About logicalincrementalism

Interested in systems, neurobiology, education and developmental disorders.

apprentice without a sorcerer

Cummings’ essay Some Thoughts on Education and Political Priorities highlights his admiration for experts, notably scientists, but this doesn’t prevent him making several classic novice errors. These errors, not surprisingly, lead Cummings to some conclusions contradicted by evidence he hasn’t considered. I’ve focused on four of them.

oversimplifying systems

Cummings knows that systems operate differently at different levels, and although all systems, as part of the physical world involve maths and physics, you can’t reduce all systems to maths and physics (p.18). But his preoccupation with maths and physics, and lack of attention to the higher levels of systems suggest he can’t resist doing just that. In his essay maths is mentioned 473 times (almost 2 mentions per page) and physics 179 times. Science gets 507 references and quantum 238. In contrast, the arts get 8 mentions and humanities 16. Ironically, given his emphasis on complex systems, Cummings seems determined to view complex knowledge domains like education, politics, the humanities and arts, only through the lenses of maths, physics and linear scales.

Cummings’ first degree is in history, but he knows a lot of scientific facts. How deep his understanding goes is another matter. He opens the section on a scientific approach to teaching practice with the famous ‘Cargo Cult’ speech in which Richard Feynman accused educational and psychological studies of mimicking the surface features of science but not applying the deep structure of the scientific method (p.70). Cumming’s criticism is well-founded; evidence has always influenced educational practice in the UK, but the level of rigour involved has varied considerably. Ironically, Cummings’ appeal to scientific evidence then itself sets off down the cargo-cult route.

misunderstanding key concepts: chunking vs schemata

Cummings claims “experts do better because they ‘chunk’ together lots of individual things in higher level concepts – networks of abstractions – which have a lot of compressed information and allow them to make sense of new information (experts can also use their networks to piece together things they have forgotten)” (p.71).

‘Chunking’ occurs when several distinct items of information are perceived and processed as one item. The research e.g. Miller (1956), De Groot (1965) and Anderson (1996), shows it happens automatically after groups of low-level (simple) items with strongly similar features have been encountered very frequently, e.g. Morse code, words, faces, chess positions. I’ve not seen any research that shows the same phenomenon happening with information that’s associated but complex and dissimilar. And Cummings doesn’t cite any.

Information that’s complex and dissimilar but frequently encountered together (e.g. Periodic Table, biological taxonomy, battle of Hastings) forms strong associations cognitively that are configured into a schema. What Cummings describes isn’t chunking; it’s the formation of a high level schema. Chunks are schemata, but not all schemata are chunks.

Cummings is right that experts abstract information to form high level schemata, but the information isn’t compressed as he claims. The abstractions are key features of aspects of the schema e.g. key features of transition metals, birds or invasions.  I can just about hold all the key features of birds in my working memory at once, but not at the same time as exceptions (e.g ostrich, penguin) or features of different bird species. The prototypical features make it easier to retrieve associated information, but it isn’t retrieved all at once. If I think about the key features of birds, many facts about birds and their features spring to mind, but they do so sequentially, not at the same time. The limitations of working memory still apply.

The distinction between chunking and schema formation is important because schemata play a big part in expertise e.g. Schank & Abelson (1977) and Rumelhart (1980). Despite their importance, Cummings refers to schemata only once, when he’s describing how his essay is structured (p.7). The omission is a significant one with implications for Cumming’s model of how experts structure their knowledge.

experts vs novices

Experts in a particular field derive their expertise from a body of knowledge that’s been found to be valid and reliable. They construct that knowledge into schemata, or mental models. New knowledge can then be incorporated into the schemata, which might then need to be configured differently. Sometimes experts disagree strongly, not about the content of their schemata, but about how the content is configured.

The ensuing debates can go on for decades. A classic example is the debate between those who think correlations between intelligence test scores indicate that intelligence is a ‘something’ that ‘really exists’, and those who think the assumption that there’s a ‘something’ called intelligence, shapes the choice of items in intelligence tests, so correlations should come as no surprise (see previous post). Another long-standing debate involves those who think universal patterns in the structure of language mean that language is hard-wired in the brain, versus others who think the patterns emerge from the way networks of neurons compute information.

Acquiring key information about an unfamiliar knowledge domain takes time and effort, and Cummings has obviously put in the hours. What’s more challenging is finding out how domain experts configure their knowledge – experts often take their schemata for granted and don’t make them explicit. Sometimes you need to ask directly (or be told) why knowledge is organized in a certain way, and if there are any crucial differences of opinion in the field.

Cummings doesn’t seem to have asked how experts structure their knowledge. Instead, he appears to have squeezed knowledge new to him (e.g. chunking) into his own pre-existing schema without checking whether his schema is right or wrong. Or, he’s adopted the first schema he’s agreed with (e.g. genes and IQ). He admits to basing his genes/IQ model largely on Robert Plomin’s Behavioural Genetics and talks by Stephen Hsu. He dismisses the controversies and takes Plomin and Hsu’s models for granted.

evaluating evidence

There are references to the scientific method in Cummings’ essay but they’re about data analysis, not the scientific method as such. A crucial step in the scientific method is evaluating evidence – analysing data for sure, but also testing hypotheses by weighing up the evidence for and against. This process isn’t about ‘balance’ – it’s about finding flaws in methods and reasoning in order to avoid confirmation bias.

But Cummings repeatedly accepts evidence in support of one thing or against another, without questioning it. I’d suggest he can’t question much of it because he doesn’t know enough about the field. Some that caught my eye are:

  • Assuming hunter-gatherers’ knowledge is “based on superstition (almost total ignorance of complex systems)” (p.1). Anthropology that might claim otherwise, is like other social sciences, summarily dismissed by Cummings.
  • Unsubstantiated claims such as “Aeronautics was confined to qualitative stories (like Icarus) until the 1880s when people started making careful observations and experiments about the principles of flight” (p.21). Da Vinci, Bacon, Montgolfiers, Caley? No mention.
  • Attributing European economic development between 14th and 19th centuries to ‘markets and science’ and omitting the role of the Reformation, French Revolution, or Enclosure Acts (p.108).
  • Uncritical acceptance of Smith’s and Hayek’s speculative claims about the benefits of markets (p.106).
  • Overlooking systems constraints on growth – in corn yields, computing power etc. (pp.46, 231-2). No mention of the ubiquitous sigmoid curve.
  • Overlooking the Club of Rome’s Limits to Growth when discussing shortage and innovation (p.112).
  • Emphasising the importance of complex systems with no mention of systems theory as such (e.g. Bertalanffy’s general systems theory).
  • Ignoring important debates about construct validity e.g. intelligence and personality (p.49).

not just wrong

People are often wrong about things and usually a few minor errors don’t matter. In Cummings’ case they matter a great deal, partly because he’s so influential, but also because even tiny errors can have huge consequences. I chose the example of chunking because Cummings’ interpretation of it has been disproportionately influential in recent English education policy.

Daisy Christodoulou in Seven Myths about Education (2014) takes the assumption about chunking a step further. She’s right that chunking low-level associations such as times tables allows us to ‘cheat’ the limitations of working memory, but wrong to assume (like Cummings) high-level schemata do the same. And flat-out wrong to claim “we can summon up the information from long-term memory to working memory without imposing a cognitive load.” (Christodoulou p.19, my emphasis). Her own example (23,322 x 42) contradicts her claim.

