Using research in the classroom: Socio-economic status and stress

sam-wass-photoIn this week’s blog, Dr. Sam Wass from University of East London tells us about his research into socio-economic status and stress, and how this relates to teaching and learning.

What is the focus of your research?

At the moment I am working mainly on my ESRC fellowship, which looks at how the early living environment affects stress and concentration abilities in babies growing up in socio-economically challenged households. We know that children from lower socio-economic backgrounds are more likely to develop mental health problems later in life, and we think that early-life stress might cause this. But we understand very little about what exactly causes stress in infants. The project is looking at two areas – environmental noise (how physically noisy the living environment is) and stress contagion (how our stress levels are influenced by people around us).

What led you to this area of research? 

There is a personal story behind this. A few years ago, my sister wanted to get two of her children into a good primary school that had a small catchment area – so she moved with her partner and her four children into a much smaller flat, that was all they could afford in the area. The effect on the children of moving from a more spacious to a much more cramped living space was, all the family felt, enormous – it seemed to affect their general stress levels, even when they weren’t at home, and their concentration. It was that that got me interested – because there is very little formal research in this area.

Could you summarise your findings?

It’s too early to know what our main findings are – we’re still collecting the data. But, based on other research, it may be that the picture that emerges is more complex than a simple case that ‘stress/noise is bad’. One big theory doing the rounds in developmental psychology at the moment is the orchids/dandelions theory – that some children (‘orchid children’) are more naturally sensitive, which makes them more sensitive to ‘bad’ things, such as background noise, but also makes them more sensitive when interesting/ memorable learning events happen. So being more sensitive is a double-edged sword. It may be that our findings fit in with this theory.

What do you think this means for teachers in the classroom?

I think there is a tonne of useful material for teachers here. First, the idea that the external environment – how noisy, chaotic and cluttered things are – can affect children’s levels of physiological stress – which, in turn, can affect their concentration. Second, the idea that some children might be more sensitive to this than others. There is also the idea of ‘stress contagion’ – that my own levels of physiological stress are affected by the people around me. And finally, the idea that not all stress is bad.

Could you give one tip to teachers, based on your work?

I think – ‘imagine what the world feels like from the child’s point of view’. Children naturally experience more intense mood swings than adults. As adults we have been highly trained at filtering out background distractions – so much so that we hardly notice them sometimes – but children find this much harder. Being a little child often feels like being a speedboat with a very powerful engine and a small rudder – you might know where you want to go but spin off uncontrollably in a different direction. And understanding this can help, I think, in how we interact with young children.

You can find out more about Sam’s work here:


Headteachers talk about educational neuroscience


For the second in our series of headteacher interviews, we are very pleased to introduce Julia Harrington, Head of Queen Anne’s School and Founder of BrainCanDo to share her thoughts on educational neuroscience.

What does educational neuroscience mean to you?

The developments in neuroscience in the last two decades have given us a much improved understanding of the human brain and its functions, albeit the brain is still very much a mystery!  I believe that this greater knowledge and understanding has direct and indirect applications for the educational sector which, after all, is based in the ‘engine room’ of so many young brains, working to help them develop to flourish both in terms of mental health and their learning and development. Not to have a knowledge and understanding of this is not just a missed opportunity, it is arguably at best bad practice and at worst downright negligent!

How do you keep up to date with the latest research?

At BrainCanDo we are involved in active research with our university partners. I also keep up to date through journals, conferences, websites which I seek out on this topic. I would particularly recommend the journal Impact [produced by the Chartered College of Teachers] which is excellent.

How has neuroscience understanding helped in your school?

We have written our own Teacher’s Handbook.  It covers topics such as memory, stress, music and the brain, biological rhythms and flipped learning.   This explains the neuroscience and psychology behind these areas and then gives ideas and guidance on how to apply in the classroom.   Our teachers also conduct their own small scale research through Learning Study Groups, analysing their findings and feeding back to students and staff.

How do you get students and teachers involved?

Firstly through making sure that BrainCanDo is firmly rooted in all of our practices and training for our staff. The Handbook has helped with this, but it is supported by inset training and work around sharing good practice.  The students are also given training throughout the year on different strategies for learning and mental health and how this relates to understanding the brain. This is delivered by our in-house team.  We also talk about brain function at assemblies, tutor sessions etc.

Are there areas where you think the research should focus next?

