We are a University-led research centre, combining the expertise of researchers in child development, neuroscience, and education at three world leading universities, Birkbeck, UCL Institute of Education, and University College London.
Dr Alex Hodgkiss from Oxford University’s Department of Education, talked about his recent research looking at whether spatial cognition is a crucial ingredient in the recipe for success in science – at primary school and beyond. See his short video summary as well as links to his papers and other resources below.
Dr Alex Hodgkiss - Vimeo
You can read more about the research in these papers:
In this week’s seminar, Christian Bokhove, Associate Professor in Mathematics Education at Southampton University talked about his recent research on geometry learning. He took as his starting point the question of why Asian countries typically score higher in PISA-type maths comparisons than European countries. Luckily for anyone who missed it, the slides of his talk are all available on slideshare here.
As part of the project, he and his partner team in Japan created a set of geometry learning materials which you can have a look at here.
Prof. Chloë Marshall led a discussion of two papers recently published by Laurence Leonard and his colleagues in the Journal of Speech Language and Hearing Research. They investigated some of the factors that can enhance word learning in children with developmental language disorder (DLD). Paper 1 investigated whether children with DLD, and also typically developing children, learnt words better when they were required to actively retrieve them, rather than just studying them. The authors found that active retrieval on repeated occasions was indeed more effective than repeated study, both when children were tested immediately on those words and when they were tested a week later.
Paper 2 developed this line of research further by comparing two different retrieval schedules – an immediate retrieval schedule, and an interleaved retrieval schedule. The interleaved retrieval schedule was more effective at supporting children with DLD and typically developing children to learn words. Interestingly, the study in paper 2 also incorporated event-related potentials (ERPs) whose data revealed that words were learnt better in the interleaved retrieval condition, supporting the behavioural data.
The papers generated lots of interesting discussion about (1) how neuroimaging methods could be used to support behavioural methods in intervention studies, (2) what the neurological mechanisms underlying the advantage for interleaved retrieval might be, and (3) how far interleaved retrieval might be incorporated into the teaching of vocabulary across all curriculum areas and for all children. We also discussed how interleaved retrieval might be used beyond teaching vocabulary, for example, as here, in maths.
Find out more about interleaving from the excellent Learning Scientists here and you can follow Prof Marshall on Twitter.
In this week’s seminar, Prof Michael Thomas discussed the background to and the findings of a US initiative set up to consider the possibility of transformative changes to education.
The Chan Zuckerberg Initiative (CZI) and the Bill & Melinda Gates Foundation (BMGF) are jointly exploring whether transformative education solutions can be developed through an accelerated research and development (R&D) effort. The approach would bring together interdisciplinary teams from education research, human development research, learning measurement, evidence-based technology-enhanced practice, professional development, neuroscience, and other fields.
In May 2018, the two philanthropic organizations came together to seek new approaches from practitioners, researchers, and the public to a set of education challenges with enormous implications for the success of all students – and especially those who have faced early trauma or learning challenges. They put out a ‘Request for Information’ (RFI) from a wide range of research, educational, policy, non-profit and business groups to seek information for innovative strategies to help address three pressing challenges they saw:
■Writing: Preparing all high school graduates for the type of nonfiction writing demanded in college and the workplace by developing the necessary habits, skills, and strategies;
■Maths: Preparing all students to deeply understand and apply mathematical skills and knowledge and related mindsets;
■Executive Functions: Improving the ability of all students to think flexibly, wrestle with multiple ideas, and manage their thoughts and actions
The main findings in these areas were:
The RFI submissions in writing focused on three big areas:
1. Writing for the real world:These approaches provide students with opportunities to engage in writing that more closely mirror the demands of college and the workplace. These range from a partnership with a science museum to promote real-world science writing to developing a community-based peer coaching model.
2. Getting students more feedback:Many of these submissions focus on developing students’ writing skills or providing feedback to students from a diverse group of readers, including outside experts such as journalists, to complement classroom teachers.
3. Next generation writing environments:A number of submissions focus on how to put technology at the disposal of teachers to help personalize writing instruction. These range from a tool to capture qualitative data from students’ drafts to help teachers see patterns in student writing, to an online learning environment that would make visible students’ contributions to peer feedback, so that teachers would know when to coach the class or an individual learner.
The RFI submissions in mathematics focused on four key topics:
1. Practice and feedback: These approaches provide students with rich opportunities to engage in deliberate practice and receive actionable feedback that leads to deep mastery of foundational math knowledge and concepts. Many of them employ digital games, intelligent tutoring, and technology-based platforms to tailor learning experiences for individual students.
