty) and others quite unique to them (personal experiences). All of this complexity needs to be captured in an explanatory way when attention turns to the life chances of those who do and those who do not access out-of-home formal early childhood education (children in wealthy urban communities are more likely to participate compared to those who live in poor urban or remote rural ones).
The neural underlay
The bigger disagreement centres on language development.
According to Hattie, there is “a ‘massive hole’ in our much-lauded curriculum, Te Whariki: its flexibility lets teachers skip over the crucial area of language development. This…is the stuff that can really make a difference to our most at-risk children, who aren’t exposed to rich vocabulary and conversations at home. I think it’s a scandal….Not nailing those language skills early can compromise the rest of a child’s schooling” (Woulfe, 2014, p. 20).
Karl Le Quesne, the Ministry of Education’s group manager for ECE, as reported by Woulfe (2014), has a different view.
Le Quesne says “equally if not more important” than covering the cognitive bases is that children become excited about learning, curious about the world and persistent, and can work with others to solve problems. “We haven’t seen any really robust evidence” to bear out Hattie’s concerns, he says. But it seems we haven’t any evidence to the contrary either (p. 21).
This, then, sets the scene for the intellectual disagreement. What are we to make of it?
To start with the last point first. The distinction between the cognitive and the non-cognitive is firmly grounded in a basic ontological feature of human existence although whether greater weighting is to be given to the non-cognitive remains to be seen. Quine (1979) makes the point that following conception we develop two related standards, a similarity standard and a preference standard. These are not something we learn since if it were it would presuppose some prior innate mechanism to make such learning possible. Our standards are given to us, innately, as part and parcel of our development prior to birth. At birth, we begin to use these standards to both learn and understand our experience of the world. Our similarity standard allows us to see things as similar to (and different from) other things, as we see them at the time. This is the beginning of our empirical understanding of what is, including our understanding of the cognitive development from birth through to adulthood (and more on this later). Our preference standard works in tandem, consisting at first of no more than simple likes and dislikes evolving over time to full blown judgements about the moral and aesthetic worth of things.
The cognitive ‘is’ and the non-cognitive ‘ought’ are interconnected. What we learn is shaped and directed by what we are interested in and exposed to: being excited and curious about something are good levers for learning and learning well. Being excited and curious cannot get any purchase on learning at all if we lack the cognitive capacity to neurally process and remember the information acquired from experience. Both the cognitive and the non-cognitive are required in good measure and it be a mistake to claim that the latter is of greater worth than the former, for this is to seriously distort how the cognitive and the non-cognitive work in tandem (A baby, on some particular occasion, uses both its similarity standard to distinguish sweet from sour tastes and its preference standard to express a liking of one over the other).
Whether Te Whariki has conceptual flaws of the kind alleged is for others to decide, but one thing is clear: if it ignores the evidence from the neurosciences about how we learn from birth onwards then the education of young children will be all the worse for it. To explore why this should be so requires the separation of two inter-related elements: etiological factors and constitutive factors (Robins & Craver, 2009). Etiological features of learning make reference to the causal mechanisms of the world outside of the brain and include all those social and environmental elements which impact on learning as a neural process. Constitutive features of learning refer to the causal mechanisms internal to the brain to include all the biological, chemical and electrical features which make learning and memory of the external world possible. How the etiological and the constitutive come together is the key to explaining learning and its maximisation.
The neural and the social
The work of Nelson and Sheridan (2011) offers some important insights into the connection between families and neighbourhoods (but unfortunately not the wider social/economic/political forces) and school achievement along with labour-market destinations as mediated by human development and the workings of the brain as the lynchpin. In short, we can have no understanding of how the social inputs can have subsequent behavioural outputs in the absence of an explanation of how the brain mediates between them.
How families, schools and neighbourhoods impact on learning will depend very much on how the young child’s experiences are aligned with changes in brain development. This is a complex matter requiring some elaboration. The brain is not some static organ to be filled with experience but is constantly in flux as learning shapes it and it shapes learning. Consisting of up to 100 billion neurons (brain cells) with each neuron composed of a single axon and many hundreds if not thousands of dendrites (think of the axon as similar to a tree with a trunk and branches and the dendrites as akin the tentacles of an octopus) where the dendrites of one neuron connect to the axons of many other neurons to form a neural network of up to 1000 trillion connections. Across this massive neural network, information flows in parallel along the many connections between neurons via their axons and dendrites with the electro-chemical exchange taking place at the synaptic gap where axon and dendrite meet. The brain possesses plasticity: that is, even if we are born with a set amount of brain cells and lose many of them in the course of our lives (Churchland, 1986), the number of dendrites can increase along with the connections between axons and dendrites which later can be lost through pruning. As we learn more so do our synaptic connections increase, and decrease as we forget things once learned.
