Remembering stuff

Someone once said that the educational debate in the UK is lightyears ahead of the debate internationally. It is a shame really because you would hope that the minds engaging with educational debate from every country would add to making the debate more urgent.

The modern education system is sometimes characterised as being one where kids are mindlessly forced to rote learn and that we have to fight against this industrial factory like education. It’s anecdotal I know but I have worked in five schools and visited a few more and never seen anything like this. Where are all these schools that are battery farming their kids? Most schools are definitely more progressive in their outlook than traditional, in this sense. Although I would contend that good schools and teachers in them know when to adopt different techniques as necessary.

If you engage in debates about the aims and methods of education it is common to read thinking like this, a popular view exposed by many educators, and widely influenced by romanticism:

“The point I am making is that DI is very successful in a certain thing that we are measuring. Remembering stuff. For an education system that measures how well you can remember stuff sat at a table for two hours (of which the DP is really no different from any other offering) then I’m sure DI is highly effective…. but really why do we care? We all pretty much know that that such a metric is a) a terrible way for Unis and businesses to know that they have recruited an effective colleague b) it just isn’t they way to make it in the world past examinations. Once our smartphones can answer any knowledge based examinations (not far off from now) then DI will just about be a waste of everybody’s time. What I’m interested in is what type of instruction leads to creative, communicative, empathetic, collaborative, entrepreneurs and explorers? If DI does that then I’m interested. But first we have to develop a way of measuring these things to see if a certain practice achieves it. Any other research is basically past its sell-by-date, as I suspect are exam based remembering courses.”

Remembering stuff. It’s the practical equivalent of the old, male and stale ad-hominem stereotype trotted out in arguments in post-modernist education discussions at times. It’s uncool. It’s useless and why would anyone who cared about kids and their futures insist on paying attention to it in their classroom or school? It’s outdated. We don’t need to remember because we have google now. We don’t need knowledge because AI will take over our jobs and if we make sure kids know and remember stuff then they are doomed to be job-less, on future the scrap heap, in a world where 65% of the jobs haven’t yet been invented yet.

Why do we care about remembering stuff? 

First, let us not conflate remembering and knowing. They are not the same thing. Technically, remembering is simply the process of retrieving information from your long term memory that you know. Knowing something is having it stored there in the first place. It is possible to know something and not remember it.

This argument above mentions remembering initially but then refers to knowledge based exams and questioning the value of knowing stuff when our smartphones can do that for us later, effectively conflating the two. Both knowing stuff and being able to remember stuff are important. It’s no good knowing stuff and not being able to remember it and you can’t remember what you don’t know. So, in my view education has to help students do both of these things. Why is knowing stuff and then remembering it important and why should we care?

Well, actually, knowing stuff is still pretty important. Believe it or not. Some educator’s use Bloom’s Taxonomy to assert that remembering stuff is at the bottom of the pile, a low order skill useless on its own. However, despite the fact that this taxonomy is not informed by the cognitive psychology of how people learn and it is often presented uncritically, this interpretation is also not what Bloom intended. He put knowledge at the bottom as it is the foundation on which all else is built.

You can’t do much if you don’t know anything. And in fact the more you know, the more you can do, including learn more. The Matthew Effect is a well documented psychological phenomenon by which the rich get richer and the poor get poorer. The more you know, the easier it becomes to learn more and therefore become a life-long learner. That is one reason why we should care, especially if we want to make life-long learners.

These days it is fashionable for international educators to discount knowing  stuff because the international consensus is that 21st century skills are more important than knowledge per se. These 21st century skills are generally recognised to be the four C’s of communication, collaboration, creativity and critical thinking. The line of reasoning is, generally, that we need to teach these skills instead of knowledge.

There are a few problems with this line of thinking. Firstly these skills are not actually 21st Century in and of themselves, and there is no reason to think that they are more important this century than they were in the time of Julius Cesar. Indeed, calls for skills based curriculums go back at least a century already.

Secondly, we can’t have people skilled in these areas who aren’t also knowledgable. Most psychological research to date suggests that creativity requires knowledge and it is only possible to think critically about what you already know about. If you really think about it – to be a great communicator you actually need to know about what you are communicating about. Could you imagine the BBC Earth documentaries not only without a knowledgable David Attenborough but the teams of knowledgeable researchers who write the scripts?

Thirdly, the idea of teaching generic skills is also flawed. The generic skills method of teaching postulates that authentic tasks are ones that mimic real life i.e. science teaching that gets kids to act like scientists. Authors like Daniel Willingham and Daisy Christodoulou point out that the most effective way of teaching skills is through the deliberate practice method. Just as a football team doesn’t practice by playing games, but by breaking the skills needed to win (dribbling, passing) down to their component tasks and practicing those.

In short knowing stuff (and remembering it) is the foundation of the skills we want to instil in our kids, it is also the foundation of understanding and the foundation of life-long learning.

We all pretty much know that that such a metric is a) a terrible way for Unis and businesses to know that they have recruited an effective colleague b) it just isn’t they way to make it in the world past examinations.