2. Novel instruction and experiential learning:These approaches provide students with the opportunity to discuss real-world math problems of interest to them to help develop a positive math identity. One proposal invites students to consider the real-world and ethical implications of math questions.
3. Improved measurement systems: These solutions propose to narrow the gap between assessment and instruction by providing richer indicators of student progress.
4. Empowered teachers: These submissions propose using technologies that deliver real-time information on student learning to teachers with recommendations for adjusting instruction. The intent is to support teachers to differentiate their approaches for students with a wide range of proficiency levels, as well as to enable teachers to try new pedagogical strategies
The RFI submissions in this area fell into three broad buckets:
1. Measures of executive functions: There were promising approaches to developing better measures of executive functions across basic and applied research. Such measures are needed to understand which interventions best target individual students’ needs and to help teachers make informed judgments. Some submissions offer tools to help teachers understand and support students’ development of executive functions, and to provide teachers with professional development in this area.
2. Interventions to build executive functions:These submissions include ideas for scaling some existing products as well as for basic research. They range from low-cost, targeted strategies that represent the essential “active ingredients” in effective programs to develop students’ social, emotional, and cognitive skills, to efforts to build adults’ knowledge and development of executive functions, which research has found is strongly associated with children’s development of such skills.
3. Tools and techniques to support programs that develop executive functions:These ideas would support and buttress existing efforts to develop executive functions
The full findings are available in this report. More information on the background to the RFI can be found here. And their website also has useful resources for teachers and educators which are regularly updated.
Susannne De Mooj, PhD student at the Centre for Brain and Cognitive Development, tells us about the work she has been doing in collaboration with Dutch educational company, Oefenweb, using data from over 300,000 individuals using the company’s maths and language e-learning apps. Online learning environments have the ability to continuously adapt and accommodate differences between learners, and changes within individual learners over time. Susanne is investigating innovative ways these apps may be tailored to enhance different aspects of the online learning experience.
Learning is an inconceivably complex system, as many elements interact with each other; general mental ability, prior knowledge, learning styles, personality characteristics, motivation, anxiety, and many more. These interactions over time result in extensive individual differences in the cognitive trajectory, making it difficult for education and research to optimise learning for everyone. Online learning environments can have a positive impact on education and individual students in general by providing individualized computer adaptive practice and monitoring tools. Tracking the individual development of both accuracy and response time can shed some new light on the complexity of learning, which is illustrated below by three individual time series of children practicing single mathematical problems (i.e. 1 + 5) for a long period (adapted from Brinkhuis et al., 2018). For example, in the upper and low panel of this figure you see a three-stage pattern, moving from mainly incorrect response, to fast correct responses. On the other hand, the middle panel shows a child who does not learn 3 + 4, while practicing this item for 61 times, with some correct responses alternated with errors. The highly variable patterns within and between the learners shows that tailoring and monitoring their learning experience is essential.
Cognitive profile and time perception. Any learning environment (offline or online) creates a certain cognitive load particularly to attention and working memory. This load can be increased through the presence of irrelevant objects/information (e.g. gamified sounds, flashing objects, alternative answer options), but also through external stimuli such as worried thoughts about performance. These stressors can either drive children to use more efficient strategies or it could compete with the attention necessary to learn new skills. One particular stressor used in a lot of game-based learning platforms and experiments, is time pressure. In one of our smaller sample studies we found that the presence of the time pressure on the screen has an impact on maths performance. Critically, we found that an individual’s ability to inhibit irrelevant information is key to whether this has an impact on the learning experience. Eye movement patterns in this study also showed that whether time pressure is visible or not in the learning environment in combination with their cognitive profile affects where and how much the children attend to. Although bigger studies are needed, time perception and individual cognitive profile are features that we might need to consider in adaptive frameworks.
Mouse tracking. In most educational tools, the most widely used indicators of learning are response time and accuracy, as shown in the individual time series figure. Although these measurements are well-suited to indicate the overall performance, they cannot be used as continuous measures of the underlying cognitive process. A promising online measure designed to track the timing of evolving mental processes is mouse tracking (Freeman, Dale, & Farmer, 2011; Song & Nakayama, 2009; Spivey, Grosjean, & Knoblich, 2005). For this paradigm, the speed and movement of a mouse point as well as where it is placed on the screen is tracked to see how much attention the user pays to certain stimuli. Mouse tracking is becoming popular on commercials website as a way to gain insight into behaviour, however it is also available and potentially useful for researchers, see for example the recent implementation in the online experiment builder Gorilla. One of our current studies tracks the mouse movements of 100.000 active users for a month while practicing arithmetic skills. Specifically, we are interested in the attraction towards alternative answer options, not selected as response, to get a better understanding of the user’s possible misconceptions. The aim of this online technology-based assessment of the misconceptions is to adapt feedback and instruction on an individual basis.
