Author Archives: dmthomas90

About dmthomas90

Maths teacher in West London.

The truth about the UK’s anti-immigration vote

I could see the opinion pieces coming as soon as it became clear we’d voted for Brexit. There would be the indignant ones of course, but there would also be those that explained away the referendum result as a protest vote about immigration, and concluded that people had concerns that might be ‘valid’ and should therefore be ‘listened to’. They would write with clear undertones implying that Leave voters were racist, whilst proposing that they should be humoured for a while as an unfortunate but necessary concession given their recent electoral success.

This shows a fundamental misunderstanding of why people are motivated to vote based on immigration. It comes from people whose lives are largely going well, and whose families have a secure place in the world. They can see how immigration benefits them – through providing an extra flow of labour for the businesses they own, work in, or buy from. They enjoy multi-culturalism and the variety it brings to their surroundings. They are clearly benefiting from immigration, and so cannot understand why someone would be against it; except for racism.

But many people come from a very different starting point. They don’t understand how their country can have room for immigrants when it doesn’t seem to have room for their own children. The root of their concern is not immigration: it is the decline of their community and the failure of politics to offer a viable solution for turning it around. They are not worried about immigrants stealing their houses – they are worried about not having a house. They’re not worried about immigrants stealing their job – they’re worried about not having a job. They’re not worrited about immigrant children at the local school – they’re worried that the local school is failing. The problem is not immigration, the problem is scarcity and decline.

The politicians and commentators who now declare that they will start listening to people’s concerns about immigration need to understand where those concerns come from. They need to understand that people have developed concerns about immigration precisely because politics has failed to offer any other compelling solution to their problems. And it seems reasonable to believe, in the absence of any better idea, that a good way to ensure you can afford to have a house is to have fewer people wanting houses.

More than once during the referendum campaign I spoke to people my age who were voting leave not because of a deeply held view about the European Union, but because it was at least trying something. They had so little faith that our political parties would create any meaningful reforms, and they were so frustrated with the present outlook, that it just seemed worth the risk. These people are not racists. They are not misguided about Britain’s place in the world. They just think that it has to be better to try something than to try nothing.

And that’s why we do not need conciliatory gestures where politicians listen to people’s concerns about immigration. Firstly we do not need them because immigration is not the real problem, and it would push us to focus on net migration figures instead of the root causes of the problem. We do not need to give more airtime to the politics of immigration, or to the politicians who seek to hijack it for their personal gain. Rather we have a duty to stand unambiguously alongside immigrant communities and make it absolutely clear that they are and will continue to be welcome. They have fought in our wars, cared for our sick and kept our economy going through recession, and we have a moral duty to be vocal about that.

Secondly, we need to do, not to listen. It is listening that has led us here. In every campaign, every politician listens, and after every campaign they talk about listening more. A round of listening to concerns about immigration will not build houses, create jobs or improve schools. We know what the concerns are, we know what’s causing them, and we know what needs to be done. The question is whether we have the commitment to do it.

Our politicians should see last week’s referendum as a mandate to be more ambitious in their policy and challenge the unwritten rules of the status quo. They should be more determined to solve the rumbling problems that have been left unchecked for years. The referendum showed that people are ready to do radical things to try and improve our country. Politicians now need to follow suit.

Why Nicky Morgan needs to set a curriculum for teacher training

In many ways, this will be a Parliament of consolidation at the Department for Education. The policies of the last five years are coming into force, and Nicky Morgan will need to put her political energy into seeing them through. But there is one area that does need reforming, and it needs it now. It is possibly the biggest opportunity to improve education in this Parliament, and one that would last well beyond 2020. It doesn’t sound glamorous or exciting, and won’t make the headlines. But its potential should not be underestimated. Nicky Morgan should use this Parliament to set a curriculum for teacher training.

Teacher workload is already extremely high, as Morgan has publically recognised. This means that government can’t improve outcomes in a way that puts pressure on schools – there are no more gains to be made from making teachers work harder. Instead, government has to look for ways to help teachers be more effective; and it should start by making sure every new teacher gets the training they deserve.

When I did my teacher training we spent laughably little time learning about learning. We discussed what made a good lesson (in the lecturer’s opinion…) but rarely why those components were good. We were often given quasi-moral justifications, like the assertions that “it is better to discover things for yourself” or “children learn better when they work in groups”, but I cannot recall a single time I heard something explained in terms of how a child’s brain would be responding.