Do we? How exactly do we know this? It seems hard to make that claim as it is pretty much unmeasurable. Even if you could survey every employer and university there are too many conflating variables. We are all products of this system. This claim is made without any proof and the burden of proof lies with the one making the claim.

Once our smartphones can answer any knowledge based examinations (not far off from now) then DI will just about be a waste of everybody’s time.

Oh no. Seriously? We still honestly think this? It is right up there with the “we can google it” claim that knowledge isn’t worth having. In addition to what I have written above I should highlight here the distinction between working and long term memory.

Working memory is what you can hold in your awareness and it is limited. The environment and long term memory are accessible from working memory and long term memory is unlimited in its store.

If we rely on google and not our long term memory we will find it very hard to make sense of the world around us as our working memories will constantly be overwhelmed. We wont be able to chunk information.

Knowledge isn’t just what we think about it is what we think with. If you rely on google on your smartphone you won’t be able to think well, you certainly won’t be able to think creatively nor critically nor communicate well.

Also, google is blocked in China. Do we really want to give governments that much power over knowledge and what we know and can know?

What I’m interested in is what type of instruction leads to creative, communicative, empathetic, collaborative, entrepreneurs and explorers? If DI does that then I’m interested. But first we have to develop a way of measuring these things to see if a certain practice achieves it.

Yes, it can do. DI has been shown to effectively increase what people know and remember. If knowing and remembering is the foundation of being able to think well, collaborate well,  and create well then we shouldn’t just throw these out.

One of the problems with international education in my view is that it over emphasises inquiry learning, making ideologues get hot under the collar when DI and other guided instruction is mentioned. We are trained to think schools are battery farming kids, when to be honest, they really aren’t.  I think we need to try to find out what works in what context and focus on that. I think that there is a place for guided instruction.

Anyway, DI does not always equate with rote learning. Why make it out to be?

I am also now reminded me of this article and this tweet. They are based on similar assumptions and outlooks, and I had wanted to write something in response to these claims.

I agree with Noah Harari when he writes that we often conflate intelligence and consciousness.  I am not convinced that AI can actually know anything. I think it is intelligent and can process a lot of information quickly, but I would contend that to know anything and remember anything you need to be conscious.

If this is true what is the real risk presented by AI? Probably automation of tasks that rely on data processing in some form. Doctoring for example, requires the ability to process symptoms and match them to known illnesses. But not every job is at risk of automation because not every job relies purely on data processing. As Harari contends in his books, the highly prized human jobs of the future will be the ones that rely on human ability to relate to other humans. Therefore Doctors are at much more risk of being automated than Nurses. However, Nurses still need to know an awful lot of stuff as well as be at good at relating to other people to be able to do their jobs.

Humans need knowledge to be able to think well and to specialise in areas. If we don’t ensure that people know things they definitely will not be better placed to work with or instead of AI. The people that are replaced by AI will be the ones who don’t know much.

Additionally, the fact is knowledge rich curriculums demonstrably reduce inequality and with the way social divides are opening up in our modern society perhaps the way for international education to contribute to a peaceful world is to close those gaps? Seeing as DI has been demonstrably shown to reduce social inequality (See Why Knowledge matters by E.D. Hirsch) and as international curriculum’s like the IB is placed in many public schools in poorer areas, I find it’s focus on inquiry teaching quite worrying.

I wonder if international educators can afford to ignore this stuff because generally our kids come from educated and affluent homes?

Intensive EAL support and differentiation in Biology

As an international teacher, I am familiar with EAL or Lang B students in my classes, and familiar with how to support them in my Biology classes which, more than even some of the other science subjects, has a lot of context-specific terminology that cannot be simplified. These terms can be almost impossible to simplify form non-native speakers but repeated INSET training has told me that I must. Some examples would include:

  • Heterozygosity
  • Anyone of the Animal or Plant Phyla students are required to know
  • Proteome
  • Clade
  • Oxidative Phosphorylation
  • Photolysis
  • Inhibitor
  • Eukaryote
  • Archaea
  • Transpiration
  • Cohesion

There are many more…

This past academic year I had a particularly difficult situation to deal with in my grade 10 biology class.

Grade 10 is the final year of the MYP and is equivalent to Year 11 in the U.K. My current school is very small, tiny in fact, by the nature that it has only been open four years.

As a new school in a competitive area we have a battle to recruit students. As an international school in an area where lots of families come with the parents work on short term contracts we have a high turn over of students.

Due to these factors, every year of teaching I have had to completely change my scheme of work for this grade and grade nine because of changes in the cohorts of students as well as yearly changes to science teaching hours across the week.

One year I only had brand new students taking grade 10 Biology all of whom had come from Francophone schools and so the MYP 5 course I had planned had to be changed to accommodate these students.

As an international school it can be normal to have turnover in students with many students leaving and new students entering at any grade. Things are also complicated because students may come from different national systems, and may have studied in different languages prior to joining us. It's very hard to comparatively assess the biological knowledge of different students coming from different languages of study and these different systems.