Large scale measure of (dis)engagement.
The way a student engages in learning is essential to their experience. Engagement is mostly defined as attentional and emotional involvement with a task (Christenson, Reschly, & Wylie, 2012). However engagement is not stable, but fluctuates throughout the learning experience. Different measures are used to assess initial but also sustained engagement, such as self-report questionnaires, heart rate changes, pupil dilation and emotion detection. For large scale, online detection, head movement has been proposed as an estimate of the dynamics of the user’s attentional state. Generally, studies find that head size, head posture and head position successfully capture engagement, such that when the person is deeply engaged, movement is less and when distracted/bored more head movement follows. To measure engagement within an online learning platform or in typical psychological experiments, we use an automated detection algorithm where we track (multiple) faces with a simple webcam during the learning experience or afterwards from videos. Our current study (N=83 children, 8-12 years old) investigates how head movement relates to both emotional and cognitive engagement and whether we can predict whether children are in the ‘flow’ or are about to disengage from the task. Hopefully, this will enable us to prevent high dropouts and adapt the presentation and content to the individual learner’s state.
Alex Black has been a science teacher for over 30 years; for many of those he has been using the CASE teaching tools developed using Piaget’s theories.
Alex Black - Vimeo
His presentation described how researchers Shayer and Adey identified the difficulties that children learning sciences experienced, particularly 11 to 16-year-olds. The researchers wanted to develop an evidenced-based theory of science learning and teaching using Piaget’s model of developmental stages. This involved really getting to grips with students’ thinking and their understanding of the formal operational schemata essential for learning abstract scientific principles in the curriculum. The researchers developed and validated instruments for testing students’ understanding with a huge nationwide survey of 11,000 school students and were alarmed by the low proportion who had reached formal operational thinking by the age of 16. This led them to explore two strategies:
The first was to develop the CAT (Curriculum Analysis Taxonomy) to allow sequencing and matching of curriculum objectives to the cognitive readiness of the students. The second was to develop and validate a programme to accelerate the movement of students from concrete to formal thinking. The ideas of Piaget, Vygotsky and Feuerstein were incorporated into the teaching methodology and teacher training which led to the Cognitive Acceleration through Science Education (CASE) and later CAME in Mathematics with students in Year 7 and 8.
These programmes have since been extended across wider age ranges and put into practice in Finland, Pakistan, Israel, USA, Ireland, Australia, and Tonga. Further, the pedagogy has been extended to English as well as to more generic programmes such as Learn to Think in China.
Educational Neuroscience (EN) is still a fledging field, with plenty of critics. Director of CEN, Professor Michael Thomas takes on the naysayers and addresses their concerns in his latest commentary for Current Directions in Psychological Science. Below, he gives us a little taster of his reply…
“The challenge in translating neural insights in learning mechanism into practical implications, can only be done via a well supported dialogue – classroom ready neuroscience not likely to ever exist. Critics generally say that either this can’t be done (perhaps individuals resistant to interdisciplinary research) or they muddy the waters by complaining of neuromyths or the dubious merits of commercial ‘brain training’ packages.
There are two main pathways via which neuroscience can interact with education: either directly or indirectly via psychology. The direct route appeals to brain health, viewing the brain has a biological organ with certain metabolic needs (nutrition, energy), response to stress hormones, or impacted by environmental pollution (air, noise). Here goal is to try to ensure that children’s brains are in the best condition for learning when they enter classroom, no need for psychology.
The indirect route argues that the psychology of learning will make greater progress when it takes account of the mechanisms the brain has to support learning. Some of these advances concern specific domains, such as reading or maths, and the current focus is on identifying core skills required for academic disciplines, which may be trainable and/or limiting factors on performance (e.g., maths, recognition of number symbols, representations of numerosity and manipulation of quantities, spatial abilities, and knowledge of principles and procedures, which are dealt with by separate interacting brain areas).