We are continuing with our work on music and the brain, looking at ‘character’ education and what this actually means and links to brain function/psychological belief systems/emotional contagion and regulation. I would like to see more work on education for adolescents on emotion regulation feeding into positive mental health.

Using research in the classroom – spatial cognition, science and mathematics

This is the first in an exciting new series of CEN blogs, where Dr. Vic Knowland asks researchers to tell us a bit about their work and how it relates to teaching and learning.

This week, Professor Emily Farran from UCL-Institute of Education tells us about her research into spatial cognition, science and mathematics.

cen-blog-emily-501-kb What is the focus of your research? 

I am interested in spatial ability and how it relates to science and mathematics abilities in children. Spatial ability involves being aware of the location and dimensions of objects and their relationships to one another. It is core to everyday living (e.g., giving directions, packing a suitcase), and is also a strong predictor of a person’s science and mathematics abilities, i.e., people who perform well on spatial tasks show strong science and mathematical abilities. Despite the everyday importance of spatial ability, spatial thinking is given little emphasis within the National Curriculum, particularly when compared to the importance placed on literacy skills. Through my research I aim to encourage policy makers and educators to recognise the importance of improving children’s spatial abilities.

What led you to this area of research? 

Originally, the main focus of my research was on spatial cognition in neurodevelopmental disorders. Specifically, I work with groups for whom spatial ability is impaired or atypical (e.g., Williams syndrome, Down syndrome, Cerebral Palsy). I am interested in whether limitations in spatial cognition can be compensated for in these groups, and what the downstream impacts of differences in spatial thinking are on other domains, such as number and mathematics. This kind of knowledge not only informs us about development in these atypical groups, but provides an important window into how individual differences in spatial cognition impact development in the typical population. It also enables us to understand the underlying mechanisms that are necessary to support optimal development of spatial cognition in typical development. Armed with this knowledge, I became interested in spatial cognition in typically developing children. Importantly, spatial ability is very malleable and thus can be trained, with impact not only on spatial ability but on science and mathematics performance. This relationship has predominantly been investigated in adolescents and adults. My research focuses on primary school children.

Could you summarise your findings?

Credit for the bulk of this research goes to Alex Hodgkiss, Katie Gilligan and Su Morris, who are PhD students in my lab ( We have found associations throughout the primary school years between spatial ability and both science and mathematics. For science, mental folding ability (imagining what a piece of paper would look like when folded along pre-specified dotted lines) and spatial scaling ability (mapping two corresponding locations between maps of different sizes) are important spatial skills. This relationship is consistent across the 7 to 11 year old age range. Spatial scaling is also important for mathematics across the 6 to 10 year old age range. We also demonstrated a developmental transition regarding which other spatial skills are important for mathematics. That is, mental rotation (imagining a shape rotating) and disembedding (identifying a smaller shape embedded within a larger image) were important at 6-7 years, but perspective taking (visualising a scene from a different viewpoint) was identified as a significant predictor of mathematics ability for 9-10 year olds. We have also found that different spatial skills are differentially important for subdomains of science (physics, chemistry, maths) and mathematics (geometry, shape, arithmetic). Having established these associations, we are now investigating the impact of training spatial skills using instructional videos, how differences in cognitive style (measured using eye-tracking) impact mathematics performance, the impact of gesture use on science learning and the impact of spatial thinking skills on science reasoning within a taught lesson.

What do you think this means for teachers in the classroom?

Understanding science and mathematics depends heavily on being able to use, understand and co-ordinate models, read diagrams, rearrange formulae, and interpret representations at different scales. At the core of science is an understanding of processes and cause and effect relationships, which are often illustrated through dynamic representations. This learning through and from various kinds of visualisations requires spatial skills. Equally, mathematics requires an understanding of shape, symmetry and numerical relationships all of which require spatial skills. By recognising the spatial elements of science and mathematics tasks, teachers will be in a position to foster the development of these concepts via the use of spatial tools (e.g., diagrams, graphs, spatial language), with positive impact on the learning of science and mathematics abilities.

If you could give one tip to teachers based on your work, what would it be?