Christodoulou’s claim is based on Kirschner, Sweller & Clark’s 2006 paper ‘Why minimal guidance during instruction does not work’. The authors say; “The limitations of working memory only apply to new, yet to be learned information that has not been stored in long-term memory. New information such as new combinations of numbers or letters can only be stored for brief periods with severe limitations on the amount of such information that can be dealt with. In contrast, when dealing with previously learned information stored in long-term memory, these limitations disappear.” (Kirschner et al p.77).  The only evidence they cite is a 1995 review paper proposing an additional cognitive mechanism “long-term working memory”.

I have yet to read a proponent of Kirschner, Sweller & Clarke’s model discuss the well-known limitations of long-term memory, summarised here. Greg Ashman for example, following on from a useful summary of schemata, says;

One way of thinking about the role of long-term memory in solving problems or dealing with new information is that entire schema can be brought readily into working memory and manipulated as a single element alongside any new elements that we need to process. The normal limits imposed on working memory fall away almost entirely when dealing with schemas retrieved from long-term memory – a key idea of cognitive load theory. This illustrates both the power of having robust schemas in long-term memory and the effortlessness of deploying them; an effortlessness that fools so many of us into neglecting the critical role long-term memory plays in learning”.

Many with expertise as varied as English, history, physics or politics, have enthusiastically embraced findings from cognitive science that could improve the effectiveness of teaching. Or more accurately, they’ve embraced Kirschner, Sweller and Clarke’s model of memory and learning.  Some of the ‘cog sci’ enthusiasts have gone further. They’ve taken a handful of facts out of context, squeezed them into their own pre-existing schemata, and drawn conclusions that are at odds with the research. They’ve also assumed that if an expert in ‘cog sci’ makes a plausible claim it must be true, but haven’t evaluated the evidence cited by the expert – because they don’t have the relevant expertise; cognitive science is a knowledge domain unfamiliar to them.

Nevertheless objections to the Kirschner, Sweller and Clarke model are often dismissed as originating either in ideology or ignorance. Ironic, as despite emphasising the importance of knowledge, evidence and expertise, many of the proponents of ‘cog sci’ are patently novices selecting evidence to support a model that doesn’t stand up to scrutiny. Murray Gell-Man is right that we need people who can take a crude look at the whole of knowledge (p.5), but the crude look should be one informed by a good grasp of the domains in question.

In 1797, Goethe published a poem entitled Der Zauberlehrling (Sorcerer’s Apprentice). It was a popular work, and became even more popular in 1940 when animated as part of Disney’s Fantasia, with Mickey Mouse playing the part of the apprentice who started something he couldn’t stop. The moral of the story is that a little knowledge can be a dangerous thing. Cummings has been portrayed as a brilliant eccentric and/or an evil genius. I think he’s an apprentice without a sorcerer.

references

Anderson, J (1996) ACT: A simple theory of complex cognition, American Psychologist, 51, 355-365.

Christodoulou, D (2014).  Seven Myths about Education.  Routledge.

de Groot, A D (1965).  Thought and Choice in Chess.  Mouton.

Kirschner, PA, Sweller, J & Clark, RE (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, 41, 75-86.

Miller, G (1956). The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information, Psychological Review, 63, 81-97.

Rumelhart, DE (1980). Schemata: the building blocks of cognition. In R.J. Spiro et al. (eds) Theoretical Issues in Reading Comprehension.  Lawrence Erlbaum: Hillsdale, NJ.

Schank, RC & Abelson, RP (1977). Scripts, Plans, Goals and Understanding: an Inquiry into Human Knowledge Structures.  Lawrence Erlbaum: Hillsdale, NJ.

 

 

 

not all in the genes

Dominic Cummings’ 2013 essay Some Thoughts on Education and Political Priorities reveals his keen interest in the implications of intelligence research for education. His Endnote “Intelligence, IQ, genetics, and extreme abilities” (p.194) runs to 17 pages.

General Intelligence

If I’ve understood Cummings’ model of intelligence correctly, it goes like this: General Intelligence (‘g’) is a trait that’s largely genetically determined and can be measured as IQ. If we could identify the genes involved, we could spot those with high cognitive ability who are needed to find the solutions to the complex problems facing us.

There’s certainly robust evidence that cognitive ability is largely genetically determined (by multiple genes), remains stable, and is a good predictor of lifetime achievement (p.197). We do need people with high IQs to work on solutions to world problems. And children with high IQs need an appropriate education. I share Cummings’ frustration that DfE officials prioritised their notion of equality over the need to develop talent (p.64). But his model is also flawed at several levels. It includes three key components that are worth examining in more detail;

  • A hypothetical human trait – general intelligence
  • The correlation between factors within intelligence tests
  • IQ

Intelligence

Towards the end of the 19th century, researchers got very interested in measuring human characteristics. Some, such as height and weight, were easy to measure, but others – like ‘physiognomy’ or ‘eventuality’- were trickier because it wasn’t obvious what the features of ‘physiognomy’ or ‘eventuality’ were.

PhrenologyPix

You can of course measure any human characteristic you fancy. You decide what the features of ‘adhesiveness’ or ‘ideality’ are and how to measure them, and hey presto! you’ve measured ‘adhesiveness’ or ‘ideality’. There might of course be some disagreement about the features of ‘adhesiveness’ or ‘ideality’ – or even about their very existence.

Also in the late 19th century, industrialised economies were desperate for a literate, numerate, ‘intelligent’ workforce. That requirement was one of the drivers for mass education.

In his 1904 review of measures of intellectual ability, the psychologist and statistician Charles Spearman decided intellectual ability could be measured using performance in: Classics, Common Sense, Pitch Discrimination, French, Cleverness, English, Mathematics, Pitch Discrimination among the uncultured, Music, Light Discrimination and Weight Discrimination (Spearman p.276). Essentially, he defined intelligence in terms of intellectual abilities. More recent measures such as Verbal Comprehension, Visual Spatial, Fluid Reasoning, Working Memory, and Processing Speed (Wechsler Intelligence Scale for Children – V) define intelligence in terms of cognitive abilities.

‘g’

Spearman went a step further. The positive correlations between the factors in his test convinced him “that there really exists a something that we may provisionally term ‘General Sensory Discrimination’ and similarly a ‘General Intelligence’” (Spearman p.272). And the correlations between scores in cognitive ability tests have convinced others of the existence of a ‘something’ we may provisionally term ‘general intelligence’.

I haven’t been able to find out if Spearman used ‘g’ to refer to the correlation between factors, or the hypothesized ‘something’, or both. Whichever it was, critics were quick to point out that correlation doesn’t indicate causality. A positive correlation between Spearman’s factors exists, certainly. Whether ‘general intelligence’ exists other than as a folk concept is another matter.

Critics also pointed out the circularity in Spearman’s argument. Intelligence tests were assumed to measure intelligence, but because no one knew what intelligence actually was, the tests also defined intelligence – even if they varied considerably. Spearman’s measures were very different to Binet & Simon’s , and neither bears much resemblance to the WISC, or to Raven’s Progressive Matrices. As Edwin Boring put it in 1923, “intelligence is what the tests test”.

IQ

In 1912, the German psychologist William Stern developed the concept of IQ –Intelligenzquotient. IQ (initially mental age divided by chronological age, expressed as a percentage) tells you how an individual’s test score compares to the average for the population. But the criticisms of ‘intelligence’ also apply to IQ. IQ tests undoubtedly measure aspects of cognitive ability, but we don’t know whether or not they measure a genetically determined trait we may call ‘intelligence’. Or even if such a trait exists.