Brain evidence supports the idea that maths is many things in the brain. Other areas of focus in the indirect route are executive functions, social cognition, and the effect of emotions on learning; the specific developmental changes that take place in adolescence; the causes of developmental deficits and what these mean for Special Educational Needs; age-related changes in learning mechanisms and implications for adult learning; the genetic and environmental factors producing individual differences in learning ability and educational outcome; and the quest for activities that produces general improvements in intelligence (such as, meditation, or learning a musical instrument) – a quest that is ongoing but as yet produced few great innovations.
The future of EN involves addressing some challenges (how to improve quality of dialogue of teachers, psychologists, educators); answering some questions (identity crisis: should Educational Neuroscience be a basic science of phenomena relevant to education or intrinsically translational?); and addressing a conundrum (how to advise policymakers before a solid, convergent, evidence base exists). EN needs to encourage evidence-informed policymaking. It needs to avoid overselling the evidence but underselling the importance of science. But its main goal is to furnish teachers with new tools and insights into learning, and the factors that affect it, that will be useful in the classroom. The reality may be that large education gains are available, but only by combining many small improvements, each of which must be separately identified and validated.”
We are delighted to introduce William Emeny, Curriculum Leader and Head of Mathematics at Wyvern College in Southampton. William was the winner of the Pearson Teaching Awards ‘Teacher of the year in a secondary school’ in 2017. He has authored many publications including The Magic of Pineapples and has a wonderful maths blog. We are very pleased to hear his views on educational research. Welcome William.
How do you stay up to date with the latest education research?
I use the Research Gate website regularly, following the researchers and topics that I am particularly interested in so that I receive email notifications each time there are new relevant publications. I also download papers from the university bio web pages of researchers I am interested in [Note from editor: academic researchers are invariably happy to send research publications if you email them]. Furthermore, I read relevant books on cognitive science, evidence-based teaching etc.
Is it important to you whether the research uses particular methods?
I think there are a number of things which make research useful for teachers and methodology is certainly one of them. My view is that ideally there needs to be a combination of lab-based and classroom-based research.
The lab-based research should follow rigorous experimental design principles (controls, independent and dependent variables, avoiding bias, significance testing etc) to illustrate the impact of specific interventions. Classroom-based research should follow as good experimental design principles as possible without overly compromising the ecological validity benefits, e.g. ensuring the methods of delivery are sustainable in regular lessons in real-world schools etc. There are trade-offs between scientific rigour in experimental design and ecological validity when it comes to classroom-based research, but I see it as essential and complementary to the lab-based work.
It is the classroom-based research which helps teachers translate concepts from cognitive and neuroscience into classroom-based practical teaching strategies. Classroom-based research is also important for showing whether observed principles under controlled conditions in a psychology lab are resilient enough to have an impact in a school classroom environment!
Could you tell us how research has influenced your teaching?
There are two main areas whereby research has influenced my teaching. Firstly, I am very grateful to John Hattie for his ‘Visible Learning’ meta-analysis work in which he meticulously compiled effect size summaries of so many different influences which impact on student outcomes. After reading this work, I adopted Hattie’s “Know thy impact” mantra as much as possible in my teaching. A teacher’s most precious commodity is their time and it is essential that we focus our efforts on things which have the greatest impact on our students’ outcomes. By systematically and rigorously evaluating the impact of our teaching approaches, we can make informed decisions about how to teach most impactfully. Hattie’s “Know thy impact” mantra has led to me take an evaluative approach to any changes I make to my teaching practice. If I’m going to make a change, I first think about how I am going to measure and evaluate the impact the change has (or does not have!). This avoids me going round in circles, trying things multiple times because I don’t know whether they were impactful or not.
Secondly, the research by the Bjorks, Roediger, Rohrer, Karpicke on retrieval, spacing and interleaving effects transformed my practice in recent years. I use retrieval-based teaching strategies regularly in lessons rather than getting students to re-read material. I realised the importance of planning for retention and transfer of learning, not just students’ understanding during first-teaching of an idea. I have built spacing and interleaving strategies into my teaching on a regular, habitual basis and have consequently measured considerable improvements in students’ outcomes.
Could you describe a research-informed idea that you feel has had a positive impact in your classroom?
I implemented distributed (spaced) practice into my teaching by ensuring that once an idea was first taught, I then deliberately planned in further practice opportunities on that topic in multiple future lessons. I also ensured further spaced practice opportunities by deliberately delaying end of unit assessments so they occurred 3 weeks after finishing teaching a topic.
