A summary of my arguments about education

And still they gazed, and still the wonder grew, that one small head could carry all he knew. Oliver Goldsmith

A tradition without intelligence is not worth having. T. S. Eliot

The debate of ideas in education – and anywhere else – is essential if we want to improve the lot of children and society. Over the past 6 years of so I’ve learned such a lot from this back and forth and have, as well as becoming a good deal more knowledgeable, become a lot more adept at thinking critically about the ideas I encounter. My views have changed a great deal over this period and I thought that now might be a good point at which to lay out a summary of my hypotheses about education.

  1. Everyone seems to agree that increasing children’s creativity, problem solving, critical thinking etc. is a worthy goal of education. Like everyone else, I want to see children able to make their way in an uncertain world, but I disagree with the consensus view about the best way to achieve this aim.
  2. Intelligence is a social good (a greater number of individuals with higher IQ makes society safer) as well as an individual good (IQ correlates strongly with creativity, leadership, happiness, longevity etc.). It therefore seems reasonable that if we want to make children more creative and better critical thinkers, we need first to make them cleverer.
  3. Although many of the claims attached to growth mindset are wrong (the brain is not like a muscle) we can increase IQ. The Flynn effect shows how aspects of IQ tests respond to cultural change and is rising by about 3 points per decade.
  4. Intelligence can be broken into fluid intelligence and crystallised intelligence. Fluid intelligence is our raw reasoning power, and is, as far as we can tell, fixed; nothing we’ve tried as yet is able increase it. Crystallised intelligence is the ability to apply what you know to new problems and can certainly be increased by adding to our store of knowledge.
  5. No one can think about something they don’t know. Equally, the more you know about a subject, the richer and more sophisticated your thinking on that subject becomes. It is my view that the much vaunted 21st century skills depend on knowing stuff within a specific domain.
  6. Evolutionary psychology points to the fact that some things are easy for us to learn (biologically primary evolutionary adaptations) but some are hard (biologically secondary modules). So-called ’21st century skills’ are actually biologically primary adaptations and cannot be taught as generic skills. They are in fact domain-specific and rely on expertise in a domain in order to be exercised and developed.
  7. Fluid intelligence is strongly correlated with working memory capacity (which also appears fixed) but its limits can be ‘hacked’ by storing information in long-term memory. Fortunately, the capacity to store new information does not appear to be correlated with our fluid intelligence: anyone can remember stuff, regardless of how able we perceive them to be.
  8. When we store knowledge in long-term memory, it organises itself into schemas which, when we use them to think about complex problems, take up less of our limited working memory capacity.
  9. Declarative knowledge (facts) is what we think about; non-declarative knowledge (skills) are what we think with. Certain kinds of procedural knowledge (skills) can be automatised so that they takes up practically no space in working memory, leaving us with far more capacity with which to think. I tried to show the relationship between memory about skill in my taxonomy.
  10. Certain domains of procedural knowledge are particularly worth automatising because they recur so often in education – phoneme/grapheme relationships, times tables facts etc. The process of automatisation is accelerated through purposeful practice.
  11. It may be true that “everything works somewhere and nothing works everywhere,” but if so it’s trivially true. Better to say, some things work in most contexts and other things rarely work anywhere. ‘Traditional’ approaches to the curriculum and instruction are better suited to achieving the ends most people value than ‘progressive’ ones. This is, I think, a social justice argument.
  12. If children automatise powerful procedural knowledge in long-term memory and encounter culturally rich declarative knowledge, they will become cleverer and, therefore, more creative, better problem solvers etc.
  13. Because intelligence (and therefore everything else) relies to some degree on genetic heritability, we cannot hope to close the gap between the most and least able. We can, however, move the whole bell curve to the right which would both benefit society as a whole and every individual within it.
  14. We may also be able to change the shape of the curve. If we try to develop skills by trying to teach generic skills directly, then children with higher fluid intelligence and those from more advantaged backgrounds will be privileged and the bell curve will stretch out. But, if we make a concerted attempt to increase children’s crystallised intelligence then the curve might become steeper as the difference in what children knew became less great. (This is the bit I’m least sure about – critique welcomed.)

I would be genuinely grateful for any constructive critique of any of these steps in my chain of reasoning, or if anyone can suggest vital bits of information I might have overlooked.