Read the rest of this article at Conservative Home.

Five lessons I’ve learned about genetics

I admit that I began reading to find evidence that supported my view. I was sure science would back me up. And then I, complete with a list of Harvard-format references, would win the next debate. The problem was that science didn’t agree with me. I could find pockets of supporting evidence, but the overwhelming consensus was that I was wrong. It made me phenomenally uncomfortable to see a consensus emerging that directly contradicted my beliefs about how the world should be. But ultimately, science is not about how the world should be. Science is about how the world is. And if I want to make it different, I need an accurate picture of how it is now.

This is a blog on reading about genetics – what I’ve learned, and what I want to do about it. The lessons are the things that struck me as a teacher most, and are largely based on reading about intelligence or other cognitive characteristics. I want to note up front that I am not an expert, and that writing this is part of my attempt to learn more. If and when I’ve made a mistake please let me know and I will rectify it as quickly as possible.

Lesson #1: Genetics explains much more of the variation between people than I was willing to accept
The most influential type of study for this blog is the twin study, which looks to explain the variation between people and attribute it to one of three categories of cause: the shared environment (factors that would be common to a pair of twins living in the same household and attending the same school); the non-shared environment (all other environmental factors); and genetics. Studies of cognitive ability tend to find that variation is 10-20% shared environment, 30-40% non-shared environment, and 50-60% genetics.

This was hard for me to accept. I wanted to believe that most variation is caused by things within our control. Instead the shared environment, of which school is only one part, explains under a fifth of the variation between people.

Before moving on to Lesson #2 it is important to stress that we are talking about variation here – not absolute levels. We can say that 50% of variation in intelligence is genetic in origin, we can say nothing about how much of your intelligence is caused by your genes.

Lesson #2: Environments change how genes are expressed
Your genetic code is fixed, but what you do with it isn’t. Geneticist Nessa Carey likens your genetic code to the script of a play, which is then interpreted extensively by the actors and director before becoming the performance that eventually appears on stage. Epigenetics is the study of these interpretations, which are as crucial to our biological functioning as the genetic code itself.

One thing we learn from epigenetics is that our environment shapes how we interpret our genetic code, and that these interpretations stick. Once we have scrawled annotations over our genetic script they will stay unless we actively rub them out – and when our children inherit our scripts they will find many of our annotations still in place.

Extreme or consistent environmental stimuli can create epigenetic modifications that change how your genes are expressed. For example, a stressful environment can lead to genes that control the production of cortisol (a stress hormone) becoming over-expressed, meaning that you become much more easily stressed in the future. Such a change will then persist, shutting off chunks of working memory and reducing executive function in years to come.

As many epigenetic modifications are heritable it is difficult for twin studies to separate their effect from the effect of genes themselves, and so it is possible that some of the causal impact of genetics is actually environmental in origin. As our ability to do more complex analysis with the genome itself increases we will no doubt find out whether this possibility means anything in practice.

Lesson #3: Environments correlate with genes
A tall child is more likely than a short child to be asked to try out for the basketball team. Where we may have a genetic propensity towards a certain area we tend to seek out (or be pushed towards) an environment that increases that propensity. This means that a small effect that begins life as just an inkling of interest or talent can easily grow into a specialised environment that exaggerates initially small effects. It is possible that correlations like this are responsible for a significant proportion of our genes’ impact. If we adapt environments, whether consciously or not, we will be magnifying genetic differences.

Lesson #4: Genetics does not determine outcomes
Twin studies observe the differences we see today and explain their origins. They do not have any say in how big these differences are or will be in the future. So the fact that 50% of variation in a characteristic is due to genetic causes today does not mean that it must be tomorrow. Nor does it mean that we must accept present levels of difference as necessary. The numbers we find in these studies are not natural constants.

Behavioural geneticist Robert Plomin says that studies tell you what is, not what could be. He likens our genetic understanding of intelligence to our understanding of weight. Whilst it is obviously the case that people can be genetically predisposed to put on more or less weight than each other, it is also true that with the right interventions almost anybody can achieve a healthy weight. The same is true for intelligence. There may be genetic predispositions, but we can make sure that everybody achieves an acceptable level by providing the right environment.