Every maths teacher has experienced students understanding topics when they are taught during lessons, but then failing to remember them later. Learning is as much about building retention of knowledge as it is about acquiring the knowledge in the first place. Research into the Spacing Effect is very robust and the strategies I describe above were one interpretation I made of how to put the Spacing Effect into practice in my classroom.
The impact has been significant with students’ summative assessment scores rising at least twice the previous rate, on average. They are remembering more of what is taught as they go, rather than getting to the end of the course and needing to be retaught so much content.
What do you think researchers should focus on next (i.e. what are the gaps in our understanding)?
The body of research on the Retrieval, Spacing and Interleaving Effects is considerable, but in general it is lab-based studies. There are many challenges that teachers face in order to translate lab-based observed effects into practical sustainable teaching strategies in real-world classrooms. For example, we know we should space out the practice students get on maths problems in order to boost their retention, but what would a good spacing interval be? How many times should they revisit a topic? Do some students need more revisits than others before their learning is retained? Should I space exercises out right from the start or is it OK for students to do some massed practice of a single topic at the beginning of learning that topic? How many exercises should they complete in each practice sessions? Does the number of exercises vary with different types of content? How can I measure whether this approach is working?
These questions cannot be answered with lab-based research; we need classroom-based research that focuses on different approaches to implementing these ideas and measuring their relative impact. Effective classroom-based studies can then be used as case studies for teachers to learn from and to see directly how they can implement these approaches in their own classrooms.
Do you have any suggestions for how communication and collaboration could be improved between teachers and education researchers?
Yes, certainly! Firstly, I believe it is important that people ‘with a foot’ in both the academic and school worlds are identified and empowered to set up collaborative relationships. These could be teachers who are keen to learn experimental methodologies etc and want to conduct classroom-based research, or it could be educational researchers with a particular interest in understanding how to implement impactful practice in real-world classrooms. These people need skillsets and credibility ‘in both camps’, i.e. some teaching experience coupled with some post-graduate training in experimental methodologies. Let’s call them “Teacher-Researchers”. They could talk both the language of the academic and the school-based worlds and be credible and relatable to both teachers and researchers.
The next step would be to empower the Teacher-Researchers with support from Educational Researchers in terms of designing their studies, and from schools who will allow time and resource to conduct the studies in their classrooms. Success hinges on relationships and the Teacher-Researchers need time (and funding) in order to develop and sustain these relationships so they are genuinely mutually beneficial.
The Teacher-Researchers could improve communication in both directions by sharing with Educational Researchers the realities, challenges and opportunities of what is possible in real-world classrooms through the eyes of teachers, and then with the teachers important findings from the academic world about potential effective practices and how to evaluate impact rigorously through the eyes of the Educational Researchers. The Teacher-Researchers are the interface between both worlds with experience and understanding of both.
On a personal note, I intend to focus my career on the Teacher-Researcher role. It doesn’t exist, to my knowledge, yet. I am focusing at the moment on trying to gain research funding to allow me time to adopt this role on a part-time basis and to then demonstrate how impactful collaboration could result from it.
In this week’s excerpt from How the brain works we look at the central position of other people in the design of our brains. A growing body of research shows how, from very early infancy, even from birth, our brains are designed to recognise and give priority to social rather than non-social signals. Our ‘social brains’ are also key to understanding the prized human ability to communicate with language. We will go on to consider language and the other special human gizmos which make us, from a species point of view, unique.
As ever, if you want to binge and jump ahead, you can. Start here
People are a priority
A lot of what concerns the brain is other people.
Humans are social primates. Like gorillas and chimpanzees, we live in groups. There are families, friends, enemies, who’s in who’s out, who’s the boss. Social primates have the largest cortex relative to their body size across mammals. Humans have the largest cortex of all mammals, relative to the size of their brains. Across social primates, the larger the social group in which the primate lives, the larger its species’ cortex. This suggests that we have a big cortex to deal with the complications of interacting with the other members of the social group, be they partners, family members, friends, or rivals. Who did what to whom? Who knows about it? What should I do about that?
Anyone who has spent Christmas with their extended family will be unsurprised by this.
The visual system is also tuned to recognise movement that comes from people rather than objects (so-called ‘biological’ motion), including the gestures people make when they communicate. Multiple aspects of sensory information (form, location, motion) are brought together to allow us to recognise other people from different angles, in various places, and while they are in motion. The auditory system has specialised pathways for processing human speech sounds separate from other environmental sounds. The motor system allows us to speak to other people, to hug them, wrestle with them: all social motor actions. The limbic system generates emotions around social interactions, be they the bonding of child to parent, the approach–avoid decisions around possible friends and enemies, attraction, maintenance of personal space and defence of resources and territory.