Advocates for general intelligence haven’t take the criticisms lying down. Cummings quotes Robert Plomin’s dismissal of the circularity criticism: “…laypeople often read in the popular press that the assessment of intelligence is circular – intelligence is what intelligence tests assess. On the contrary, g is one of the most reliable and valid measures in the behavioral domain” (p.195).

It’s worth noting that Plomin uses g and intelligence interchangeably, even though intelligence is a hypothesized trait and he refers to g as a measure. There’s no doubt that g is reliable and valid when measuring some cognitive abilities. Whether those abilities represent a genetically determined trait we may term ‘intelligence’ is another matter – which Plomin goes on to admit: “It is less clear what g is and whether g is due to a single general process, such as executive function or speed of information processing, or whether it represents a concatenation of more specific cognitive processes…” It’s also worth noting that Plomin attributes the circularity argument to laypeople and the popular press, rather than to generations of doubting academic critics.

The implicit assumptions made by those emphasizing the importance of g and IQ, are important because they can have unwanted and unintended outcomes. One is that correlations between factors might hold true at population level, but not always at the individual level. Deidre Lovecky, who runs a resource centre in Providence Rhode Island for gifted children with learning difficulties, reports in her book Different Minds having to pick ‘n’ mix sub-tests from different assessment instruments because individual children were scoring at ceiling on some sub-tests and at floor on others. How intelligent are those children? Their IQ scores wouldn’t tell us.

Also, hunting for hypothetical snarks can waste a huge amount of time and resource. It’s taken over a century for us not to be able to find out what ‘g’ is. Given the number of genes involved ,you’d think by now people would have abandoned the search for a single causal factor. It’s a similar story for chronic fatigue syndrome (‘neurasthenia’ – 1869) and autism (‘autistic disturbances of affective contact’ – 1943); both perfectly respectable descriptive labels, but costly red herrings for researchers looking for a single cause.

Characteristics, traits, states, and behaviours

What convinces Cummings that intelligence, g and IQ are ‘somethings’ that really exist is evidence from behavioural genetics. Scientists working in this field have established beyond reasonable doubt that most of the variance in human intelligence, however you measure it, is accounted for by genetic factors. That shouldn’t be surprising. Intelligence is almost invariably defined in terms of cognitive ability, and cognitive ability emerges from characteristics such as visual and auditory discrimination, reaction time, and working memory capacity, all biological mechanisms largely determined by genes.

But not all human characteristics are the same kind of thing. Some characteristics such as height and weight are clearly physical and are easily measured. For obvious reasons genes account for most of the variance in physical characteristics.

The term trait applies to physical characteristics but also to stable dispositional characteristics. Disposition refers to people’s behavioural tendencies – how introvert or extravert they are, what they like and dislike, do and don’t do etc. The evidence from behavioural genetics suggests that genes also account for most of the variance in stable traits.

States are also dispositional characteristics, but they’re temporary and usually emerge in response to environmental factors. So Joan might be extravert and prone to angry outbursts, and Felicity might be introverted and timid, but both of them are likely to become anxious if fire breaks out in the office they share. Their reactions to the fire are largely genetically determined, but are triggered by an environmental event.

Behaviours are things people do. They are undoubtedly influenced by genetic makeup, but occur primarily in response to environmental factors, because that’s the main function of behaviour. Joan might try to extinguish the fire and Felicity might take the nearest exit, but both behaviours would be in response to specific circumstances. If we were pre-programmed automatons, the human race wouldn’t have lasted very long.

In support of his genes-determine-intelligence argument Cummings cites Stephen Hsu, a physicist turned behavioural geneticist, who claims that much of the nature/nurture debate has been settled. Hsu’s right in respect of the genetic influence on traits. But that still leaves plenty of room for the environmental influence on states and behaviours. That has significant implications for Cummings’ model of education.

Genes, intelligence and education

The principal components of Cummings’ model of education are genes, intellectual ability, effective teaching, and exam results. But in real life many other factors impact on educational outcomes. Take Ryan, Joan’s nephew, for example.

Ryan lives with his mum, a single parent. She cares for her father, disabled following a work accident, and her mother who has complex health problems. They live in a former industrial town, currently in economic decline. Ryan’s parents’ relationship broke down due to the financial and time pressures on the family.

Ryan has average intellectual ability, but episodes of glue ear when he was younger left him with a slight speech and language delay. He struggled with maths and reading and was often reprimanded for not following instructions. He loved physical activities, but the regulatory education framework required Ryan, as a child who was ‘falling behind’, to do less practical activity and more arithmetic and phonics.

Ryan soon began to disengage with school. He was referred for speech and language therapy and to the educational psychologist, but both had lengthy waiting lists. By his teens, Ryan had a low reading age, was making slow progress academically, and skipped school whenever he could. His mum couldn’t find paid work to fit around caring for her parents, and was on medication for anxiety and depression.

Genes undoubtedly account for some challenges faced by Ryan and his family; his family’s health, his intellectual ability, and quite likely his glue ear. But environment plays a significant role in the shape of income, diet, viral infections, and national economic, social, and education policy. So do life events (so commonplace their importance is often overlooked); where the family happens to live, grandfather’s accident, parents’ break-up, which school is closest to home.

Then there are specific behaviours on the part of Ryan, his parents, grandparents, teachers – and government ministers. Specific behaviours are often framed as a ‘choice’, but that choice is often highly constrained by circumstances.

Choose your metrics

Cummings measures the effectiveness of the education system by exam results (although he questions the quality of the exams). Exam results are positively correlated with IQ, and IQ is largely genetically determined. So his choice of metric means Cummings places a disproportionate emphasis on influence of genes on educational outcomes.

Of course there’s nothing wrong with IQ or exam results as metrics. If you want to find someone with good cognitive abilities, a modern intelligence test can identify them. If you want candidates with a mathematical ability of at least GCSE level, check out GCSE maths results.

But the choice of a single metric for something as complex as an education system shows an inadequate understanding of complex systems. And begs the question of what education is about. If quality of life in local communities were the key metric, the education system would look very different. By bizarre coincidence, the gene pool of large populations produces people with a wide range of abilities and aptitudes, just what those populations need in order to thrive. That wide range of abilities and aptitudes should be cultivated. Cummings’ choice of metric means the exam-results tail wagging the quality-of-life dog.

Accommodating a wide range of abilities and aptitudes doesn’t equate to having ‘low expectations’ for those with less than stellar exam results. There’s no virtue in people doing jobs they don’t enjoy and aren’t good at, and careers aren’t set in stone. An academic high flyer might become a superb potter, and a former train driver might get a PhD. If the education system doesn’t offer such opportunities, it’s to the detriment of all us.

Cummings would no doubt argue that his claims about education are evidence-based; he cites evidence for pedagogical approaches that improve exam results. But his starting point is an assumption that what the world needs is academic high flyers with high IQs and ‘extreme abilities’. He looks right past those with other abilities and aptitudes essential for communities to keep functioning. And those, who through no fault of their own, can make only a very limited contribution to their communities, but like all of us have a right to a decent quality of life.