Spatialise your teaching. That is, embed spatial thinking within your teaching. Construction toys are important; blocks, for example bolster understanding part/whole relationships, symmetry and measurement. Equally, number lines are a spatial tool that can make abstract concepts like fractions and negative numbers more concrete; they help children to visualise the relationships between values and amounts. Teachers could also teach children how to use maps and diagrams, and direct children to visualise a structure (e.g., the respiratory system) whilst learning from a diagram. Encouraging children to use gesture, sketching and diagrams during problem solving will also enhance their science and mathematical understanding via spatial thinking. Spatial language is also an important tool because it has high communicative value (describing patterns of data on a graph, conveying the location of plant roots relative to the plant stem) and capacity to enhance spatial understanding (words like ‘parallel’ and ‘converging’ succinctly communicate otherwise difficult spatial concepts).  Children’s use of spatial language is influenced by the amount of spatial language that they hear, and is also positively related to their spatial abilities.

Headteachers talk about educational neuroscience

steve-baker-photograph-smallerIn the first of a new series of blogs, we will be hearing from headteachers about their views on educational neuroscience. First up is Steve Baker, Principal of the Aspire Schools Federation and Member of the Learnus Advisory Group.

What does educational neuroscience mean to you?

Educational neuroscience is about developing a better understanding of the development of the brain, and its plasticity, and the underlying mechanisms that shape our cognition and behaviours.  I once heard a professor of psychiatry suggest that trying to understand learning through neuroscience is like trying to understand the plot of East Enders by taking the back off your television set.  I wholeheartedly disagree and believe that although the field of educational neuroscience is relatively new, medical advances and ongoing research will allow us the opportunity to better understand how we can develop our brains, and ultimately shape our understanding of how we learn.

How do you keep up to date with the latest research?

I endeavour to read as much as possible around the subject, including books, articles and published research papers.  In addition, I am incredibly fortunate to be on the advisory board of the think tank Learnus whose vision is to bring together the fields of neuroscience research and practice.  They are currently doing this by developing a community of teachers, psychologists, neuroscientists and academics in order to bring the insights of neuroscience and the learning sciences into the classroom.  I would certainly recommend having a look at their website:

Can you give some examples of how neuroscience understanding has helped you and your school?

We are very fortunate to have been working with Dr Alice Jones Bartoli for a number of years.  Alice is the Director of Unit for School and Family Studies at Goldsmiths, University of London, and is also a member of the Learnus Council; she has supported our efforts to focus on a non-confrontational approach to behaviour modification at my secondary setting, Kilgarth School, which supports young men with Social, Emotional and Mental Health (SEMH) difficulties.  We are also currently working with a clinical psychologist who is undertaking research into the role of limited prosocial emotions on responsiveness to punishment (and reward), and the mediating role of emotional memory in children and young people.

At Gilbrook School (my primary SEMH setting) we are supporting the research of a member of staff with a background in psychology.  He is undertaking an MSc in Children and Young People’s Mental Health and Psychological Practice and his latest literature review has focused on attachment in infancy and developmental well-being.  We have been focusing on developing the use of outdoor space to promote positive mental health and resilience in our children; in May we were used as a best practice case study by the Department for Education for our outstanding mental health work.  We are also currently liaising with Professor Francis McGlone’s team at the University of Liverpool, who are investigating the importance of affective touch in the development of the social brain.

How do you get people involved?

I work with an incredible group of staff who have always been keen to get involved with our research focus and this was celebrated during our latest Ofsted inspection.  In their final report, the inspectors commented on the positive impact of our engagement with research:

“Your professional curiosity and determination to do the best for every child mean that you never rest on your laurels. You and your staff keep up to date with the latest developments, both nationally and internationally. You have established innovative partnerships in international research. Staff research what works for pupils and use this to develop best practice at Gilbrook.”

We have a relatively small number of staff, yet in the last three years we have supported members of the team to undertake further learning and research at both a Master’s and Doctorate level and we use research opportunities to engage staff and support their professional development.

Are there areas where you think research should focus next?

There are a number of key areas of research that I believe would be of huge benefit, including developing our understanding of growth mindsets, mindfulness and how to promote and incentivise good behaviour, instead of using punishment. Indeed, research has shown the importance of developing non-cognitive skills in order to achieve educational success.

There also needs to be a clear drive to ensure that research is made accessible to members of the teaching profession; workload and stress are key issues affecting the profession and we are constantly inundated with new education “silver bullets” and fads.

Is there anything else you would like to say?