Whereas, last year, all the students in my grade 10 class were new to the school and I had to create a novel one year curriculum for them to ensure that none of the fundamentals from grade 9 were missing, this year I could revert to the original two year program I had planned previously.

This year I had some students who had progressed to grade 10 biology from grade 9 (these grades are planned as a two year consecutive course) internally and were on track to take the MYP eAssessment.

However I also had students placed in the class who came from different schools and were new to studying in English, let alone biology in English. Amongst these students there was variation. One student had absolutely no prior experience using or studying in the English language and others had never studied in the language, academically, but had spent some time of heir lives speaking and communicating with English.

At the start of the year, I was informed that all of these students would be taking the MYP eAssessment (the IB equivalent of GCSE)!

Despite my protestations that these students would not be ready for the eAssessment with only six months of going to an anglophone school, let alone studying biology in English and that they were better off being placed in an intensive EAL program, I was ignored.

The message to me was that I simply had to differentiate for these students! Differentiation is fine but when does differentiation steadily become "plan a whole new program?" What are the practical limitations for a teacher that determine when differentiation should stop and alternative arrangements need to be made.

A similar situation happened to a colleague of mine who teaches French. One year he was told that he would have French A (Literature – native speakers) students mixed in with French B (Aquisition – non-native speakers) and that the teacher would have to differentiate between these two groups.

I am all for differentiation and trying to meet individual students where they are at but I don't like it when it becomes a lazy shield for management to hide behind. Instead of the SLT taking charge and actually putting a proper intervention in place for these students, it is easier to pass the buck to the teacher and simply say "differentiate!" The problem with this is the anxiety, stress and associated mental health issues it will invariably create for staff.

What seemed to be lacking from members of the schools management is the difference between Jim Cummin's BICS and CALPS. Being able to speak in a second language with your friends is one thing, but being able to think about and explain complex, abstract concepts in a second language is quite another. Biology has a huge amount of subject or context-specific terminology that even native speakers can find daunting.

The year hasn't been a great success. Unfortunately some non-negotiables have to be negotiable as there is a limit to what a person can achieve in a day. What this meant for these students is that I simply wasn't able to plan for them as well as I would have liked, with all my additional responsibilities, particularly the running of the university guidance.

I focussed what time I could devote to this class on the students who would be taking the exam and focussed on developing the thinking routines within the class; connect-extend-challenge has become very popular!

However I have been able to learn something from this experience and found that the following techniques could be put in place very easily to support EAL students without too much interruption to the flow of the lesson:

  • Glossaries for every unit that focus on key words. I have started adding them to my DP workbooks as simply a space at the back for students to add their key words and definitions, but for the younger grades I will provide the words and the definitions.
  • Whole-class reading in every lesson. Making solid use of available texts and reading these out gives students a change to practice saying new words and gives me a chance to feedback to them and explain any new terminology.
  • When asking students to explain a concept to check for their understanding, allowing them to write out their ideas in the their mother tongue to support a speaking in the second language.
  • Asking students to write, in English, a short paragraph (3-4 lines) explaining what they learned either at the start of end of a lesson. As the teacher, I can rotate and check grammar, spelling and sentence construction. This is best done by hand as 1) the IB exams are currently written and 2) due to the Lindy effect, writing is likely to be around a lot longer than google docs.
  • Taking care to fully explain the roots of words e.g. "photo" & "synthesis" and giving students time to find the words in their mother-tongue if they have studies this concept before.
  • Allowing students to speak in their mother tongue to each other to aid explanations and comprehension.
  • During explanations given by me, slowing down and, where possible, using simpler language (not always possible in Biology – what is a simpler word for heterozygosity?).
  • Always check for understanding with open questions. "Please can you explain/write/draw this for me?" to show understanding.
  • Use of colours and images to describe tasks so that students become aware that when a symbol of a quill is used it means that they have to write.

Any more advice or ideas welcome in the comments!

Is Content King?

I have reached a watershed in my thinking about teaching and my philosophy about teaching science.

I trained and begun learning to teach in a school with a very robust academic record. Teachers were considered absolute experts in their field and students were, on the whole, very high achieving but who had high expectations of their teachers academically too.

In this environment I learned that the teacher’s fundamental responsibility was to be an an absolute expert in their field; if you didn’t know everything, and could not answer every question, the community of students would lose faith in you. Or at least that it is what it felt like.

I mentioned in my review of Ritchhart et al of comments made by an ex-colleague of mine which reinforced this sentiment.

In those formative days then learning to teach was about mastering your subject knowledge. Content was King. Delivered in lovely little powerpoint slides where students would simply copy down their notes and then memorise them.

I left that school confidently arrogant that I was an expert in my subject and in the IB. That any school was going to want to employ me after the time that I had spent in that school. And indeed I was partly right. I secured a position as Head of Biology at a prestigious boarding school. The time there was little different. I benefitted from working closely with the chemists and physicists, in a closely knit science department. However the sentiments were the same. Content was King. Our role as science teachers was to deliver the curriculums content. The learner profile was dismissed by the Head of Science as fluff.