71 Responses to A summary of my arguments about education

  1. […] Here is a summary of what I’ve learned through debating ideas in education. […]

  2. The original theoretical basis for IQ was that it was a fixed entity and it was this that IQ tested. One critique of this was that really all that IQs tested was what IQs test for; ie all they showed, it was said by some, were scores for a particular kind of question which may or may not correlate with some other activities. Then, as you say, it was shown that you could improve your scores. Did that mean you were improving your intelligence? Or improving your ability to do the test? Or is this de facto the same question? Or a different one?

  3. Dr P says:

    Great summary. Very close to my own position.

    Playing ‘dual N back’ has been reported to increase fluid intelligence, including transfer to other domains.


    The better education gets, and the fewer differences in provision we provide, the more heritable educational achievement becomes as a greater share of the variance will be due to genes.

  4. bocks1 says:

    I still can’t agree with one of the main premises of your case David, which alludes to the ‘fact’ that greater knowledge necessarily leads to richer and more sophisticated thinking. I have encountered many, many professionals who’s knowledge is greater than those around them but who’s thinking (reflected in their chosen representations of said thinking) is at odds with your claim.

    There are many other perspectives which can be referred to in highliting the flaw in this assumption that it is an automatic link in the process of gaining and then using knowledge through ‘better’ thinking. Just one would be a student studying quantity surveying at master’s level who couldn’t work out how to move a cupboard around an office. Obviously, there are arguments about spatial awareness, etc but the physical application of his learning does not reflect the argument s premise. Or am I missing the point somewhere?

    • David Didau says:

      Ok – let’s be clear. I’m not claiming that greater knowledge means that you’ll automatically become a creative problem solver. What I’m saying is that creativity and problem solving within a domain are impossible without knowledge. Likewise, if we make everyone cleverer then everyone will be better at thinking. You’re anecdotal experiences need to be reversed: if you “encountered many, many professionals [whose] knowledge is greater than those around them but who’s thinking (reflected in their chosen representations of said thinking) is at odds with [my] claim,” then I’d ask you to imagine how woeful their thinking would be if they knew less.

      To take your example of the QS student, the problem is one of transfer and it is well established that increasing expertise within a domain makes it easier for experts to transfer problems between closely related contexts. That is to say, the more they know, the better their thinking.

      • James says:

        May I ask your opinion on flipped classrooms? They have blown up in popularity, but more, I believe, as fashionable cover for social constructivism, and not direct/guided instruction. They want students to know problem solve in class without assurance that any student has adequate knowledge to do. Very inefficient. Based on previous comments, I would be interested in your thoughts? Thanks

        • David Didau says:

          I can see how ‘Flipping’ classrooms so that the instruction takes place at home and the classroom is used for discussion & practice makes intuitive sense. Unfortunately, while it’s likely to work very well for experts it won’t be nearly as useful for novices. In my mind it’s clear that this sort of approach is only likely to benefit those who are already advantaged.

      • bocks1 says:

        Sorry for not responding – in France so expect delays!

        Point taken (esp. about transfer) – but an implicit part of my observation was that some of those (at least those who I have encountered) with less knowledge have a greater ability to think creatively and solve problems (or at least suggest solutions maybe, as you say, from closely related contexts) than those with more knowledge. Undoubtedly there is a link and I appreciate your argument is very well constructed. I just do not feel the case made that knowledge in and of itself has as much influence as, for example, successful problem solving experience. Maybe the link for me is more about how one approaches solutions and, if ones approach involves a variety of perspectives and a willingness to consider a variety of models, then successful thinking is more likely. For these good folk, of course, knowledge is of huge importance and impact.

        My head hurts now so I am off to celebrate wine o’clock 🙂

        • Catherine Scott says:

          Maybe a brief case study or two of people who didn’t know much but came up with a creative solution would be helpful. Guess we should define creTivity. Standard definition is a solution to a known problem or logical next step that is both original and effective/appropriate .

          I’m suspicious because we have a lot of cultural beliefs about creativity that are wrong. Our model of the act of creativity involves a lone genius who springs from nowhere. We are wilfully blind to the long preparation/education that contributes to any act of creativity. Self made man and all that.

        • David Didau says:

          But “successful problem solving experience *is* knowledge. That’s the point.

    • Catherine Scott says:

      The plural of anecdote isn’t data. David is reporting the findings of cognitive science and decades long research into the development of expertise.

  5. Michael Pye says:

    If we make the curve steeper doesn’t that mean we have shortened the gap?

  6. Catherine Scott says:

    Sounds like you read my book.