‘How does Jonny tend to behave? Where am I compared to Jonny in the social hierarchy?’
More complex systems allow us to verbalise our thoughts, emotions and intentions, as well as remember factual knowledge of actors in our social group. For example, the front of the temporal lobe develops social scripts through experience – who tends to do what to whom and how does that feel? And factual knowledge of actors in the social group – what do I think of Jonny and what does Jonny think of me? How does Jonny tend to behave? Where am I compared to Jonny in the social hierarchy? (Hey, I think I’m way cooler.)
As we grow up, we create links between different types of knowledge, experiences and actions. For example, the body sensation (or ‘somato-sensory’) system can detect needs and arousal levels in our bodies, such as thirst and excitement. We link the feeling of thirst to the intention of drinking and the action of picking up a bottle. So, too, in our interaction with other people. We learn social scripts, such as the custom that when you meet a new person you introduce yourself, try to remember their name, shake their hand, and ask how they are. You’re in France, do you greet with a kiss on one cheek or two cheeks? Isn’t it awkward when you get it wrong?
Putting these types of knowledge together, we can guess what other people may be feeling and what they will do next, based on our own experience. This is called mindreading or mentalising. If we see someone grabbing a bottle, the neurons that respond to seeing a bottle and those involved in the action of picking up a bottle will activate in our own brain: it doesn’t quite trigger the action itself but it helps us figure out why the person might be making that action: they’re thirsty.
Similar systems allow us to empathise with the feelings of others. We may link certain actions and facial expressions with, say, sadness in ourselves (crying, walking slowly). When we see others crying, we feel sad. We flinch when we see others in physical pain.
‘We only feel other people’s pain if we like them’
But even here, frontal brain systems come into play, dosing empathy with context. We only feel other people’s pain if we like them. The frontal cortex applies this logic to modulate the sensory or emotional pain we experience in sympathy with others. We feel the hurt of other people’s misfortunes more if we take their perspective. A region at the junction of temporal (facts) and parietal (space) lobes plays this role. In its fashion, the brain takes the act of perspective-taking quite literally – it involves spatial computations to see the world from another point of view: to distinguish our view from the other, our self from the other.
Finally, the frontal cortex must combine the context, its own goals, and emotional states to select plans and control sensory and motor systems, in order to behave in the right way in social situations. Don’t slurp your tea in polite company.
So the social thing is very important and rather sophisticated. But there are other ingredients in the human brain recipe which are key to distinguishing us from even our closest apey relatives.
A gizmo is a device or small machine that performs a particular task, usually in a new and efficient way
Birds fly, bees buzz, every species has something that it does well. What is the human speciality, what are its gizmos?
‘We don’t have the biggest brains – that’s elephants and whales’
We like to feel special; we like to feel we are apart from other animals. So what will it be? Do we have the biggest brains, the wettest blood? In the animal kingdom, our brains are not exceedingly special.1 We don’t have the biggest brains – that’s elephants and whales. Sure, we have a high proportion of cortex (the outer layer) in our brains, but it’s on a par with chimps, horses, and short-finned whales. We have quite a lot of brain for our body size, but amongst primates, this proportion isn’t strongly linked with thinking ability. Now, we do have a decent number of neurons: over twice as many as gorillas. But even then, not close to the number that dolphins have.2 And to be honest, we probably have the same number of neurons as our ancestors in the wider archaic homo family tree, including Neanderthals – and we like to think we’re specialer than them, don’t we?
Not sure about the wettest blood thing.
There are five human gizmos. Tool use, language, conceptual power, a clutch, and niche building. They are linked.
The first human gizmo is tool use. One of the things we do exceptionally well is to build and use tools, particularly to shape and interact with our physical world. As we saw in the previous section, evolution tends to innovate at the periphery, out in the body. We have dextrous hands and opposable thumbs. We don’t use them for walking. In the same way the bat has no special new part of the brain to support echolocation, we don’t have a special new part of the brain to support tool use. The motor functions are supported by the front part of the brain. We do have more ‘front of the brain’. Our brain develops using a similar recipe to other mammals and primates, but the front bit of the cortex grows for a longer time and becomes larger. The recipe is tweaked. The extra cortex allows us to develop fine motor control and coordinated movements to create and use tools.