Since moving on from that school I have been involved in setting up a school and taking it through its IB authorization process as the only Biology teacher and as one of two or, more recently, three science teachers. I cannot point to any single experience from this time that has been the catalyst but my thinking has begun to change. Perhaps it was being forced to seriously consider the IB’s other bits; the ATLs; the IB Learner profile. Perhaps it was being exposed to and challenged by the MYP. Perhaps it was teaching a new DP Biology syllabus with so much focus on the nature of science. Perhaps it was beginning to teach TOK. Perhaps it was becoming a workshop leader. Perhaps it was working with so many truly excellent IB educators. I don’t know.

But I now question the sentiment that content is king in science teaching.

I am beginning to think, to really think that more important than learning the content, my students need to learn to think. It might sound like an odd thing to write. It certainly feels like an odd thing to write.

I’m sure that many people who aren’t teachers would raise their eyebrows at what I wrote above. Surely, a teachers job is to teach students to think? But it’s not as simple as that. Teaching students to ask strong questions and to develop different thinking dispositions is no simple task. It’s much easier to focus on the curriculum delivery. What are my students supposed to know? Fill the time in with student-centred activities, and group work, debates and presentations and you are doing a good job right?

I’ve moved on from didactic lecture like teaching in my early days to worksheet, activity based teaching but has anything really changed? My students still present as apathetic. School is still something that they just do on the whole. I’m sure most of them forget what they “learn” instead of engaging with the deeper issues.

And this is what I want: I want my students to be engaged, passionate and switched on critically to the world around them and be scientifically literate.

How do I do that when sometimes I question my own scientific literacy?

Perhaps its time to really focus on the thinking and the types of thinking that are needed in science and needed to be developed in students of science. The trouble is I am sometimes not sure that I know what thinking really means…

In Making Thinking Visible Richhart et al (2011) discuss turning the content into a vehicle for teaching and framing certain thinking skills. It is argued that developing thinking skills is important because these skills are the tools that students will take forward into future life when the content is forgotten. They are the tools the future adults will utilize to navigate life.

The thing is, thinking doesn’t just happen. As teachers, we need to be explicit with students about the types of thinking that are useful in certain situations and provide strategies that help students learn to think in these ways. We can’t just leave it up to chance. After all, traditionally, we don’t leave the content up to chance (normally), instead, we are explicit with it. We need to give students the chance to think about their own thinking and what it means to them.

Ritchhart provides a list of “high-leverage thinking moves that serve understanding well”:

  1. Observing closely and describing what is there.
  2. Building explanations and interpretations.
  3. Reasoning with evidence.
  4. Making connections.
  5. Considering different viewpoints and perspectives.
  6. Capturing the heart and forming conclusions
  7. Wondering and asking questions
  8. Uncovering complexity and going below the surface of things

I will be posting these “moves” in my classroom as a start as well as try to relate the activities we are doing to these types of activities.

As science teachers, we need to ask ourselves: What type of thinking is important in science? More specifically what types of thinking do we want to develop in students of science? How is thinking framed in terms of the work that scientists do? What are the essential questions of science?

Clearly, the thinking moves above are addressed by different elements of scientific enquiry. Observing closely is an important part of observational studies and also hypothesis generations so is wondering and asking questions. To generate a hypothesis requires building explanations and reasoning with evidence. When we draw our data out we try to capture the heart of a problem and draw a conclusion,

Once we have a clear idea of this then we can begin to teach the thinking alongside an understanding of the nature of science through well-planned content. The difference is that our learning objective is twinned – we have a thinking objective and a content objective.

Understanding how to teach in this way is important.  Biology teacher Paul Strode has written some articles in this vein. In one he looks at reasoning like a scientist and the other deals with teaching the hypothesis. Although he still focuses on framing the content instead of necessarily framing the questioning, these are good reads. However, I feel that the questioning and thinking strategies needed to become front and centre of the teaching instead of the content.

Thinking relies heavily on questioning. In science we are trying to ask the following questions:

What do I notice?

What does that tell me?

Why does it work like this?

How can I test this idea?

How can I be sure that my findings are valid?

Or, according to strode whose list is below:

Step 1: What claim am I being asked to accept?

Step 2: What evidence supports the claim? Is the evidence valid?

Step 3: Is there another way to interpret the evidence?

Step 4: What other evidence would help me evaluate the alternatives?

Step 5: Is the claim the most reasonable one based on the evidence?

Teaching like this requires teachers to step down as the “font of knowledge” in their classrooms and have the courage to be wrong. I have worked in schools where the culture of the school would simply not allow that to happen.

As Ritchhart points out we need to be able to ask our students authentic questions, meaning that the teacher needs to not know the answer, and if teachers are worried about seemingly not knowing something how can they do this?

This academic year I am going to try and put thinking centre and front in my classroom. I just hope that the crazy timetabling and work-load pressure doesn’t push me back into easy, old habits.

Learning Theory & Educational Neuroscience

I wrote this article in February 2015 as part of my PGCE Top-Up course at the University of Northampton. This is a course aimed at teachers who already have completed initial teacher training through the graduate training programme and gained QTS, but want to add on the university PGCE to this qualification.