    Re the narrowing the bell curve it’s a distinct possibility. In a culture that is obsessed with nurturing individual differences education widens the difference between ‘top’ and ‘bottom’. I noticed that a long time ago.

    A way to see this is to look at attainment in places like the UK where the nurturing individual differences hold sway and France, where teachers think it’s their job to make sure everyone learns the same fundamental skills and knowledge. The curve is narrower in France, or used to be. Haven’t looked recently.

    Patricia Broadfoot and her team did work on that around the mid ’90s. Probably possible to obtain her publications. Oh and Robin Alexander’s five nation study of course.

    I’ve also looked – literally,no statistical analysis – at PISA data and countries that have the same educational beliefs as the UK tend to produce bigger gaps between high and low achievers.

    I’ll just plug my book again, as you may find it useful. It’s written as a text coz that was what Cambridge UP wanted but it isn’t a traditional text it’s an exploration of the ideas that you grapple with here. ‘Learning to teach, teach to learn’ published 2015.

    Catherine Scott

  7. Matt says:

    Interesting stuff.

    Have you read anything by people working in grounded/embodied cognition, David? They have a slightly different view of memory that you might find interesting: ‘facts’ recalled in semantic memory are kind of ‘shallow’ simulations / recall of sensorimotor episodic experiences. Semantic and episodic may not fundamentally be that different.


  8. Yes! I’ve been waiting for someone to say what you’ve said. I have a theory I’ve been developing that relates to what you’re saying and also attempts to get past the education wars. My idea is that learning is about recognizing and mimicking patterns. We do this in every realm from the numeric to the auditory to the social. Each of us is able to easily detect (discover) and mimic certain patterns with little to no instruction. And each of us has certain patterns that we struggle to detect and mimic without explicit instruction. If I explicitly teach a pattern to someone who can discover it on their own I’m taking all the joy from the learning process. If I ask someone to discover a pattern that they cannot detect on their own I’m torturing them and they will not be successful. We spend a lot of time arguing about explicit v. discovery methods of instruction as if there is one right way. Clearly we have to match the method to the need. I think your theory and mine work pretty well together!

    • David Didau says:

      Pattern recognition is a long established finding of how experts solve problems. The problem are twofold:
      1. Novices don’t recognise or understand what experts can see
      2. Some things are easy to spot patterns in (biologically primary) but other things are hard (secondary abstractions)
      Cognitive load theory is interesting in that it explains why discovery approaches work both for experts and in biologically primary domains. Explicit instruction works best with novices (school age children) and biologically secondary modules (school subjects). Therefore, it really is worth arguing about the best way to teach – one way will clearly be more effective.

      • If a child almost of any age responds to a story by giving another analogous example either taken from life or from another story, that child is spotting a feature, selecting it from hundreds/thousands, analogising from experience and so in that instant creates a ‘set’. They may even give it a title, like ‘I know a sad thing like that..’ or ‘a sad thing like that happened to me’. These tiny acts of response are in their own way abstractions.

        • Michael Pye says:

          Those abstractions are likely to be flawed or outright wrong. Guidance using clear factual example helps correct this. As normal I found it hard to figure your point out so I am assuming it was that children use pattern recognition as well.

          Novice used unpredictable and often incorrect patterns.
          Expert internalises reliable patterns recognising them and acting on them quickly.

          • So, child spots ‘sad’ moment in a story and in response tells a story that has a ‘sad’ aspect to it and identifies it as ‘sad’ – the conversation drifts into a discuss of ‘sad’ and ‘sadness’. What is possibly ‘flawed’ or ‘wrong’ about this? It’s an exploration of the abstract notion of ‘sadness’ through the concrete sets of circumstances from life and a story. It’s the classic ‘exemplum’ principle used by fables and parables in nearly all world religions and philosophies but in a slightly different way.

          • David Didau says:

            That’s not wrong or flawed, it’s entirely natural. In fact I’, pretty sure our response to stories is likely to be a biologically primary adaptation seeing as how we respond to and think in narrative so effortlessly. The point is, the more abstract the concept we’re trying to communicate, the less likely a child will be to correctly work it out using a primary module. An explicit instruction is most likely to benefit most children.