I would recommend that people get involved in school-based research themselves and, where possible, keep up to date via social media platforms such as twitter.  There is also a lot of information available at websites such as and

Education and brain plasticity

  • Brain plasticity is a term describing changing connections between neurons and neuronal networks in the brain, based on experiences.
  • Deficits in low-level skills (such as perception and motor abilities), resulting from deprivation in the early years of life, are unlikely to be overcome through brain plasticity.
  • In contrast, the development of high-level skills (such as reading, writing, and mathematics) is not limited to specific, sensitive periods, and can therefore continue to develop over the lifespan.
  • Brain plasticity reduces earliest in sensory and motor domains, and latest in regions associated with higher cognition.


Blog written by Professor Michael Thomas

Brain plasticity was an early pre-occupation of educational neuroscience, perhaps not surprisingly given that education is predicated upon it. Learning can be characterised as the changing and strengthening of neural connections and networks in the brain. The initial focus was on changes in brain plasticity with age and the possible implications for the time at which education should commence and various skills should be taught. But this focus was not inevitable, or perhaps even the most pertinent. It makes as much sense to investigate the different constraints on plasticity that operate in different brain systems – the amount of experience each requires, the optimal schedule, the requirements for consolidation, the rate of forgetting, modulatory factors such as emotional state and stress, and so forth – along with the mapping of these brain systems to the learning of specific academic skills.

Bruer (1997) was highly critical that the research on sensitive periods in brain plasticity in the 1990s was inappropriately and prematurely extended to policy implications, in particular the conclusion that the first 3 years were crucial for a child’s educational outcomes (so-called ‘early years determinism’), which he felt to be erroneous. The neuroscience of the time was mainly based on low-level perceptual and motor skills in animal models, and the impact of early sensory deprivation. The extrapolation of these findings to high-level cognition in humans was far from clear (Howard-Jones, Washbrook & Meadows, 2012) – indeed, age-related molecular constraints on plasticity in perceptual systems do not appear to be found in higher-level association cortex (areas of the cortex which are involved in more complex functions such as recognition, thinking and planning) even in animals (Takesian & Hensch, 2013; see Cooper & Mackey, 2016).

The current view is that there are few lifespan brain constraints on plasticity with respect to high-level cognitive skills, unless these higher skills are reliant on the acquisition of new low-level motor and sensory skills where sensitive periods are found. However, there are other age-related factors which, together, blur direct comparisons of learning speed over age – these include correlated changes in modes of learning with age (e.g., from implicit to explicit), increasing strategic ability to achieve goals while minimising new learning, and changes in motivation. These age-related changes can be exemplified by language learning, whereby the ability to discriminate sounds outside a first language is reduced after the first 6-months of life. This does not prevent the learning of new languages later in life, but adults may require greater amounts of practice to achieve automaticity, and there may be a lower ceiling of ultimate proficiency that can be reached (Thomas, 2012; Knowland & Thomas, 2014).

While the early years represent a period of vulnerability for the long-lasting impact of deprivation and abuse, there is now less emphasis – at least amongst researchers – for their educational importance in cases of typical development. The order of acquisition of knowledge and skills is important, but it seems less likely that evidence from age-related changes in brain plasticity will tightly constrain whendifferent academic skills should be taught. 


Bruer, J. T. (1997). Education and the brain: A bridge too far. Educational Researcher, 26(8), 4-16.

Cooper, E. A., & Mackey, A. P. (2016). Sensory and cognitive plasticity: implications for academic interventions. Current Opinion in Behavioural Science, 10, 21-27.

Knowland, V. C. P., & Thomas, M. S. C. (2014). Educating the adult brain: How the neuroscience of learning can inform educational policy. International Review of Education, 60, 99-122.

Takesian, A. E., & Hensch, T. K. (2013). Balancing Plasticity/Stability Across Brain Development. Progress in Brain Research, 207, 3-34.

Thomas, M. S. C. (2012). Brain plasticity and education. British Journal of Educational Psychology – Monograph Series II: Educational Neuroscience, 8, 142-156.

The nature and nurture of education

Environmental and genetic causes of individual differences in educational achievement

Blog written by Professor Michael Thomas


The nature-nurture issue is well-known amongst teachers: children differ, and some of these differences are due to the children’s nature, some due to the environment they are raised in, and some a combination of children’s different natural reactions to the environments they are raised in.

Gaps in educational achievement between children are a key issue for society, and their causes have been a focus for research in the social sciences. These gaps have spurred educational neuroscience investigations into possible underlying brain mechanisms, with separate work in the areas of environmental influences and genetic mechanisms.