Why publish it here? I have found that my own interests within Biology have developed hugely since I started teaching, taking me to academic areas that I never studied in my original Zoology degree. This is partly through trying to keep abreast with a subject whose post-16 content has changed and continues to change dramatically year on year and also partly through my own genuine interest in the subject. The brain and behaviour has been one of these areas.

As teachers we have a natural interest in how the mind works and how individuals learn. In one (very loose) sense teachers are Biologists because of this interest; we want to understand the mind of this species of hominid and how it develops.

My interest in educational neuroscience represents for me a cross over of these spheres of interest in my own professional life – biological science, specifically neuroscience and education.

Thoughts gratefully received.

Introduction

On 19th October 1964 a paper was published in the journal Physical Review Letters. In it the author, Peter Higgs, hypothesised about the existence of a fundamental particle that was responsible for giving mass to other fundamental particles: the so-called Higgs Boson (Higgs, 1964). 47 years, 8 months and 15 days later, the European Organisation for Nuclear Research, CERN, confirmed that experimental physicists working at the facility had demonstrated the existence of the particle (CERN, 2015).

This story of discovery illustrates the wonderful interplay in science between scientific theory and scientific fact. The Higgs theory was just one of several competing models which had been proposed over 4 decades to explain how fundamental particles may interact. With the discovery of the Higgs Boson, the Higgs theory, with some modification, was proved to be the correct explanation.

In a similar way neuroscientific studies of the brain and its functioning could be used to constrain and validate psychological theories of learning. Educational practice uses psychological theories, developed over the past century or so, what if we attained physical evidence to illuminate which ones should be developed and which ones could be discarded?

Modern educational theory has diversified hugely with specialist areas devoted to studying different learning contexts e.g. classroom, outdoor, experiential, life-long, as well as at different developmental stages e.g. early years, school-age, university and adult (For a review see Illeris, 2009). It is only relatively recently that educational researchers have begun to try to forge links between education theory and neuroscience (Geake, 2009), while some have questioned the basic ability of these two fields to be bridged (Bruer, 1997).

I will review the evidence that educational neuroscience is yielding, and review the arguments for and against use of neuroscience in the context of education. Neuroscience still has much to learn about the brain but we already have an understanding that can inform educational practice on a variety of levels. I will begin by describing the development of psychological theories of learning before moving on to examine the contribution that modern neuroscientific or brain based theories of learning may yet make towards developing our understanding of how humans learn.

Learning Theory

Humankind’s interest in learning and teaching could be said to go right back to the early days of our pre-history when, as a new species, we had to invent new ways to respond to a changing environment. Indeed learning is without doubt a very, but not solely, human trait; it is essentially what has allowed us to adapt to every environment on the planet.

Modern attempts to explain how humans learn have their roots in the psychological theories of the late 19th Century with the advent of cognitive psychology, behavioural science and ethology (Pritchard, 2009).

In the 20th Century behaviourists, notably Skinner (1958), developing the work of Ivan Pavlov, focussed on innate behaviour in animals and discovered the mechanisms of conditioning and reinforcement. Behaviourist approaches to understanding learning and human development view learning as the acquisition of new behaviour (Prichard, 2009).

In contradiction to behaviourism, constructivism views learning as the result of mental construction i.e. new learning is added to pre-existing knowledge. Piaget (1954) and Vygotsky (1997) separately developed their own particular brands of constructivism which differed fundamentally about how learning is constructed: Piaget viewed learning as being cognitively constructed and that students acted as lone scientists who learn through discovery; Vygotsky viewed learning to be socially constructed, with the teacher (and other students) having a significant contribution to play in scaffolding the work and setting the challenge for their students (Pritchard, 2009).

The influence of these theories cannot be understated. Constructivism is the key idea in education, underpinning not only many modern theories of learning, but also curriculum models (like the International Baccalaureate, an inquiry-based curriculum model [IBO, 2015]) and classroom based pedagogical approaches. Today it is taken for granted that learning is constructed within the mind of the learner and therefore new learning builds upon prior learning and understanding. This is the overwhelming epistemological standpoint that underpins all of modern theories of learning (Samuels, 2009).

Neuroscience and Education

Much of the early research in neuroscience focused on the structure and function of neurons, the specialised cells that make up the brain and nervous system. These neurons, form connections (synapses) with each other. At these synapses individual neurons are able to generate or inhibit the “firing” of impulses within the other neurons that they are connected to. In this way neurons are assembled into neuronal groups or brain modules (Geake, 2009). It is these neuronal groups, their interconnectivity and how they may relate to pedagogical practice that is of interest in educational neuroscience.

An early neuroscientific model of learning, that is still robust today in terms of its explanatory power is that proposed by school-teacher turned neuroscientist Donald Hebb (1949). In Hebb’s model of learning it is the number of connections within the brain not the number of neurons that is important. He states that when a neuron stimulates or inhibits a signal in another neuron across a synapse, that synaptic connection is reinforced. Conversely when signals are not issued across a synapse very frequently, that junction between the two cells, is not preserved. Thus neurons that consistently communicate with each other have their synaptic connections maintained, while those that do not lose their connections.