Cummings first chooses his metric and then chooses supporting evidence, but only the evidence in support of it. Ironically history is littered with examples of academic high flyers with high IQs and ‘extreme abilities’ causing chaos for the rest of us. Cummings’ use of evidence is the subject of the next post.

reference

Spearman, C.  (1904).  ‘General Intelligence’ objectively determined and measured.  The American Journal of Psychology, 15, 201-292.

acknowledgements

Image from People’s Cyclopedia of Universal Knowledge (1883) via Wikipedia https://en.wikipedia.org/wiki/Phrenology

 

 

Dominic Cummings on education

Dominic Cummings has become a highly influential figure. He steered the UK’s education system towards a ‘knowledge curriculum’, persuaded many who voted in the 2016 referendum that they wanted the UK to leave the EU, and is now well on the way to ensuring that Brexit gets done – whatever that entails.

In 2013 Cummings published online an essay entitled Some Thoughts on Education and Political Priorities. His thoughts extend to nearly 250 pages.  I had a couple of goes at reading them at the time, but was fazed by the plethora of references to mathematicians and physicists. My rusty A level maths and even more rusty O level physics weren’t quite up to checking them out.  Following Cummings’ spectacular return to public life, I scrolled past them and found myself in more familiar territory.  This is the first of three posts, on Cummings’ views of education, intelligence, and expertise.

An Odyssean Education

Cummings isn’t happy with education systems. He complains that students aren’t taught about some fundamentally important ideas, so political leaders lack them too, which explains poor political decisions. He believes the ideas could go a long way to resolving the global crises facing us, so it’s imperative they’re taught in schools and universities. He’s particularly interested in the education of people with a high IQ.

Cummings refers to Neitzsche’s distinction between ‘Apollonian’ thinkers using logical analysis and ‘Dionysians’ who use intuition and synthesis. The physicist Murray Gell-Man suggested a third group – ‘Odysseans’ – who “combine the two predelictions”, look for connections between ideas, and take a “crude look at the whole” (p.5). As Cummings puts it “An Odyssean curriculum would give students and politicians some mathematical foundations and a map to navigate such subjects without requiring a deep specialist understanding of each element” (p.7).  He’s right about the map. Human knowledge has increased exponentially over the past century, so in-depth specialisms have become the order of the day. The best anyone could currently achieve is a ‘crude look at the whole’ but that crude look is essential if we are to understand the challenges confronting us.

Cummings structures his Odyssean curriculum as a “schema of seven big areas” (p.7) sketched out on page 2:

  1. Maths and complexity
  2. Energy and space
  3. Physics and computation
  4. Biological engineering
  5. Mind and machine
  6. The scientific method, education, training and decisions
  7. Political economy, philosophy, and avoiding catastrophes.

The essay includes 15 Endnotes on specific topics, and a reading list. In this post, I focus on education, addressed in Chapter 6.

Uniformity vs diversity

Cummings is critical of an education policy that aims for increased uniformity of achievement, based on the assumption that all students have the same potential, and would reach it if aspirations were raised and equal opportunities provided. Cummings’ model in contrast, assumes students don’t have the same potential because differences in ability are largely genetic in origin. He thinks more effective teaching will raise attainment levels for all, but will also widen the attainment gap (pp.74, 83). In my view, both models are wrong due to flaws in their implicit starting assumptions. Here’s why:

Human beings have been ‘successful’ in the evolutionary sense, in part because speech enables us to communicate complex information to each other. To survive and maintain good quality of life, everyone doesn’t need to know everything, but we each need access to the expertise of farmers, plumbers, electricians, doctors, lawyers, poets and dancers to name but few.

What enables populations to adapt to changing environments is genetic diversity. And genetic diversity produces people with the diverse abilities, aptitudes and interests that enable communities to adapt to changing circumstances. Communities thrive, not because of their uniformity, but because of their diversity. A good general education is important for everyone because we each need to know how the world works, but the last thing we need is for everyone to be the same.

The diversity does indeed mean that improving teaching would result in larger gaps in attainment – but only if you measure attainment on a linear scale such as exam results or IQ. Cummings is right that we desperately need people with high IQs who can do the maths required to model complex systems, and politicians who understand what’s being modelled. But our society couldn’t function if it consisted entirely of people who were a whiz at complex equations and/or political decision-making; we need people with a wide range of abilities, aptitudes and interests to make life sustainable and worth living.

Uniformity appeals to policy-makers because one-size-fits-all policies look like they’ll save money.  A diversity narrative is often used to make uniformity more palatable. But diversity in communities doesn’t only make life more interesting and colourful, it’s essential for our biological and economic survival and well being.

Aptitude

Genetic diversity provides communities with the wide range of abilities, aptitudes and interests they need to thrive. Ironically, the suitability of an education to aptitude (what someone is good at) has been embedded in English education law since at least 1944, but has received scant attention since the advent of the national curriculum and standardised testing.

Paying attention to aptitude doesn’t mean every student needs a personalised education programme, nor that schools should undertake vocational training. But developing the inherent qualitative variation in aptitude would mean the ensuing quantitative variation in exam scores became less important. Gaps in academic achievement matter only to societies that accord a disproportionately high status to professions requiring academic skills.

For example, doctors and lawyers are generally well paid and have high social status. The pay and social status of train drivers and electricians is generally lower. But train drivers and electricians are no less essential to a functioning community. Cummings lauds scientists, and is pretty dismissive of doctors and lawyers, but the people who maintain the complex infrastructure of the developed world don’t feature at all in his model of education, other than often being on the wrong side of the IQ bell curve.

Cummings’ proposals

To fix the problems with the education system, Cummings proposes (pp.69-83):

  1. Largely eliminate failure with the basics in primary schools
  2. Largely eliminate failure with the basics in secondary schools
  3. A scientific approach to teaching practice
  4. Maths for most 16-18
  5. Specialist schools from which all schools (and Universities) can learn
  6. Web-based curricula, MOOCs, and HE/FE
  7. Computer Science and 3D printers: bits and atoms, learning and making
  8. Teacher hiring, firing and training
  9. Prizes
  10. Simplify the appallingly complicated funding system, make data transparent and give parents a real school choice.

Most of his criticisms of the education system are valid ones, but criticism is the easy bit – it’s more challenging to come up with alternatives. Cummings generates ideas like they’re going out of fashion, but almost invariably overlooks context; notably what caused the problems, and the implications of his ideas being implemented. Here are some examples:

Maths     For Cummings ‘the basics’ are English, Maths and Science, with Maths the sine qua non because it provides the ‘language of nature’ (p.63). His proposal that 16-18 year-olds continue to study ‘some sort of Maths course’ (p.75) was implemented in 2015 in the form of students being required to re-sit Maths and English GCSEs if they got lower than a C grade. As far as I’m aware the scheme wasn’t piloted, placed a huge burden on an FE sector already pared to the bone, and many students found their career plans stalled due to an arbitrary and unnecessary requirement.

Reading     The UK’s achievement in reading is contrasted with that of Finland (p.69), but overlooks the fact that Finnish orthography is highly transparent (almost 1-1 correspondence between graphemes and phonemes) whereas English orthography is highly opaque.

Specialist schools     Cummings has high hopes for specialist schools (pp.75-77) but doesn’t mention their introduction in the 1988 Education Reform Act, or that under New Labour most state secondaries became specialist schools. Evaluations showed the consequent small improvement in exam results was as likely due to the additional funding, rather than specialist status as such. There doesn’t appear to have been a subsequent surge in superb scientists or brilliant politicians.

Teacher hiring, firing, and training     For Cummings “real talent is rare, mediocrity ubiquitous” (p.81). He would recruit academic high flyers, pay them well, get “roughly averagely talented teachers” to use Direct Instruction scripts and allow head teachers to sack the ones who still didn’t make the grade. He doesn’t mention working conditions or why teacher retention is so low.