With respect to environmental influences, research has focused on the effects of socioeconomic status (SES), one of the environmental measures showing most predictive power on cognitive and educational outcomes. SES is usually measured by parental levels of education and income. Notably, SES differences in cognitive abilities are already observable when children start school, and tend not to narrow with age (e.g., Hackman et al., 2015), and may even widen. For example, von Stumm and Plomin (2015) reported that in a large sample of almost 15,000 UK children followed from infancy through adolescence, children from low SES families scored on average 6 IQ points lower at age 2 than children from high SES backgrounds but by age 16, this difference had almost tripled. Notably, the differences in cognitive ability in school-age children associated with SES tend to be larger than the effects produced by different schooling (e.g., Walker, Petrill & Plomin, 2005). The greater effects of the home than the school on cognitive ability suggest that educational neuroscience must retain a focus on developmental factors beyond the classroom.

SES as a measure of the environment is only a proxy for the actual experiences of the child and therefore the actual causal mechanisms. These mechanisms may operate along multiple pathways, and those pathways may differ depending both on the absolute level of poverty across countries and the level of inequality. These pathways include prenatal factors, such as maternal diet, smoking, alcohol consumption, and stress; postnatal nurturing factors, such as early caregiver sensitivity; and the richness of postnatal cognitive stimulation (Hackman, Farah & Meaney, 2010; Sheridan & McLaughlin, 2016). Notably, the effects of SES are uneven across cognitive profiles, with relatively greater effects on language development and executive functions, and weaker on visuo-spatial cognition (Farah et al., 2006), although the reasons for this unevenness are unknown.

In a large US sample, Noble et al. (2015) demonstrated differences in structural brain measures of cortical thickness and cortical area correlated with SES measures, in regions that fitted with the cognitive abilities showing largest effects (temporal regions for language, prefrontal regions for executive functions). Investigations of causal mechanisms are compromised by the fact that so many correlated environmental factors are associated with differences in SES (Hackman et al., 2015); but in theory, an understanding of mechanism would suggest most effective points to intervene to alleviate the effects of poverty and deprivation on educational outcomes (Thomas, 2017).


With respect to genetics, work in behaviour genetics has begun to impact on education. Most obviously, evidence points to the heritability of differences in educational achievement. Heritability is defined as the amount of variation in behaviour explained by genetic similarity. Heritability is either inferred on the basis that achievement is more similar the more genetically similar individuals are (e.g., the idea that ability runs in families); or it is measured directly by correlating variation in individual letters of DNA (single nucleotide polymorphisms or SNPs) to educational outcomes in large samples (though the variation in behaviour explained by direct measures of DNA variation is typically much smaller, perhaps only ~10% instead of the ~50% explained by observing patterns that run in families; e.g., Okbay et al., 2016). For example, within the last five years, papers have been published showing that the heritability of educational achievement aged 16 is up to 60%, and that controlling for IQ, it appears to be the same genes that explain variability in different academic disciplines (Krapohl et al., 2014; Rimfeld et al., 2015); that social mobility (measured as children achieving higher educational levels than their parents) is itself around 50% heritable (Ayorech et al., 2017); that, on genetic grounds, there is little evidence that selective schools produce better educational outcomes than non-selective schools (Smith-Woolley et al., 2018); and that educational achievement may be a causal protective factor against Alzheimer’s disease (Zhu et al., 2018).

There is insufficient space here to evaluate these types of claims (see Thomas et al., 2013; Ashbury & Plomin, 2014; Meaburn, in press). However, we can simply note that a genetic perspective on education emphasises that not all differences between children are environmental in origin; but as yet, does not point to specific implications for teaching. Somewhat counter-intuitively, environments that optimise learning will increase the extent to which educational success is heritable. For example, greater heritability is observed in classes with better teachers (Taylor et al., 2010), as it is in affluent families compared to impoverished ones (Turkheimer et al., 2003). This is because heritability acts as an indicator of where limiting factors lie: when better school environments reduce limits on learning, variability between children is more readily explained by their genetic make-up (Asbury, 2015; Thomas, Kovas, Meaburn & Tolmie, 2015). Increasing heritability rates could therefore be a useful indicator of reducing educational inequality.