Attempts to link the findings from neuroscientific research and formal educational practice date back to the 1980s (Bruer, 1997) and since that time, opinions of educational researchers have been divided on the usefulness of neuroscientific research in education (see Bruer, 1997, Geary 1998, Geake & Cooper, 2003, Goswami, 2004). However, recent writers are less pessimistic (Goswami, 2006, Varma et al., 2008, Samuels, 2009, Ansari et al., 2011, Howard-Jones et al., 2014,  Howard-Jones 2014, Schenk & Cruickshank, 2014) and the trend in published articles becomes more positive. Indeed, it is telling that in the last decade we have seen the formation of the International Mind, Brain and Education Society (IMBES) along with the Mind, Brain and Education Journal. The Societies aim is to “facilitate cross-cultural collaboration in biology, education and the cognitive and developmental sciences” (IMBES, 2015). In addition there have been two formal reviews of the field, first by the Organisation for Economic Co-Operation and Development (OECD, 2008) and the second by the Royal Society (Royal Society, 2011). All of these developments suggest that the findings from neuroscience and education research are beginning to converge.

Many of the arguments questioning the usefulness of educational neuroscience have focussed either on the limitations of the methodologies employed in studying neuroscience or the extrapolations that education professionals (researchers, teachers, civil servants) have made about the results from neuroscientific studies resulting in the so-called “neuromyths”.

Bruer (1997) argues that neuroscience only has an explanatory power when viewed through cognitive psychology. He described the three fields of classroom instruction, cognitive psychology and neuroscience as being spanned by two bridges – one from instruction to cognitive psychology and a second from cognitive psychology to neuroscience and that only by contributing to our understanding of cognitive psychology could neuroscience hope to deepen our understanding of classroom learning. He describes using neuroscience to study learning as a bridge too far. His essay has been citied a great number of times and the arguments he makes are worthwhile to the classroom practitioner.

Bruer’s premise is that studying the mind is not necessarily informed by studying the brain. This argument is rebutted by Cruickshank & Schenck (2014) and Howard-Jones (2014) who argue that because the mind is created by the brain it must have biological correlates. The systems of processing in the mind must be reflected by systems in the brain. This is an idea that as a Biologist and Science Teacher I tend to agree with.

Bruer (1997) also describes at length the early work of neuroscience that was conducted on single neurons in rats, mice or monkeys. He demonstrates that much of the evidence from these studies has been extrapolated to humans and used to describe human neural development. He makes the valid argument that extrapolation from rats to humans is a large assumption. This extrapolation has formed the basis of many “neuromyths” – misconceptions about learner’s brains that have been adopted by the education community. These misconceptions tend to contain “nuggets” of truth which have been misunderstood or poorly applied (Howard-Jones 2014).

Goswami (2006), Geake (2009) and Howard-Jones (2014) provide excellent up to date considerations of the neuromyths that have been adopted by the education community. They cite the ideas that learners are left or right brained; brains are male or female; the existence of brain buttons under the ribs; that there are critical periods for learning; that brains process information from different senses independently and that there are, consequently, individual learning preferences, as examples of neuromyths.

The prevalence of neuromyths cited within the literature and used to support various philosophies and policies of education is used by Bruer (1997) as evidence that neuroscience cannot, and should not, influence education. It seems to me that this argument is to misunderstand and misappropriate the role of science in society. It is precisely because neuromyths abound that systematic research needs to be conducted and communicated clearly to stakeholders. The reports from the Royal Society (2011) and the OECD (2008) along with Geake (2009) and many other authors now highlight the need for initial teacher training that provides some training in general scientific and neuroscience specific methods, as well as making an argument that deeper collaboration between the education and neuroscience academic communities is necessary so that educators and neuroscientists are able to better spot and counter these myths with biological evidence. Educational neuroscience has great potential to become a transdisciplinary area of collaboration with ideas from both fields influencing the other.

Bruer (1997) also writes about the problems with interpreting data from neuroimaging studies as well as the use of neuroimaging technology to study educational problems. In the 1990’s there was a huge expansion in development of technologies used to study the brain. For a review of these methodologies see Geake (2009) but it is important to note that the maps produced by scans of the brain are averages and do not necessarily represent individual brains. At that time neuroimaging technologies had very little ability to ask questions about classroom practice due to their size and cost, however these limitations are dramatically decreasing (Royal Society, 2011, OECD, 2008) and studies that actively image the brain during specific classroom based tasks are beginning to be published.

The relationship between neuroscience and the psychological study of literacy and the acquisition of language in school children is the oldest and most robust (OECD, 2008) and researchers in the field now have a good understanding of the neurological correlates for language learning which can inform the choice and timing of pedagogical activities. There is a sensitive but not critical timing for learning a second language in the early years of education (Geake, 2009 & Royal Society, 2011).