Cummings also claims “managing schools is much easier than being a brilliant maths teacher and requires only the import of competent (not brilliant) professional managers from outside the education world” (p.83).  The transferable management skills hypothesis has been widely tested since the 1980s and been found seriously wanting.

Lectures     We’re told “students remember little from traditional lectures” (p.72). That might because traditionally, lectures formed only the framework for the students’ learning. Traditionally, students were expected to do further reading. And the ‘proven’ Oxbridge tutorial system is not as Cummings claims, limited to Oxford and Cambridge (p.78). It’s been in use in every university I’ve been involved with from the 1970s to the present. Maybe I’ve just been lucky.

Funding     The education funding system certainly needs rationalising, but costs vary across geographical areas, so who decides what a “flat per pupil amount” with “as few tweaks as possible” (p.81) means?

Parent choice     The other things described above … could be done even if one disagrees with the idea of a decentralised system driven by parent choice and prefers the old hierarchical system run by MPs, Unions, and civil servants” (p.83). Cummings appears completely unaware that the ‘old hierarchical’ system was decentralized and run by local authorities, school governors (including parents) and head teachers. And would probably have stayed that way if it hadn’t been deliberately centralized relatively recently by the Thatcher and subsequent governments.

Data transparency     Few would want to “define success according to flawed league table systems based on flawed GCSEs” but if “private schools have defined success according to getting pupils into elite universities” (p.82) where does that leave the bulk of the population? We’re not all going to get into elite universities – if we did, they wouldn’t, by definition, be elite.

Scientific evidence     Cummings is right that an evidence-based approach to education is vital, but has a touching faith in randomized controlled trials (RCTs) (p.64). The medical community’s objections to RCTs was not, as Cummings claims, because their expertise would be challenged by data, but because individual patients don’t always share the features of a large population. The same is true for school pupils.

Cummings follows Feynman in accusing educational researchers of ‘Cargo Cult’ science – mimicking the surface features of scientific research but not applying its deep structure (p.70). Regrettably, deep structure is noticeable by its absence from the hotch-potch of findings about cognition, lectures, tutorials, testing, genetics and IQ that he proposes as an alternative.

Sub-system optimization

Cummings repeatedly does what systems theorists call subsystem optimization at the expense of system optimization. A bit of a tongue twister, but it’s a simple and common phenomenon. The components of systems, by definition, are linked to each other, so tweaking one part is likely to result in changes to another. And improving part of the system can sometimes have the effect of making things worse overall. If the components of a system are loosely coupled (weakly connected), the impact might be negligible. If they’re tightly coupled (strongly connected) the impact can be substantial.

Cummings should know this because he devotes an entire section to the features of complex systems (pp.17-21), but appears have filed complex systems under ‘mathematical modelling’ rather than ‘public policy’ in his mental directory. He doesn’t apply systems theory to his own proposals, even though he recognizes many poor political decisions are made because politicians don’t understand how complex systems work.  A similar criticism can be applied to his thoughts on genetics and IQ, the subject of the next post.

 

 

 

 

 

 

 

 

tell-’em-and-test-’em

I’ve just re-read John Holt’s How Children Fail and Doug Lemov’s Teach Like a Champion. It was instructive to read them in tandem.

Holt’s book is a reflection on his observations of children learning (Maths mainly) in the US between 1958 and 1961. I read it a couple of decades later during a PGCE course.  My first take on How Children Fail was that it was a series of fascinating insights into children’s misunderstandings of abstract concepts. My own Maths education in contrast – in a primary school that would have delighted Lady Plowden – was all about grasping concepts.

I re-read Holt’s book when my children were young. What struck me second time around was his use of concrete objects, notably Cuisenaire rods, to get abstract concepts across. As an Infant, I’d been introduced to Cuisenaire rods, and found them utterly confusing – fingers were far more helpful. I was a somewhat synaesthetic Infant; each finger not only represented a number, but also had a distinctive colour. The Cuisenaire rods were different colours. Fingers were also faster. You could work out 5+3=8 in about a second on your digits, but it took significantly longer doing trial-and-error matching à la Cuisenaire.

One of my children had real trouble with mathematical concepts. And with Cuisenaire rods, fingers, number lines and number sentences. The breakthrough came with the excellent Murderous Maths series. He was very keen on narrative, and found he could understand mathematical concepts explained via a story. He also discovered that if he pictured numerals in his head, they didn’t ‘move around’ like they did on paper. (We later found out he had a visual problem – convergence insufficiency – that explained all the visuospatial issues).

What stood out from my third and recent reading was how Holt deconstructs a child’s problem with a concept into its cognitive components. His description of Dr Caleb Gattegno teaching teenagers with severe learning disabilities (pp.98-101) is profoundly moving. Few teachers would have begun with the absolute basics (how patterns repeat) and few would have persevered until the students understood the patterns.

Holt and Lemov

Holt was born in 1923 and had experienced what he called a ‘tell-’em-and-test-’em’ education (p.151). He, his peers, and his teachers, learned how to game the system. Here’s Holt on a teacher giving his class a list of topics to cram for prior to college Board exams. “We got credit for knowing a great deal about ancient history, which we did not, he got credit for being a good teacher, which he was not, and the school got credit for being, as it was, a good place to go if you wanted to be sure of getting into a prestige college. The fact was that I knew very little about ancient history; that much of what I thought I knew was misleading or false; that then, and for many years afterwards, I disliked history and thought it pointless and a waste of time.”

Doug Lemov was born in 1967, soon after Holt’s book was published.  He struggled with school, due largely to social issues, but got to college and became a teacher. At which point he says “I was part of this educational system that was this great, giant ship that didn’t do the things it said it was set out to do.

After an MBA at Harvard (where he picked up more ideas about teaching), Lemov became a director of Uncommon Schools, which manages 53 charter schools in Massachusetts, New Jersey and New York.

Teach Like a Champion was published in 2010.  It’s jam-packed with practical tips for teachers – as is Holt’s. Lemov is deeply concerned about schools not doing their job and students failing to learn – as was Holt. He takes a step-by-step approach to teaching – as did Holt. But that’s where the similarity ends.

A significant difference between Holt and Lemov is how they frame those challenges. Lemov is about teaching, Holt is about learning. Lemov breaks down tasks into instructional steps, Holt is interested in the steps involved in students understanding concepts. Lemov is about controlling students’ learning, Holt is about them controlling their own learning. Lemov wants students from underprivileged backgrounds to have the knowledge that will enable them to ‘compete in college’ (p.39). Holt questions the quality of the knowledge of students from a tell-’em-and-test-’em system.

Both writers have concerns about schools that don’t succeed in educating children, especially those from deprived backgrounds.   Holt wants the children to understand important concepts, because the concepts will be important in later life.  If I’ve understood correctly, Lemov’s model involves providing children with the knowledge they need to get a college education, because that’s a gateway to better jobs, higher pay and could eventually bootstrap entire communities to a higher standard of living and better quality of life.

At first glance, Uncommon Schools appear to be pretty good at this. 99% of their students who graduated high school were accepted for college places, and 76% of those either graduated college or were on track to graduate. There’s no doubt that charter schools have improved high school graduation rates, but the picture is a mixed one, and I couldn’t find data on what proportion of Uncommon Schools students graduated high school.