Effects linked to genes or changes in the brain are not inevitable

The risk with both neuroscience evidence of the effects of poverty on brain development, and of genetic effects on educational achievement, is that these will be construed by educators as ‘deterministic’ or inevitable outcomes. Yet many cognitive effects of poverty can be ameliorated by intervention, such as training executive functions, because the brain is plastic (Neville et al., 2013); and previously measured genetic effects may disappear when environments are altered. Indeed, the future potential of genetics would be to predict the best, tailored environment for each child to reach his or her genetic potential. However, currently, genetic studies are focused on maximising predictive power (such as by the use of polygenic risk scores, which combine the effects of all measured DNA variation to predict differences in behaviour) – rather than informing a neuroscientific understanding of the brain mechanisms of learning that would enable such tailoring of environments.



Asbury, K., & Plomin, R. (2014). G is for Genes: The Impact of Genetics on Education and Achievement. Oxford, UK: Wiley Blackwell.

Ayorech, Z., Krapohl, E., Plomin, R., & von Stumm, S. (2017). Genetic Influence on Intergenerational Educational Attainment      . Psychological Science,28(9), 1302 – 1310.

Farah, M. J., Shera, D. M., Savage, J. H., Betancourt, L., Giannetta, J. M., Brodsky, N. L., …  & Hurt, H. (2006). Childhood poverty: Specific associations with neurocognitive development. Brain Research, 1110, 166 –174.

Hackman D.A., Gallop, R., Evans, G.W. & Farah, M.J. (2015). Socioeconomic status and executive function: Developmental trajectories and mediation. Developmental Science, 18(5), 686–702.

Hackman, D.A., Farah, M.J. & Meaney, M.J. (2010). Socioeconomic status and the brain. Nature Reviews Neuroscience, 11, 651– 659.

Meaburn, E., (in press). Genetics and education. In: M. S. C. Thomas, D. Mareschal, & I. Dumontheil (Eds.), Educational Neuroscience: Development Across the Lifespan. London, UK: Routledge.

Noble, K.G., Houston, S.M., Brito, N.H. et al. (2015). Family income, parental education and brain structure in children and adolescents. Nature Neuroscience, 18, 773–778.

Okbay, A., Beauchamp, J. P., Fontana, M. A., Lee, J. J., Pers, T. H., Rietveld, C. A. et al. (2016). Genome-wide association study identifies 74 loci associated with educational attainment. Nature, 533, 539–542.

Rimfeld, K., Kovas, Y., Dale, P. S., & Plomin, R. (2015). Pleiotropy across academic subjects at the end of compulsory education. Scientific Reports, 5, 11713

Smith-Woolley, E., Pingault, J-B., Selzam, S., Rimfeld, K., … Plomin, R. (2018). Differences in exam performance between pupils attending selective and non-selective schools mirror the genetic differences between them. npjScience of Learning, 3, Article number: 3 (2018).

Thomas, M. S. C. (2017). A scientific strategy for life chances. The Psychologist, 30, 22-26.

Thomas, M. S. C., Kovas, Y., Meaburn, E., & Tolmie, A. (2015). What can the study of genetics offer to educators? Mind, Brain & Education, 9(2), 72-80.

von Stumm, S. & Plomin, R. (2015). Socioeconomic status and the growth of intelligence from infancy through adolescence. Intelligence, 48, 30–36.

Walker, S. O., Petrill, S. A., & Plomin, R. A. (2005). A genetically sensitive investigation of the effects of the school environment and socioeconomic status on academic achievement in seven-year-olds. Educational Psychology, 25(1), 55-73.

Using analogies in the classroom

apples-and-orangesBy Matt Slocombe

In my talk at the Centre for Educational Neuroscience, I discussed my research looking at how children learn using analogies. Using analogies can be a very powerful teaching and learning strategy in the classroom since analogies allow children to rapidly learn new knowledge by seeing how something new is similar to something they already know about. In a biology lesson, they might hear the analogy ‘mitochondria are the power source for a cell’. By using this analogy, children can use their knowledge of the causal relationships between something they know about – perhaps a battery and a mobile phone – to quickly understand the causal relationships between mitochondria and a biological cell.

The study I discussed investigated how the strength of children’s existing knowledge affects their ability to use it in an analogy. To use the mitochondria-power source example, the results indicate that just knowing about power sources is not enough; children need a strong abstract concept of power source to successfully make the analogy. When presented with the mitochondria-power source analogy, children with weaker abstract concepts may well be thinking of irrelevant features of a concrete example (such as how a battery looks or the sound of an engine) rather than the necessary abstract power source concept.