Educational neuroscientific research into the neurological correlates for numeracy and mathematical ability is newer, although important evidence is already emerging about how the brain processes the different mathematical information and learns specific mathematical skills (Geake, 2009 & Royal Society, 2011).

Perhaps the most interesting and important questions that educational neuroscience is addressing are those concerned with learning difficulties. Educational neuroscience research has now provided a biological basis for the causes of Dyslexia. Diagnosis of the condition can be made based on neurological evidence and when twined with an improved understanding of how the brain processes word forms and sounds, neurological evidence can suggest effective methods of treatment. Similar work on Dyscalclia is already underway (Geake, 2009 & Royal Society, 2011).

Several authors (OECD, 2008, Geake, 2009, Royal Society, 2011) provide a thorough overview of the key findings from neuroscience generally and how they may apply to educational practice. A key general understanding is that no two human brains are the same. This may seem trite but even identical twins, which are the same genetically, show differences in their brain structure. This illustrates how much the brain is shaped by the environment it interacts with. The Royal Society 2011 writes:

“The brain is constantly changing and everything we do changes our brain…the brain has extraordinary adaptability, sometimes referred to as ‘neuroplasticity’”

The report goes on to explain that this is due to the processes that strengthen synapses and the effect is present throughout life. Contrary to early ideas of brain development we now know that the brain can adapt, change and therefore learn throughout life even into old age (OECD, 2008). Throughout life new synapses grow and are pruned but this process of pruning and growth is most prevalent at certain sensitive periods, from early childhood to late teens and early twenties. Individual experiences and environments shape individual brains (Royal Society, 2011).

While Individuals show differences in the structure of their brains this does not mean that there is evidence for individual learning styles of preferences. Due to the massive interconnectivity within the brain between individual neurons and between brain modules we know that information is processed across a wide variety of areas of the brain and that these areas are overlapping and interlinked. The ideas of learning styles –that learners learn exclusively through one sensory modality are false (Kratzig & Arbuthnott 2006). For example the areas of the brain that process speech overlap with those that process movement. The idea that an individual processes visual information in isolation from any other sense is another example of a neuromyth (Geake, 2009). In fact the interconnectedness of different sensory areas within the brain supports the notion of multisensory teaching i.e. approaching subject matter and skills through a variety of sensory inputs as this will enable more robust networks of neurones to form in the same manner as may be expected from repetition.

Geake (2009) defines the purpose of education as enabling the individual to gain transferable life skills from a variety of contexts. He also points out that learning in the form of memory formation of skills and concepts requires directed attention from working memory i.e. the engagement of the prefrontal cortex and the areas associated with working memory. Evidence shows that learners need to be guided. The brain can just as easily learn incorrect skills and content, but unlearning them is difficult because it requires the pruning of connections in the brain. Thus there are implications for inquiry based teaching methods and the idea that gifted students are able to teach themselves. Adult guidance and encouragement along with appropriate intellectual challenges should therefore be a central strategy for schools (Geake, 2009, Krishner et al., 2006).

Geake (2009) highlights the need for repetition within the learning environment of an individual. Repetition over time reinforces synaptic connections and allows the effective transference into long term memory. He illustrates this argument with the example of learning music. Hours of practice of the correct finger movements on an instrument allow the motor cortex to develop the neural networks that control the movement sequences. He does not advocate repetition in the sense of drilling exercises but suggests that spiral curriculums where individuals meet related concepts throughout their school experience, each time at a deeper and deeper level, along with lower pupil rations and immediate feedback from assessment to correct errors in processing would be beneficial for learners.

Educational neuroscience has also highlighted the interdependence of intellectual and physical wellbeing and much work has highlighted the importance of emotional wellbeing for learning (OECD, 2008). We now know how stress can inhibit learning because the centres of the brain that deal with emotion affectively inhibit the areas that help to regulate activity across the brain and are used in learning.

Conclusion

Modern theories of learning build firmly upon constructivist ideas (Samuels, 2009), but precisely because there is such a plethora of modern learning theories means that they cannot all be right (Geake, 2009).

Gardner’s (1983 & 1999) theory of multiple intelligences, a retelling of Plato’s ideal curriculum, is one such educational theory that must be qualified. It has been widely cited in educational policies and led to many misinterpretations such as labelling all children in a school as gifted by definition Geake (2009). Howard-Jones (2014) and Waterhouse (2006) argue that there is no neural evidence to support the idea of multiple intelligences but that there is evidence to suggest that there is a general cognitive ability underpinning all the possible dimensions of intelligence.

While massive differences exist in brain structure, the interconnectivity of the brain does point to a single underlying intelligence factor. Intelligence does have a genetic and environmental component in the same way that an individual heights do. Genetically, intelligence is brought about through the interaction between many genes; each of which have an individually small effect. The environment also has a role to play in unlocking the brains potential as diet, toxins and social interactions all up-regulate or down-regulate the effects of genes. A good social educational environment will enable an individual brain to reach it full intelligence potential (Geake 2009). 