Soon after conception, within three to four weeks, the embryo forms a neural tube which generates the growth of neurons until early post-natal life. This process overly produces brain cells such that the infant has many more of them than they will have when adults. Over the course of the first few years of life there will be a massive loss of neurons. As with neurons, there is a massive over-provision of dendrites and synaptic connections and subsequent pruning of them. Now, if the origin and early growth of neurons is genetic, their reduction is due in large part to experience. The former we cannot control, the latter we can to a considerable degree. However, the development of the brain, the rise and fall of the neural componentry, is not all of a kind but varies with time:
…the peak of overproduction of synapses in the visual cortex, the locus of our ability to see, occurs at around four months, and adult numbers of synapses are eventually reached by the time a child is four to six years old. In contrast, the peak of overproduction of synapses in the pre-frontal cortex – the area of the brain that sits behind the forehead and is involved in higher cognitive function and regulating emotions - occurs at about one year of age, and adult numbers of synapses are not obtained till mid- to late adolescence (Nelson & Sheridan, 2011, p. 29).
None of this implies neural determinism because while genetics may supply the initial brain material it is modified, and heavily so, by experience. For example, alcohol and drug abuse by a pregnant mother can have serious effects by irrevocably destroying neurons and pruning synaptic connections in the unborn child’s brain which may later be essential for memory of past learning and the facilitation of new learning.
There are two forms of neural plasticity: developmental and adult plasticity. Developmental plasticity takes place during the period of rapid neural expansion while adult plasticity occurs once the neural network is cemented in. Nelson and Sheridan (2011) make plain the significance of both forms of plasticity. With adult plasticity, once the neural connections are in place it is often more difficult to alter them, especially if they are formed early in life. Things are a bit different with developmental plasticity:
…there are constraints on developmental plasticity. First, because different regions of the brain mature at different rates, once a region or circuit is mature, it will prove much more difficult to modify with experience. Thus, timing matters. Second, some regions and circuits require more experience than others to develop normally, and if sufficient experience does not occur during the time that particular region or circuit is forming, the function of that region or circuit may be limited. For example, for normal language acquisition to occur, children must be exposed to the sounds of language very early in life. Such experience sculpts and eventually narrows the perceptual window through which language is processed, leading to expertise (p. 30).
Noting that some neuroscientists have adopted the expression “plasticity cuts both ways”, Nelson and Sheridan go on to say:
If a brain is exposed to good experiences during a sensitive period, then the long-term outcome is biased to be positive. However, if the brain is exposed to bad experiences, then the long-term outcome is biased to be negative. Once a particular region or circuit of the brain has passed through a sensitive period, the principles of developmental plasticity cease to play a role, and the mechanisms of adult plasticity must come into play (p. 31).
All of this suggests that Hattie’s concerns, outlined earlier, are with some empirical foundation. Advances in the neurosciences indicate that even if our understanding of the brain is not the whole answer to the differences in learning and the inequality of school/centre achievement, then it is nonetheless a critical part of it. It helps us to understand, at a deeper level, why certain sorts of experiences (such as language acquisition, skills development and social interactions) are so essential to the cognitive development of young children and their later life chances. We cannot do much about our neural endowment, for that is given to us: but what we do with it is up to us. How we use it to maximum benefit depends very much on adults, especially parents and teachers, having a far better understanding of how etiological experiences and constitutive processes come together in the young child’s brain in order to maximise learning. This will give every child the best opportunities possible for successful school achievement, later satisfying labour market destinations and the living of a good life.
Clark, J.A. (2014). Challenging a myth: teachers do not have the greatest within-school impact on student achievement. New Zealand Principal. 29(2), 25-6.
Nelson, C. & Sheridan, M. (2011). Lessons from neuroscience research for understanding causal links between family and neighbourhood characteristics and educational outcomes. In G. Duncan & R. Murnane (Eds.) Whither opportunity? Rising inequality, schools, and children’s life chances. (pp. 27-46) New York: Russell Sage Foundation.
Quine, W.V. (1979). On the nature of moral values. Critical Inquiry. 5, 171-80.
Robins, S. & Craver, C. (2009). Biological clocks: explaining with models of mechanisms. In J. Bickle, (Ed.) The Oxford handbook of philosophy and neuroscience. (pp. 41-67) Oxford: Oxford University Press.
Woulfe, C. (2014). Early warnings. Listener. April 19. 16-23.
About the Author
John Clark is an Associate Professor at Massey University, Palmerston North. He is a philosopher with a particular interest in neuroscience and education, especially as this relates to the causes of and solutions to the inequality of student achievement. The issues discussed in John’s paper form part of a wider and on-going philosophical research programme into the deep dispute between folk psychology (minds and mental states) and neuroscience (brains and brain states).
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