Lesson #5: Genetics assumes determinism
If a study assumes that all difference is caused by either genetics, the shared environment or the non-shared environment, then it is also making one other underlying assumption: that everything about a person has an external cause. It assumes that your intelligence or success is a function solely of your genes and your environment. But what if everything about us is not 100% deterministic?

I was hesitant to write this lesson down, for fear of seeming to criticise the entire body of work genetics has given us. Science has to operate by studying the relationship between cause and effect. I cannot challenge it for failing to account for independent free will. But I am nonetheless uncomfortable not accounting for it. I do not know nearly enough in this area to do anything more than speculate. But I do wonder whether the large influence of the non-shared environment, that bucket for everything we can’t put our finger on, may be substantially down to things like attitude and motivation that may not be fully caused by an external mechanism.

So what do I take from all this?
Firstly, that genetics plays an unquestionably big role in explaining who we are, and how our brains work. Even if some of the effect attributed to genes is in fact environmental in origin (due to epigenetics or gene-environment correlations) there is no doubt that genes have a huge influence.

But secondly, even though genes make us all different, they don’t determine our cognitive future. Long-term memory still has unlimited capacity; brain plasticity is still immense; and good teaching can still take advantage of this. Genes determine difference, but they’re no excuse for educational inequality.

We can’t afford to ignore the lessons from Chinese school

Imagine I told you there was a way to make our children perform 10% better in their exams after just four weeks of study. It involves changing a school’s timetable and teaching style, but still leaving plenty of room for leadership opportunities and extra-curricular activities. You’d expect to hear a clamour insisting that we roll this out in all schools immediately. Instead, Chinese School has earned itself a long list of critics. They don’t like Chinese education because it of its values. Or more precisely, because it values knowledge.

They argue that we should not be seeking to learn from Chinese teaching, despite its superior results. They concede that doing so would make our children learn more, but that this would come at too high a cost. Any improvement in our teaching of knowledge, they argue, would stop pupils being creative thinkers or challengers of the status quo. Yes, Chinese teaching may improve the learning of rules and information, but it does nothing to teach originality.

They seriously appear to be arguing that in a system in which 35% of 16 year olds failed English GCSE this year our problem is learning too much vocabulary, knowing the laws of grammar too well, and sticking too rigidly to the traditions of the literary canon. Otherwise why complain that Chinese teaching is good at helping pupils learn information?

Read the rest of this article at Conservative Home.

If we want to build character, we must challenge children

Character is the new fad in education. We all want to develop good character in our children, but the policy that achieves this has proven elusive. Proponents of every conceivable activity have queued up to explain how their pet project develops character (and so should get to dip their hands in the pot of government gold). But while many of these are perfectly good things, building our children’s character requires much more fundamental change.

So instead of looking for new projects to fund, let us ask a different question: why is there a deficit that needs to be made up in the first place?

The deficit exists because the core activity of schools – lessons – can become too easy and too self-consciously fun to need any character at all. Take resilience as an example. A child learns resilience by practising. They try tasks that are difficult, fail at them, and keep trying again. Eventually they learn that you do not need to give up when you face difficulty but can be successful if you invest enough effort.

Read the rest of this article at Conservative Home.

Be scared of the myth of big data

Last night I attended a lecture by Yuval Noah Harari – historian and author of the popular book ‘Sapiens’. Harari’s thesis is that human society is built on shared myths, and that without these we wouldn’t be able to organise ourselves into groups of more than a couple of hundred people. These myths are things like religion, social caste, political ideologies, and money.

During questions a member of the audience asked Harari what he predicted the next great myth would be. He answered, “Data.”

Harari’s contention is that with the growth of big data we are moving towards deifying quantitative information. Just as money has become something in which we unanimously place our trust (and therefore grant great power to otherwise valueless slips of paper) so we will begin to place our faith in data.

I can see signs of this myth emerging already, and I think it goes something like this: “if we get enough data we will be able to predict the future.”

The problem is that we won’t. There are some things data cannot tell us; there are limits to its power. Bigger sample sizes can take us so far, but there are certain frontiers that no sample size can help us cross. My fear is that if the data myth grows we will increasingly find ourselves basing decisions on statistical fallacies, and in a false sense of security end up with all of our eggs in a very unstable basket.