At this stage educational neuroscience may not have the resolution to inform specifically about many aspects of classroom pedagogy (e.g. in science teaching) or classroom contexts but it is able to inform us about generalities that may inform curriculum planning on a whole school and regional basis. E.g. sleep patterns and gender differences, developmental differences, as well as serving to identify the psychological theories that may be most robust.

Obviously if we were to remove an individual’s brain we would soon find that they had lost the ability to learn altogether! Therefore is it unreasonable to be able to expect the workings of the mind to be understood through a deeper understanding of the brain?

The beauty of educational neuroscience is in its potential ability to underpin and constrain psychological theories of learning. Like Higgs with his Boson and the experimental physicists that validated its existence, educators are on the cusp of not only being able to identify a psychological intervention that works but also able to explain why it works, thanks to the evidence derived from educational neuroscience. To enable this we need better communication between the education and neuroscience communities.

Bibliography

Ansari, D., Coch, D., & De Smedt (2011) ‘Connecting Education and Cognitive Neuroscience: Where will the journey take us?’ Educational Philosophy and Theory. Vol. 43, No. 1.

Bruer, J. T., (1997) ‘Education and the Brain: A Bridge Too Far’ Educational Researcher Vol. 26, No. 8.

CERN (2015) http://press.web.cern.ch/press-releases/2012/07/cern-experiments-observe-particle-consistent-long-sought-higgs-boson accessed on 5th January 2015.

Geake, J. G. (2008) ‘Neuromythologies in education’ Educational Research. Vol. 50, No. 2.

Gardner, H. (1983) Frames of mind: The theory of multiple intelligences. New York: Basic Books

Gardner, H. (1999) Intelligence reframed. New York: Basic Books.

Geake, J. G. (2009) The Brain at School: Educational Neuroscience in the Classroom OUP.

Geake, J. & Cooper, P. (2003) ‘Cognitive neuroscience: Implications for education? Westminster Studies in Education.’ Vol. 26, No. 1.

Geary, D.C. (1998) ‘What is the function of mind and brain?’ Educational Psychology review. Vol. 10, No. 4.

Goswami, U. (2004) ‘Neuroscience and Education’ British Journal of Educational Psychology. Vol. 74, No. 1.

Goswami, U. (2006) ‘Neuroscience and Education: from research to practice?’ Nature Reviews Neuroscience. AOP.

Hebb, D.O. (1949) The Organisation of Behaviour. Wiley. New York.

Higgs, P. W. (1964) ‘Broken symetries and the masses of gauge bosons’ Physical Review Letters Vol. 13, No. 16.

Howard-Jones, P.A. (2014) ‘Neuroscience and education: myths and messages’ Nature Reviews Neuroscience. AOP. pp1-7

Howard-Jones, P.A., Ott, M., van Leeuwen, T., De Smedt, B. (2014) ‘The potential relevance of cognitive neuroscience for the development and use of technology-enhanced learning’. Learning, Media and Technology. AOP.

IBO (2015) http://xmltwo.ibo.org/publications/migrated/production-app.ibo.org/publication/169/part/1/chapter/2.html accessed on 19th January 2015.

Illeris, K. (2009) Contemporary theories of learning: Learning theorists in their own words. Routledge. London.

IMBES (2015) http://www.imbes.org accessed on the 20th January 2015.

Kratzig, G.P. & Arbuthnott, K.P. (2006) ‘Perceptual learning style and learning proficiency: a test of the hypothesis’ Journal of Educational Psychology. Vol. 98, No. 1.

Krishner, P.A., Sweller, J. and Clark, R.E. (2006) ‘Why minimal guidance during instruction does not work: an analysis of the failure of constructivist, discovery, problem-based, experiential and inquiry-based teaching.’ Educational Psychologist. Vol. 41, No. 2.

OECD (2008) Understanding the Brain: the Birth of a Learning Science. Paris. OECD.

Piaget, J. (1954) The Construction of Reality in the Child. New York: Basic Books.

Pritchard, A. (2009) Ways of Learning: Learning Theories and Learning Styles in the Classroom. 2nd Edition. Routledge.

Royal Society (2011) Brain Waves Module 2: Neuroscience Implications for Education and Lifelong Learning. London. Royal Society.

Samuels, B.M. (2009) ‘Can the differences between Education and Neuroscience be Overcome by Mind, Brain, and Education?’ Mind, Brain and Education. Vol. 3, No. 1.

Schenck, J. & Cruickshank, J. (2014) ‘Evolving Kolb: Experiential Education in the Age of Neuroscience’ Journal of Experiential Education. AOP pp1-23

Skinner,  B.F. (1958) ‘Reinforcement Today’ American Psychologist. Vol. 13, pp94-99

Varma, S., McCandliss, B. D. & Schwartz, D. L. (2008) ‘Scientific and Pragmatic Challenges for Bridging Education and Neuroscience. Educational Researcher. Vol. 37, No. 3.

Vygotsky, L.S.(1997) Educational Psychology. CRC Press.

Waterhouse, L. (2006) ‘Multiple Intelligences, the Mozart Effect, and Emotional Intelligence: A Critical Review’ Educational Psychologist. Vol. 41, No. 4