For teachers, one way to help children with weaker abstract concepts use analogies may be to briefly discuss the existing knowledge you want to use in an analogy first. For example, discussing the functional role of batteries in phones and engines in cars prior to introducing the mitochondria-power source analogy would highlight the relevant causal features of power sources necessary for understanding the functional role of mitochondria in cells.


For more information or to stay up to date with Matt’s research, please see his website at  or follow him on twitter @matthewslocombe

Stress and learning in children: evidence from neuroscience and relevance for teachers

In yesterday’s CEN seminar, Dr Sue Whiting talked about the complexities of the human stress response. She explained how each individual’s stress response – the strength and duration of each person’s response, their base stress levels, what constitutes a ‘stressor’ – is highly variable, presenting challenges for teachers to pitch lessons in a way that will be effective for all learners. At the end of her talk, Sue gave some tips for teachers which might help moderate the effects of children vulnerable to high levels of stress:

Supervised breakfast clubs could potentially serve a dual purpose: in addition to providing good nutrition, they could also allow a longer period of time for delayed cortisol effects, arising from stressors outside the school environment, to dissipate.
Deep diaphragmatic breathing, which appears to balance the nervous system by stimulating the parasympathetic system, sometimes characterised as the ‘rest and digest’ system. This could be used with whole classes on a regular basis to help control all the children’s stress levels.

If teachers learn to recognise signs that children are beginning to be overwhelmed, then they could reassure them and take some of the pressure away by reducing the complexity of a task, particularly reducing the load on working memory.

For some children, rewarding effort may help. Others may respond to adopting a mindset which repositions stress as an enhancing agent. Some children find it helpful simply to say ‘I am excited’, as a way of recognising their stress and casting it as something positive.

Simple interventions to capture interest can improve reading comprehension

In our last seminar, Lisa Fridkin and Jane Hurry presented their work investigating situational interest in children, asking whether improving intrinsic motivation through simple manipulations such as the arrival of a novel person in the classroom or being offered (apparent) choice in a reading book, could improve reading comprehension. Below, Lisa talks a bit more about the research:


Situational interest (SI) is described as the first stage of interest development (see Hidi & Renninger, 2006; 2011) and is potentially of high value to practitioners because it is an intrinsic motivator that can be externally manipulated. It is theorised to raise attention, effort and enjoyment in a task or activity and act as a forerunner to personal interest.

A series of three experimental studies were conducted to investigate the effects of three potential triggers of SI on reading comprehension performance and reported task enjoyment with children aged 8-9 years old. Interaction effects for gender and reading ability were also investigated. Approx. 100 children participated in each study which used a repeated measures, cross-over design, and the same central materials (two short stories, comprehension questions, enjoyment questionnaire).

Study 1 investigated choice, offering children a perceived but meaningful choice in storybook (control condition: allocated story); Study 2 investigated novelty where a story prologue was read aloud by a visitor (control condition: task administered by class teacher, without the prologue read aloud; Study 3 also investigated novelty, through non-textual features – scratch and sniff stickers interspersed in the text, (control condition: no stickers).

All three studies found significant effects on reading comprehension performance (medium to large effect sizes) and on reported task enjoyment (small effect sizes), suggesting that for this age group, these triggers are effective in changing the way the children interact with a reading comprehension task. Effects by gender were found for Study 3 only, where girls achieved higher scores on the reading comprehension task compared to boys. No effects were found by reading ability.

These results suggest that quite slight manipulations of a task can have a relatively large and immediate impact on comprehension task performance and enjoyment and suggest that SI may signal an effective way to introduce intrinsic motivation in the classroom. There is emerging evidence linking motivation to reward circuitry, indicating that our understanding of these processes could be supported with further research.

Susanne de Mooij talks about the potential for personalised learning in an online maths game for children

The examples below show how the eye and mouse tracking work with a real example.

Susanne says, “While answering a maths question, we measure where the child looks on the screen and how they move their mouse, as an indirect measure of their thought process before making the choice.
The figures display the eye (black line) and mouse tracking (orange line) of two opposite strategies.
The first figure (6+6) suggests mental calculation where the child’s eyes have first fixated on the question, followed directly after by fixating on the correct answer. In the second example (7×4), the child alternates between the question and several possible answer options, before ultimately giving a wrong answer.
The information that can be gleaned from such examples is clearly much more detailed than simply whether a child got a particular question correct or incorrect.”example1_strategyuse_mouseeyemovements example2_strategyuse_mouseeyemovements