There are four reasons this myth is wrong:

The way we use statistical significance is logically flawed – so we cannot trust our results
Many social scientists use statistical significance tests to answer the question “Given the hypothesis is true, what is the probability of observing these results?”. However the question it should be used to answer is “Given these results have been observed, what is the probability that the hypothesis is true?”. Though similar, these questions are fundamentally different.

Ziliak & McCloskey (2008) liken this to the difference between saying “Given a person has been hanged, what is the probability they are dead?” (~100%) and “Given a person is dead, what is the probability they have been hanged?” (<1%). Although these questions sound similar they give completely different answers; and we could be using our statistical significance testing to make mistakes as big as these.

The laws of societies are not fixed – so we cannot predict the impact of our actions
We use data to estimate parameters about society and the economy, such as the relationship between inflation and unemployment, or between income inequality and crime. Although we can measure the parameters of these relationships at the moment, these parameters are not fixed. In fact they are highly prone to change whenever we alter something like technology or government policy.

So for example we cannot predict the impact of a new invention on society, because our prediction would be using parameters from the pre-invention world and not accounting for the invention’s impact on the deeper structures of society. This means that the times we most want to use data to predict the future – those times of significant change – are precisely those times when to do so would be utterly invalid.

No amount of data can capture the complexity of human systems – so we cannot make predictions beyond very short time horizons
Non-linear systems suffer from what mathematicians call “sensitive dependence on initial conditions”, popularly known as the butterfly effect. In a linear system measurement error is not a big problem. As long as a measurement falls within reasonable bounds of error we can make predictions within similarly reasonable boundaries because we know how much the error can be magnified. In a non-linear system, however, measurement error, even if utterly minuscule, can completely dominate a prediction. This is because the feedback loops in such a system continually transform and magnify the error until the resulting behaviour of the model is totally divorced from that of reality.

Human systems are so complex that we cannot measure them accurately. There will always be a measurement error, no matter how much data we obtain. They are also extremely non-linear. And this means that our predictions will quickly deviate from reality.

We don’t know how to handle uncertainty – so we cannot forecast probabilities
Our forecasting models are built on probabilities. We manage risk by assigning probabilities to all possible outcomes, based on historical data. What we can’t do is manage uncertainty. Uncertainty is different to risk because it describes a situation where the possible range of outcomes and/or their probabilities are not known. If we don’t know the probability of an outcome, or we don’t even know what the outcome is, then we can’t build it into a model. And if our models only take a subset of possible outcomes, and assume that the probabilities of the past are unchanged in the future, then the probabilities they forecast will be wrong.

3 Teaching Techniques That Made My 2014

At the start of this academic year I wanted to really put the theory of learning I knew into practice. Here are three teaching techniques I tried that I’ll be taking with me into 2015.

1. Interleave *everything*
We know that interleaving concepts and procedures is a desirable difficulty that improves learning. This year I’ve made it my aim to never teach a lesson that uses only one topic. Extension work doesn’t count: the main bulk of a lesson must include multiple concepts. In practice, this means that every set of questions I write includes applying the new thing being learned to problems involving other concepts from earlier on in the curriculum. I found this daunting at first – “what if it’s just too confusing for them?” – but I’ve found there’s tremendous power in my expectation that they can competently use everything I have taught them, at any time.

It’s also made the questions I write far richer and more interesting than ever before. A standard lesson on volume would include questions on upper and lower bounds, percentage changes to a volume when dimensions change by different percentages, and using Pythagoras’ Theorem to find missing dimensions before calculating a volume. These questions were the normal ones. They were not special extension questions for the top 20%. The message this broadcast, combined with the cognitive effect of the desirable difficulty, has made a noticeable impact on learning.

2. Spaced testing of *everything*
We know that spacing and testing are two of the most powerful tools in an educators’ arsenal. So I’ve made it my aim to space out testing of everything my students’ have studied.

The first way I’ve done this is through our departmental testing. This year we’re using low-stakes quizzes on each topic as a replacement for the half-termly summative tests we used to use. What’s great about this is that each topic has two quizzes: one taken at the end of the topic, and one a month later. This reinforces the expectation that students should remember what they’ve been taught, and incentivises them to revisit their learning when it will have the biggest impact on longer-term retention.

The second way is through an idea I’ve borrowed from Bruno Reddy and Kris Boulton at KSA. Long ago they told me about “Only 100% Will Do” starters: simple recall or procedural questions that had been previously studied. Now my students begin every lesson with an “Only 100% Will Do” sheet where they work on concepts from any past year group to make sure that they’re keeping up to speed.