A college education can open up many opportunities, so there’s some justification for the view that a school’s job is to do to get as many students into college focusing on students who engage and work hard. But that’s a very narrow view of education. Two rather telling phrases about college caught my eye in Lemov’s book.

no opt out

In the first, Lemov describes an Uncommon Schools Key Idea No Opt Out – ‘A sequence that begins with a student unable to answer ends with the student giving the right answer’ (p.31). The ‘sequence’ involves other students or the teacher providing the right answer, and the original student being asked the question again. In one example a student fails to read the word performance. Another student reads the word and the first student is asked to read it again. Lemov comments ‘it’s probably not worth the time to break down the error as the decoding skill the student struggles with is less closely related to the day’s objective. That said, [the teacher] has still firmly established a strong accountability loop. Lemov concludes ‘This ensures that everyone comes along on the march to college’. I’m sure Uncommon Schools would address the student’s issues with decoding, but the focus appears to be on the student’s accountability for their own learning, not on Holt’s focus – what might be posing an obstacle to it.

right is right

Another Key Idea is Right is Right, which involves using technical vocabulary. In the example given by Lemov, volume is not ‘the amount space [sic] something takes up’, but ‘the cubic units of space an object occupies’. This had me scratching my head. Cubic units are a quantification of volume, not volume per se. Also, gases have volume, but whether a gas could be described as an ‘object’ is debateable. Lemov comments ‘This response expands student vocabularies and builds comfort with the terms students will need when they compete in college.’

‘When they compete in college rather than ‘when they are in college’ seemed a rather odd way to frame college requirements. Over the past few decades of course, competition has been an underlying principle of economic policy in the developed world due to an assumption that it drives up quality. Competition can drive up quality if the competitors compete on quality. But it’s pretty clear they often don’t. The alternatives include underbidding, cheating, lying, bribing, gaming… whatever it takes to ‘win’. The sort of thing Holt describes about his college entry process.  Competition also wastes an enormous amount of time, energy, and resources that could be more effectively deployed via collaboration and co-operation. If competition produces winners, it also produces losers, and being a loser can in itself create problems.

Lemov’s world is one where there are right and wrong answers. And the right answers (even if they’re questionable, as in the definition of volume) are what allows you to ‘march to college’ and ‘compete’ in it. Lemov clearly wants as many students as possible to get to college. What isn’t clear is what happens to students who can’t or won’t comply with the Uncommon Schools approach to teaching and learning, or those who find that knowing the right answers isn’t enough at college or in later life.

Those are the students Holt is interested in. The ones who, try as they might, just don’t ‘get’ key concepts, but have figured out how to give the ‘right answers’ (popular strategies included letting a teacher or another student answer first and copy them, or to read the teacher’s body language for cues). Holt is also interested in the students who get to college by giving the right answers but have no proper understanding of the subject or interest in it.

Tell-’em-and-test-’em was widely used in early mass education systems. But many students, like those Holt observed, didn’t grasp what they were being told and tested on. In response during the post-war period, child-centred approaches became increasingly popular, and then began to lose touch with a fundamental feature of education – knowledge. The completely reasonable antipathy to learning entire lessons by rote morphed into avoiding learning anything by heart. Objections to being fed lists of facts turned into objections to learning factual information. The necessity of acquiring higher-level skills transformed into acquiring higher-level skills only. It’s not surprising that teachers who didn’t experience tell-’em-and-test-’em MkI are advocating tell-’em-and-test-’em MkII, but those who cannot remember the past are doomed to repeat it, and Holt provides a vivid reminder that tell-’em-and-test-’em isn’t enough.

references

Holt, J (1965).  How Children Fail.  Penguin.

Lemov, D (2010).  Teach Like a Champion: 49 Techniques that put Students on the Path to College. Jossey-Bass.

 

 

 

Hayek, Popper… and Brexit

I’ve met a fair few libertarians in my travels. Many have cited FA Hayek, the Nobel Prizewinning economist, in support of their ideas. Curious, I read The Road to Serfdom (1944), popular amongst those who advocate market forces. Hayek’s arguments are impressive, but I wasn’t convinced. It was Karl Popper citing with approval a passage in Hayek’s The Constitution of Liberty (1960) that prompted me to read more.

Hayek and Popper

Friedrich August von Hayek was born in 1899 into an academic Viennese family. He was related to Ludwig Wittgenstein and strongly influenced by his ideas. Hayek served in the Austro-Hungarian army in WW1, an experience that prompted him to choose an academic career. He joined the London School of Economics in 1931, remaining in the UK after the outbreak of WW2.

Hayek soon gained a formidable reputation as an economist, and The Road to Serfdom was highly influential. But he found himself at odds with John Maynard Keynes and JK Galbraith amongst others, and in 1950 moved to the USA, settling at the University of Chicago. He, Milton Friedman, Frank Knight, Karl Popper, Ludwig von Mises and George Stigler founded the neoliberal Mont Pelerin Society in 1947.

Contemporaries, both Hayek and Popper were born in Vienna and studied at the University there. Both emigrated from Austria before WW2 and worked at the London School of Economics. They were founder members of the Mont Pelerin Society, and for both, freedom was vitally important – Popper published the two-volume The Open Society and Its Enemies in 1945, a year after Hayek’s The Road to Serfdom. But their thinking is very different.

Hayek’s model

Hayek’s starting point is individualism and the principles of 18th & 19th century liberalism; in the postscript to The Constitution of Liberty entitled “Why I am not a Conservative” he describes himself as an ‘Old Whig’.

For Hayek, individual freedom (the absence of arbitrary coercion) is a paramount principle. Not only because people don’t like arbitrary coercion, but because maximising individual freedom affords the greatest opportunity for innovation – new technologies, foods, medicines, techniques, trading relationships etc.

The best safeguard against arbitrary coercion is the rule of law; not specific legislation, but rather underlying principles that everyone, including government, is aware of and equally subject to. For Hayek individualism is fundamental, so not surprisingly he considered socialism – for which collectivism is fundamental – to be the arch-enemy of freedom.

The section of The Constitution of Liberty entitled ‘Freedom and the Law’ is stunning in its scope and argumentation. And if you want to explore the downside of socialism, Hayek is your go-to source. It’s when he comes into contact with the real world in ‘The Value of Freedom’ and ‘Freedom in the Welfare State’ – that I feel his reasoning becomes distinctly wobbly.

freedom vs coercion     Hayek admits that complete freedom and a total absence of coercion aren’t possible within a social group. For society to function, some behaviours will be prohibited and others required. But these constraints are similar to those we encounter in the natural world.

safety net vs welfare state     He also recognises the need for a safety net to prevent destitution – that might require public funding. Hayek has two main concerns; that a safety net will introduce the expectation that all should be the same, and that it will become a lever for coercion on the part of government.

equality vs equalisation     Hayek wants everyone to have equal access to the safety net, not for the safety net to evolve into a welfare system that equalises everyone. He doesn’t support the redistribution of wealth, or spending significantly more resources on one group of people rather than others.

market forces vs centralised planning     The assumption that we’re all entitled to the same quality of life results in central planning. But the real world is too complex for central planning to work. People and their circumstances are all different, so fairness in a centrally planned system requires discretionary decisions on the part of administrators, and those can be used to arbitrarily limit the freedom of individuals. His solution to the complexity problem is the market, an impartial function that can respond to any situation. He advocates competition (for goods, housing, jobs) mediated by price.

impartiality     Hayek argues; “And if one way of achieving our ends proves too expensive for us, we are free to try other ways” (Serfdom, p.97). That, I’d suggest, is where his argument collides with reality. Hayek doesn’t appear to have ever met anyone who has run out of ‘other ways’ to try – whose poverty, poor health or complex adverse circumstances mean that they simply can’t bootstrap themselves out of the situation.

