Cognitive Science in Education: Achieving an overview
One of the difficulties in dealing with emerging fields is the inevitable delay between the initial burst of activity that characterises any rapid advance in knowledge and the moment when the dust begins to settle and some clarity emerges in the guise of broad themes that are helpful to understanding the field and also to making sense of the continuing flood of new findings.
One particular useful but very coarse-grained distinction lies in the difference between two prominent traditions currently driving the bridges being built between research and the classroom. There is the approach that focuses largely on the role of memory, such as the Deans for Impact Science of Learning approach with its association with Rosenshine’s principles; cognitive load theory; blocked/spaced, interleaved learning and retrieval practice; and the learning-as-acquisition paradigm, which is the model favoured by Ofsted in its research reviews. This is the model that underpins the coherent curriculum and finds expression in the assertion that elaborations of Bernstein’s models of conceptual frameworks – vertical/ horizontal, hierarchical/layered – in some way match the cognitive architecture of learning. This approach appears to be welcomed at secondary level and even KS2 but, in my opinion, it lacks explanatory power as a theory of learning when considered with very young children.
An approach that makes more sense at all stages of learning is provided by the field of developmental cognitive neuroscience which pays attention to the crucial aspects of attention and emotional regulation in directing learning and provides a much more convincing picture of how metacognition emerges. The work of Dehaene, S., Johnson, M.H., Karmiloff-Smith, A., Goswami, U. and Immordino-Yang, M.H. are useful starting points in this area that is challenging to the non-scientist but nevertheless provides a comprehensive theory that reflects the complexity we recognise in the learning environment, particularly in the social domain, and takes the nature/nurture debate to a whole new, informed and interesting level.
Another very broad but useful distinction is between those ideas that arise from a standard linear cognition orthodoxy of input-process-output and those that are underpinned by a radical non-linear cognition of dynamic state-spaces, perturbations and arrestor states. The former is largely associated with early computer science where symbolic representations of reality are algorithmically operated on by a brain sealed off from the world by the sensory buffer, in order to work out the optimum meaning or course of action. The latter arises from more recent work on connectionist learning – deep neural networks, self-organising intelligence and AI – which offers powerful explanations of how complexity develops in the growing brain. Cognitive Load Theory, for example, appears to be informed by a standard cognition model whereas Embodied Cognition (the distribution of thinking across mind, body and environment) would be a good example of radical cognition.
PG students on placement need portable mental models to work with and when mentoring, I have found that Howard-Jones et al (2018) offers a really useful three-part metaphor – engage, build, consolidate – with the appropriate caution that the brain does not work in a linear, staged way and so the model is not a blueprint for lesson planning. Also, the article is very clear on the need for teachers to “critically theorise” any research findings for their own circumstances and again this has been useful in encouraging ATs to think beyond the positivist illusion of silver bullets and recipes for teaching. Of equal practical value is Dehaene’s (2020) concept of the four pillars of learning – attention, active engagement, error feedback and consolidation.
In first introducing students to these ideas – and for our own confidence in the material – it is helpful to consider where cognitive science sits in relation to the theories of learning with which we are more familiar. In this respect, I can think of no better opening than Goswami’s (2014) introduction to the chapter on Theories of Cognitive Development in The Wiley Blackwell Handbook of Childhood Cognitive Development which briefly discusses what is extant in the theories of Piaget and Vygotsky before going on to highlight how developments in cognitive science are changing the way we think about childhood development.
Finally, as Andy Clark (2011) points out, the quest is always for knowledge that is grounded in the very best science we can achieve but that knowledge remains amoral, inert and potentially misleading until it is made philosophically significant for the purpose for which we intend it. What is perhaps meant here is that the glittering knowledge from neuroscience needs to be made to add to the human project by presenting it in its relationship to other ideas about purpose, moral truth, individuality and society.
Clark, A. (2008;2011;). Supersizing the Mind: Embodiment, Action, and Cognitive Extension. Oxford University Press.
Dehaene, S. (2020). How We Learn: The new science of education and the brain. Allen Lane.
Goswami, U. C. (2010;2011;). The Wiley-Blackwell handbook of childhood cognitive development (2nd;2;Second; ed., Vol. 32). Wiley-Blackwell.
Howard-Jones, P., Ioannou, K. & Bailey, R., et al. (2018) Applying the science of learning in the classroom. Impact the journal of the Chartered College of Teaching 2: 9–12.
edutaytion 