The second gizmo is language. In one way, this is similar to tool use. Language is a sequence of complex movements, but now used to shape and interact with our social world. The innovation of evolution is in the articulators – lips, tongue, larynx – and mechanisms of airflow, which together enable us to make the range of speech sounds. In the brain, language also requires the extra cortex to learn the complex and precise motor movements to produce words. But there are no new special parts for language. Language utilises circuits used in making sequences of movements, circuits for perception, concepts, processing situational scripts, social intentions and agents. It fashions these together into a system that allows for fluent use of this motor skill. And if we want, we can use movements of the hands to communicate, in sign language.3
’This football match is like David vs. Goliath’
Language is a great gizmo because it is an enabler. It allows you to acquire knowledge without direct experience. You can learn by being instructed. It supports building abstract concepts, by using a language label (like “six”) to bring together all the different situations involving six-ness (an Arabic numeral, a group of six things, an object with six parts, a sequence of numbers where six falls between 5 and 7, a pile of sweets bigger than 3 but smaller than 20, a length of 6, and so forth). Language can be used to bring to mind knowledge that is not automatically elicited by the current situation, via verbal analogies (e.g., ‘This football match is like David vs. Goliath’; ‘You can view electricity like the flow of water along a pipe’). Beyond the individual, language supports sophisticated socially coordinated activities, greatly increasing the potency of group behaviour.
The third gizmo is more conceptual power. With more cortex, especially in the front of the brain, more complex ideas can be developed. The evolutionary reasons for the larger cortex are murky. Maybe it was to support language, maybe tool use, maybe to support social cognition to deal with life in larger groups (keeping track of who likes whom, who did what to whom, what does everyone want, who’s lying, etc.). Maybe all these things at once. But once you have more power, the game changes.
We talked about sensory and motor systems in terms of towers. The lower floors see patterns, each higher floor sees patterns within a patterns. The larger cortex means humans have higher towers. In sensory systems, they can see deeper patterns of meaning in what they perceive, in motor systems they can plan motor sequences that reach farther into the future.
The deeper patterns of meaning include mental models of how the physical world works. This can include inventing invisible forces to explain physical events (electrons, germs, gods, ghosts). In the social world, it can include more sophisticated knowledge of social scripts, episodes, situations, and motivations. Although our basic emotions are probably similar to other social primates, we can attach these to more complex social scripts (W does X under Y circumstances and feels Z; Sophie snubs Bill at the party and feels guilty). This leads to a wider palette of emotions: pride, hubris, dignity, honour, admiration.4 Our mental simulations can include ideas about ourselves, in so-called meta-cognition, self-awareness, where I form a theory about how I behave, and use this knowledge to alter my future behaviour. More pre-frontal cortex, where the modulatory system lies, also gives the modulatory system more precise control over the meaning systems in the rest of the brain. It can separately control bits of ideas. I’ll have this bit of the idea, but not that bit. It allows for thinking about ‘what-if’ counterfactuals, about hypothetical situations. I mean, what if the moon was made of cheese?
One particular advantage of more precise internal control is that it gives us a clutch.
Definition: clutch – a mechanism for connecting and disconnecting an engine and the transmission system in a vehicle, or the working parts of any machine
The fourth gizmo is a clutch. Part of the modulatory system (sitting in the ventromedial pre-frontal cortex, sigh) is a disengage system. Brain activity can be decoupled from perception and turned to internally focused thought. You hear a sad story, and it makes you _think_… When disengaged from the present moment, the brain can run mental simulations. Fantasy and imagination. It can retrieve memories of past experiences to envision future and alternative perspectives and scenarios, conceive the perspective of others, simulate the navigation of social interactions, ruminate, generate and manipulate mental images, decide on moral dilemmas. All the things we do when we sit and think rather than perceive and respond to our immediate environments. The brain can even disengage while it carries out automatic activities. You daydream while you do the washing up. When the clutch is pressed down, we have the opportunity to learn not from the world but from our imaginations.
The final gizmo builds on all the other four: tool use, the social coordination enabled by language, the planning and imagining of other worlds enabled by greater conceptual power. It is a gizmo that most marks us out from other similar species: niche construction. A niche is the particular environment that a species lives in, and to which it is adapted. Unusually, you can find humans almost anywhere. Jungles, swamps, savannahs, mountains, deserts, tropics, icy wastes. Birmingham. Humans use their gizmos to adapt to all these environments, to build their own niches. Clothes, dwellings, modes of transport, hunting and farming equipment. We change our environments to fit our biology.5
So there you have it. Human do have some gizmos, without being biologically particularly special.