3. Lightning fast in-class assessment
I have always been a big fan of in-class assessment, and could singlehandedly prop up the UK’s mini-whiteboard industry. But over the summer Joe Kirby introduced me to an app called Quick Key. It changed my life!

Quick Key is an optical scanning app for mobile phones. It works by scanning in students’ answer sheets to a multiple choice quiz, and giving you great analytics on your phone or in a spreadsheet. It’s also fast – I can scan a whole class set of answers in about a minute. This lets me pinpoint exactly how well the class are doing at a topic. I will discover that one mistake or misconception is bogging down the whole room, or that four students need extra support in this lesson and another five need extra challenge. The laser-like precision with which I can adapt during a lesson or plan the next one is having a big impact on my teaching.


 
Like any technique, these three have worked well because I made them a habit. We do these three things in the same way in almost every lesson. This consistency no doubt aids their effectiveness. But they are nonetheless three real techniques that put into practice the theory of learning we know to be so powerful.

There Is a Magic Bullet: how to reduce teacher workload in one fell swoop

Teaching is a tough job, with a tough workload. It isn’t easy, and it isn’t going to become easy either. But it can and should be manageable. Sadly in too many schools workload can become excessive, and can do so without improving teaching. But there is one policy that would reduce teacher workload and improve lessons in English schools:

Abolish the Quality of Teaching judgment in Ofsted inspections.

We should do this because:

It incentivises bad leadership
It is easier to tick QoT tick boxes than it is to actually improve results. It is easier to produce an evidence trail than it is to produce an impact. And it is easier to force teachers to work ever harder than it is to make their effort more productive. School leaders who face a grilling from external inspectors, be they Ofsted or otherwise, will find it much easier to create an illusion of performance and score well on QoT than to create actual performance and score well on Achievement.

So why not insist that all staff plan all lessons in detail and in writing on a school proforma? It might not improve learning, but it’s good way to demonstrate QoT. Why not make all staff mark all books every night in four different colours of pen? It might not improve feedback, but it’s a good way to demonstrate QoT. And before you know it, terrified leaders in many schools are imposing dreadful policies on their staff; because it’s easier to put on a show for an inspector than it is to improve results.

It makes teachers teach worse lessons
QoT judges teaching by how it looks, not by what it achieves. This makes teachers ensure teaching looks better, even if that doesn’t make it achieve more. So teachers spend their time on appearances. They buy books on 100 ways to make their lesson look outstanding, and trade chinese whispers about what Ofsted want to see. The time they would spend increasing the impact of their teaching they spend implementing new fads; not because they work, but because they look good.

It harms the quality of teaching – and causes excessive workload
The QoT grade doesn’t improve impact, just appearances. But even if some of this pressure does rub off on impact, that impact doesn’t come for free. There is a huge opportunity cost to everything that a teacher does. If they’re spending their time on appearances then they’re not spending their time improving learning. And that matters. It matters because teachers can’t work infinite hours, and so something has to give. When that something was improving the actual quality of teaching, not the illusory QoT, it’s children who lose out.

So instead we should lose the QoT grade. Judge schools on the impact they have, not on how they look. Then we can lose the smoke and mirrors policies that look good but make real improvement harder. Leaders and teachers will have one aim – to improve the impact they have on children. And there will be no perverse incentive to distract them from it.

This isn’t a blog about private schools

But it’s not because I couldn’t write one. I have quite strong views on private schools, and I even think they’re well-reasoned. But I’m not going to write about them.

Why?

Because this debate doesn’t matter. Will forcing reluctant private schools to share their theatres change education? Would an extra £150 million for the DfE budget really improve the system? No.

One day we might reach the point where the next most important change is reform of private schools, in which case we can have this debate. But until then we should focus on bigger things. Like:

  • Over a third of schools either Require Improvement or are Inadequate
  • Over a third of 16 year-olds don’t get at least 5 A*-C with English and Maths
  • Our alternative provision fails almost everyone who needs it
  • Teacher Training fails to teach you about how people learn
  • CPD tells teachers piles of rubbish pseudo-science
  • Teachers spend much of their time doing things without an evidence-base to please various interest groups

Sharing theatres might be nice, but it won’t solve these.

Let’s postpone the debate until we have.