Hayek is aware that his model will be tough for some, but doesn’t see market forces as any different to natural ones; “Man has come to hate, and to revolt against, the impersonal forces to which in the past he submitted even though they often frustrated his individual efforts” (Serfdom p.209). What he conveniently overlooks is that throughout history people have revolted against impersonal forces (climate, geography, famine, sickness) and that revolt has been the driver for a great deal of innovation.

socialism and conservatism

For Hayek, socialism with its centralised planning is the antithesis of the kind of world he’d like to see. He points out it led to the totalitarianism of Stalinism, and that Hitler’s rise to power was facilitated by the socialist policies already in place in Germany. Understandably, he’s worried that what he sees as socialist thinking across the political spectrum in the UK will end up with the same outcomes.

Of course that’s not what happened. Not yet anyway. Hayek was right that the post-war worldview would result in successive governments, of the right and the left, centralising power and limiting individual freedom. But I’d argue that those actions are the result, not of socialism, but of a human tendency to want to increase control over our environment and to reduce the amount of information we have to deal with. And any model of society is prone to that tendency.

Hayek touches on this in the chapter ‘Why the Worst Get on Top’ in The Road to Serfdom. Those who are highly motivated to seek power and oversimplify have an advantage over those who aren’t bothered about power and who know complex issues can’t be reduced to a soundbite.

The fact that control-seeking and over-simplification are human tendencies rather than outcomes of a particular political worldview, is important because of those who subscribe to Hayek’s view risk seeing socialism as the enemy of liberty, when in fact the enemy is human behaviour to which they are equally prone.  Margaret Thatcher was heavily influenced by Hayek, but centralised and simplified like there was no tomorrow – including over-simplifying Hayek.

Popper’s model

Popper is also committed to freedom and opposed to arbitrary coercion. But his starting point is reasoning. In Conjectures and Refutations (1963) he systematically compares and contrasts empiricism and intellectualism, and shows how the latter, unfettered by evidence, leads to essentialism, utopianism, then totalitarianism.

abstract principles

Hayek is in his element with abstract principles. But when he comes up against the real world he begins to falter. He acknowledges that the real world and his market model, are complex, messy and sometimes harsh, but believes people will put up with that in order to hang on to an abstract principle of ‘freedom’. This is where Hayek and Popper part company.

For Hayek, freedom is of paramount importance. For Popper, any single paramount abstract principle is problematic. Via a painstaking critique of Plato, Hegel and Marx in The Open Society and Its Enemies, Popper shows how making abstract principles paramount results in essentialism, utopianism, then totalitarianism.

The world Hayek envisages isn’t a utopia in the way most people would use the word, but it is in the sense Popper uses it – in Hayek’s case an ‘ideal’ world in which individual freedom is prized above everything and impartial market forces (eventually) result in significant benefits for all.

Ironically, Hayek’s model means that despite the impersonal forces of nature and the market applying equally to all, some people through an accident of birth or adverse circumstances are likely to have to be more submissive to those forces than others who happen to be in the right place at the right time with the right opportunities.

Submitting to the impersonal forces, as Thomas Hobbes pointed out, can result in life being ‘solitary, poor, nasty, brutish and short’. In Hayek’s model that fate is averted by the minimal safety net, but he doesn’t go into detail. Ironically, his model implies that it’s OK for some people never to escape the safety net because they still have their individual freedom and there are benefits for others collectively from economic advances. Hayek’s approach has been tried in the West for the last three decades. We’re still waiting for the economic benefits to trickle down.  His model has resulted in a few becoming richer, many becoming poorer, and postponing action on pre-existing crises involving raw materials, pollution and ecological catastrophe.

the real world

Popper points out that theoretically possible abstract concepts considered by philosophers and logicians are often impossible in the real world – because the real world is constrained by complex factors that philosophy and logic don’t have to take into account. That doesn’t mean you can’t base a socio-politico-economic system on abstract principles such as individual freedom and the rule of law, but it does mean making an abstract principle paramount will be problematic.

The economist Paul Krugman reportedly observed that Hayek’s ideas were more about politics than economics. A friend commented; “He must be an economist if he uses equations”. I said I hadn’t seen a single equation in either book. The response was “But equations tell you there are variables”. The challenge for most economists tackling the real world is getting all the relevant variables into their equations.   But Hayek doesn’t have that problem because he’s dealing with abstract principles and can include or exclude whatever variables he wishes.

Popper is happy to embrace abstract principles, but is well aware of what happens when they collide with the real world.  At the end of The Open Society and its Enemies: the Spell of Plato, Popper points out that if piecemeal improvements to institutions go wrong, the damage is limited, but if things go wrong with the wholesale changes advocated by utopians, it’s catastrophic (p.172). Abstract principles make great servants but dangerous masters.  As we’re discovering with Brexit.

references

Hayek, FA (1944).  The Road to Serfdom, Routledge.

Hayek FA (1960). The Constitution of Liberty, Routledge.

Popper, K (1945). The Open Society and its Enemies Vol 1: The Spell of Plato, Routledge.

Popper, K (1945). The Open Society and its Enemies Vol 2: Hegel and Marx, Routledge.

Popper K (1963). Conjectures and Refutations, Routledge.

 

Rousseauian nonsense revisited

A few days ago Greg Ashman released the proverbial cat amongst the Early Years pigeons with this tweet:

greg gibb

Early Years practitioners were a bit miffed and responded robustly; there were several requests for more detail about the ‘Rousseauian nonsense’. Greg obliged in a blogpost.

He opens with a paragraph on Rousseau’s ‘work of fiction’, Émile. He goes on to contrast guidelines requiring the avoidance of formal teaching in Early Years, with evidence for its efficacy, referring to Geary’s theory of biologically primary and secondary knowledge, and  advocates a balance between play and formal teaching. Many of Greg’s posts are informative and constructive, but this one left me feeling uneasy.  I’ll start with the ‘Rousseauian’ element.

Rousseauian

Émile is indeed a ‘work of fiction’ in that it’s written as a novel – and a rambling, sometimes rather incoherent novel at that. Voltaire was typically scathing. Following its publication, Rousseau’s books were banned in Geneva and France and he went on the run to avoid arrest. Obviously, the strength of this reaction wasn’t simply down to a poor writing style or his advocating following a child’s interests.

What Rousseau challenged in Émile was authoritarianism. He’d grown up in Calvinist Geneva, later converted to Catholicism, and had seen the impact on children who’d been educated under both systems. He’d also seen the children of peasants and artisans, who lacked a formal education but were often more contented and self-assured.

Calvinism and Catholicism both used the idea of original sin to justify a strict approach to child-rearing and education. Rousseau argued that despite sin, Nature remained God’s creation. If God created children to develop in the way they did, it made far more sense for education to go with the child’s God-given nature, than to go against it.

In one section of Émile, “The Creed of the Savoyard Priest”, Rousseau abandons his novelistic approach and tackles Descarte’s model of reason head-on, in an insightful essay setting out the questions about perception, cognition, reasoning, consciousness, truth, free will and the existence of religions, that perplexed the thinkers of his day. It was the only section Voltaire thought worth publishing.