‘You can’t explain how the modern human brain works just by looking inside it’
Unfortunately … these gizmos aren’t enough to explain how the modern human brain works. And that’s because you can’t explain how the modern human brain works just by looking inside it.
To get to the bottom of that, we need to go back. A long way back. And that’s what we’ll do in the next excerpt. If you can’t bear the suspense, you can jump ahead instead
 See who wins the my-brain-is-specialer-than-yours competition
 You may have heard theories that various abstract properties of human language, like grammar, are special genetic features of our species (‘grammar is innate’). All I can say, for the purposes of this resource, is that these theories are probably wrong.
Welcome to our blog series where we ask teachers about their experiences of accessing and using research. We are delighted to introduce Tom Colquhoun who is Assistant Headteacher, Teaching & Learning at The Blue School in Wells and Director of West Somerset Research School.
What does educational neuroscience mean to you?
I believe that those with an interest in educational neuroscience aim to try and better understand how the brain works, how we learn and how this can help teachers and learners to be more successful. The core business of all teachers and educationalists is to improve the life chances of those in their care. This is best done through helping children to learn, develop knowledge, skills and understanding and to develop as a person. If we can become more informed about some of the challenges involved and the potential barriers to learning, we can start to become even more effective in our work.
How do you keep up to date with the latest research?
As Director of one of 22 Research Schools across England, it is a requirement that I remain well-informed of the latest education research and the evidence that is generated. Fortunately, this has become so much easier in the last five years with organisations such as the Education Endowment Foundation (EEF) and the Institute for Effective Education (IEE) on the scene. Here, some very good people spend considerable time and effort producing clear, accessible summaries that busy teachers and school leaders can use to help inform their decision-making and to improve classroom practice. If you haven’t done so already, I would strongly recommend that you register to receive ‘Best Evidence in Brief’ from the IEE – a fortnightly mail shot with all of the key education research headlines from across this country and indeed the world. This is an excellent example of how teachers and school leaders, with little or no time and effort involved, can keep abreast of the latest developments. I would also urge colleagues to sign up for the EEF’s ‘News Alerts’ and to consider becoming a member of the Chartered College of Teaching. In particular, the College’s Impact Journal comes through the door each quarter, packed on every page with interesting, evidence-informed writing from some of the world’s leading researchers and writers. One last signpost is to The Learning Scientists who have helped many teachers across the world to access some really useful strategies and resources for improved teaching and learning. Sign up to receive their weekly digest too, for an interesting and thought-provoking read!
Can you give some examples of how neuroscience understanding has helped you and your school?
At The Blue School in Wells, a large comprehensive secondary school, we have invested heavily in improving the quality of teaching and learning in all lessons. All teachers are members of a group of fellow professionals who work closely with one of ten appointed teaching coaches. With a focus on sharpening up the first ten minutes of lesson, the coaches have encouraged their group members to be innovative in their practice and to implement the recommendations of the EEF’s Guidance Report on Metacognition and Self-Regulated Learning. As part of this new model of CPD, colleagues have been supported to read more about memory, cognitive load theory and effective modelling and to consider how this could improve their practice.
How do you get teachers and students involved?
All teachers are assigned a teaching coach who will visit lessons, offer feedback and facilitate the sharing of effective practice across the school. We have included the engagement in this new type of CPD as a target in this year’s cycle of Performance Management. We’re not expecting all of this innovative practice to work, but we are hoping that our staff will become more comfortable to engage with and believe what the best evidence suggests. They will hopefully then consider what might be the ‘best-bets’ for our children, going forwards. Our students have already been quizzed about the impact of these changes in practice through our system of regular student voice interviews. We were mightily relieved to hear that the feedback from them was overwhelmingly positive!
Are there areas where you think research should focus next?
The field of educational research is huge and growing by the day. The EEF have already published ten guidance reports on high-priority issues for schools (literacy, maths, parental engagement, etc) and plan to publish many more in the coming months (feedback, digital learning, etc). One that I particularly look forward to reading is their offering on ‘Behaviour’, due to be released very soon. Many teachers question their ability to help children learn effectively when the behaviour presented is so difficult to manage. I look forward to reading what the experts recommend and to thinking about how I can bring that practice in to my own teaching.
To find out more…
If you’d like to find out more about The Research Schools Network, visit the website to track down your nearest school, read their blogs and view their training and events calendar. Register to receive their monthly newsletter, which will be packed full of research findings and opportunities to get involved.