But you’d never know that to read Greg’s impression of ‘Rousseauian’. Instead he highlights a ‘central tension’ in ‘educational progressivism’ where Rousseau acts as a puppet master ostensibly following Emile’s interests whilst manipulating them behind the scenes. That tension exists only if your model of education is that it must be either adult-led or child-led. In Rousseau’s framework, the child needs to learn certain things about the world, but can do so in a way that makes sense to them. There is no tension because the teacher and the child are working together; not either/or, but both/and.

Émile is about a one-to-one education and some teachers would argue that it’s impossible to teach like that in a class of thirty children. It probably would be unworkable in a normative education system that ‘expects’ children to know specific things at a specific age, but Montessori schools have been using this approach successfully for a century, and a variant worked well at the primary I attended in the 1960s – class sizes 16 (5-6s), 24 (7-8s) and 35 (9-11s).  What Greg means by ‘Rousseauian’ is essentially a caricature of what Rousseau was saying.

Nonsense

I agree that there’s a lot of nonsense in education, and Early Years is no exception, but what Greg refers to is an antipathy to ‘formal learning’ embedded in government guidelines, contrary to the evidence supporting ‘formal teaching methods’ in developing the foundations of academic skills.  What he appears to be saying is that Rousseau came up with a daft, inconsistent idea about education, and Early Years teachers are told Rousseau was right, so they should avoid formal learning as it could be harmful.

This is again a caricature. Anyone who’s taught young children will know that a major obstacle to them acquiring academic skills is their immaturity. They have immature visual and auditory discrimination, motor control, impulse control, social skills, and awareness of how the world works. Those skills develop very effectively through play (you can see it happening), and Early Years settings almost invariably use directed play to help all children develop the skills they’ll need. There’s no tension in the play being directed, either via instruction or setting up a particular environment, because what the teacher and children do is complementary.

It wouldn’t surprise me if some early years teachers advocate undirected play and/or feel that any hint of formal learning is harmful, but my guess is they’d be few and far between. Most early years teachers use formal teaching, but it might look different to what Greg envisages. How effective is formal teaching until children can control their arms, legs, fingers, tongue, attention, bowel and bladder?

Criticism of ideas

Greg says his original tweet was ‘criticism of ideas rather than people’, and claims ‘many responses to it were of a personal nature’ implying that he wasn’t entitled to an opinion because he’s not an Early Years teacher. He says he would welcome opinions on secondary maths teaching and if people are wrong, will happily point out why they are wrong. All very reasonable, except that…

  • I’m not clear how “there’s a lot of Rousseauian nonsense in Early Years” is a ‘criticism of ideas’. To me, it looks more like a throwaway comment that indirectly impugns both Rousseau and Early Years teaching without explaining why. Which appears to be a bit ad hominem itself.
  • The responses Greg screenshots don’t question his entitlement to an opinion. Instead they question is his entitlement to sling mud at Early Years teachers without explanation.
  • The responses were pointing out why they thought he, Early Years teacher or not, was wrong.

Greg’s blogpost offered him an opportunity to justify his comment about ‘Rousseauian nonsense’. Turns out it’s based on a caricature of Rousseau and of Early Years teaching, and any complaints about the comment, regardless of their validity, are treated as ad hominem.  Is there any hope for constructive debate?

 

 

 

 

 

 

 

 

 

 

Skipping school: Britain’s invisible kids

This was the title of the Channel 4 Dispatches programme broadcast on Monday this week.  It was about home education and presented by the Children’s Commissioner, Anne Longfield.  Ms Longfield called for a complete overhaul of the system relating to home education, but her call was based on some significant misunderstandings of the current legislative framework. There are some key principles that need to be taken into account before any legislative changes are considered.

education should be suitable to the individual child

The Education Act 1996 (s.7) gives parents a duty to cause their child to have a suitable education – suitable to the individual child (s.7 uses the now somewhat archaic ‘he’). That’s important because if the education isn’t suitable to the child as an individual, they are unlikely to learn well.

In contrast, the current education system requires teachers to deliver an education suitable to the average child. Teachers are expected to differentiate their teaching for the many children who are not average, but have little training in doing so. This inherent tension appears to be a major factor in the increasing numbers of home-educated children – all the children who appeared in the documentary had had significant problems with school.

the law treats education and welfare as distinct issues

That’s important because a child could be well educated but at risk of harm, or safe and well but poorly educated.

If it appears that a child is not receiving a suitable education (s.437(1) Education Act 1996), a local authority has powers to make inquiries about the child’s education and to issue a school attendance order if necessary.

If a local authority has reasonable cause to suspect a child is at risk of significant harm (s.47 Children Act 1988), it has powers to make inquiries about the child’s welfare, including entering the home and seeing the child if warranted.

home-educated children who have come to harm have not been invisible

In 2014 the NSPCC published a briefing featuring seven Serious Case Reviews for home-educated children who had come to harm.  I have been unable to find any additional similar Serious Case Reviews (SCRs) prior to this date, so I think it’s fairly safe to conclude that Ms Longfield’s concern that there might be thousands of home-educated children at risk of serious harm might be disproportionate.

In each case, the child in question was previously known to the authorities. Almost 70% of the SCRs’ recommendations related to the failure of the authorities to follow procedures correctly. In five cases, the failure of healthcare services to do so may have contributed directly to the harm experienced by the child.  I’ve blogged about the briefing in detail here.

In Skipping School Ms Longfield highlighted the tragic death of Dylan Seabridge in 2011, and commented that he was ‘all but invisible’. But Dylan’s mother worked at a school in a neighbouring local authority and the Head Teacher had raised concerns about her children in 2007. In 2010 Ceredigion social services considered her vulnerability due to her deteriorating mental health, but didn’t alert the local authority for Pembrokeshire where the family lived.  Fiona Nicholson has documented this case in detail here.

The Seabridge family’s welfare was a welfare matter. The fact that the local authority didn’t have right of entry to the home to check on the children’s education is beside the point. Exactly the same conflation took place prior to the death of Khyra Ishaq, where concerns about the welfare of Khyra and her siblings had been raised by the school she had previously attended, but the local authority complained that education legislation prevented them from seeing the children.

home education and illegal schools are two different things

The boundary between home education and an unregistered school is blurred only because the criteria for school registration are unclear (notably about the number of hours involved), not because home education is on the rise.  Fiona Nicholson has documented this issue in detail too, here.

conclusion

The programme began by attributing the increase in home education to schools ‘off-rolling’ difficult pupils. It concluded by calling for local authorities to have powers to register and monitor home-educated children on the grounds of ‘the rights and best interests of the child’. But if local authorities cannot ensure that their own schools provide a suitable education for those children, where does that leave the rights and best interests of the child?

Local authorities already have powers to intervene if they have concerns about the welfare or education of home-educated children – but are often unclear about what those powers are. That lack of clarity has been a factor in home-educated children coming to harm.

I agree wholeheartedly with Anne Longfield that a good education is vital to children and the wider community, but if schools are failing to provide it, I can’t see how local authorities monitoring the education provided by despairing parents will address the root cause of the problem.

I’ve suggested in response to previous government consultations that if a child is removed from a school roll to be educated at home, their per capita funding be retained by the local authority and ring-fenced to provide resources and advice centres – maybe based at local libraries – to support any families who need it.

Home educated children are not skipping school. Nor are they invisible. And what they and their families need from local authorities is support – not ineffective registration and monitoring.