  9. Jos says:

    Is it not always: Knowledge is stored in long term memory, every thing else is just volatile information. You need knowledge to think about something. You can gather information but you have to “create” a kind of a view (schema) with the provided information. The more information about a subject is stored in long time memory, the better the view about that subject. Only then you can think critically about that subject and one can become an expert on that subject. Kind of logic…

  10. trishajha says:

    I understand and appreciate the distinction between procedural and declarative knowledge but I’m wondering how you would divide aspects of Languages/MFL teaching between those categories. One of my assigned textbooks says the following:

    “Declarative knowledge consists of what the learner explicitly knows, as knowing the grammar rule that you need to add an “s” to a noun to form the plural in English. Procedural knowledge is knowing how to do something without having conscious awareness, as being able to produce L2 sentences without conscious reflection on what needs to be done first, second, etc., and is thought to underlie automatic performance. Traditional information processing views suggest that declarative knowledge precedes procedural knowledge.”

    Is this correct?

  11. Matt says:

    Not sure it’s the same with L1 though – you don’t need to declaratively know the morphosyntactic rules of your native tongue to be an expert in it. Most people don’t. I wonder if there’s degree or more of implicit – pattern recognition based – learning taking place in L2 after a certain threshold of explicit learning has taken place?

    • Matt says:

      Depends how immersed in the language you are perhaps?

      (This comment double posted above was meant to be here!)

  12. cbokhove says:

    Sorry for the delay.
    I was ‘battling’ fallacies on twitter re prog/trad dichotomy.
    I agree with most of this, but think 3,6,11 and 12 can be formulated more precisely, or -dare I use the word- are more nuanced.
    I can’t/won’t give a full treatise but simply flag up why I think so. I am sure you roughly know what I’m on about.
    3. Flynn effect critiqued. Indications leveling off. Although no limit LTM known, can be negative effects see
    “the Knowledge” reduction spatial skills.
    6. From what I’ve read very much primary and secondary related. Boundaries greyer.
    Certainly ‘load link’ imo a bit circular.
    11. Far more related to social justice are SES effects. Schools and teaching can make a difference but as
    SES moderates most of them, I think *only* saying traditional does this best is incomplete. Certainly because the SES interactions are less clear-cut.
    12. The second part does not follow *automatically* from the first part. This is why BOTH need to be taken into account. And can, according to for example the creativity literature.
    Of course there are different ‘schools’ of this.
    Your blog often has a lot of depth, I’m sure some of my points can be debunked.

    • David Didau says:

      Thanks for this – as the title stated, this post is a summary so I very deliberately avoided going to much depth. That will be the subject of my next book.

      One question and a point:
      Q. Can you tell me what SES stands for?
      P. I haven’t said “only “traditional methods work, I’ve said explicit instruction works *best*.

      • Felicity says:

        Socioeconomic status (SES)?

        • David Didau says:

          Right, thanks. The correlation between SES and IQ isn’t as strong as you might expect (r=0.3 – r=0.5). There’s no doubt that your background has an effect on your life chances, but there’s also evidence of a connection between higher IQ and social mobility; the cleverer you are, the more likely you are to improve your socio-economic standing. Where you start off will be an important determining factor in where you end up, but so will your intelligence.

  13. Luc Kumps says:

    For points 13 and 14, perhaps a link to Benjamin Bloom’s “2 sigma problem” might be useful?
    In 1984 Bloom pointed out that two doctoral dissertations illustrated the difference between individual tutoring and classroom instruction: “the average student is 2 sigma above the average control student taught under conventional group methods of instruction” (point 13).
    But the shape of curve also changed: the variance was lower in the individually tutored group (point 14).
    See Figure 1 on page 5 of Bloom’s article:

    • David Didau says:

      Thanks Luc, I’ll take a look

    • Michael Pye says:

      Luc how did he control for different cohorts. (Students who get 1;1 tutoring are likely different)
      Did it include homeschooling. What exactly is he suggesting that we change?

      From a brief read the corrective work and extra tutoring seems to be similar to a response to intervention model used early to bring students up to speed. Am I missing something?

      • Luc Kumps says:

        It was an experimental design with students assigned randomly to one out of three groups. The three conditions are described in the first column on page 1 of the PDF (link at the bottom of my comment above). This was replicated with four samples (Grades 4, 5 and 8) and two subjects (Cartography and Probability).
        Bloom gives a few suggestions (in Hattie-style, with effect sizes) and probably the 3000+ articles (according to Google Scholar) referring to this article will offer many more.

        However, I think that the main contribution of the article (and the research reported in the dissertations) aren’t the suggestions that it offers but rather the conclusion in the introduction that “the most striking of the findings is that under the best learning conditions we can devise (tutoring), the average student is 2 sigma above the average control student taught under conventional group methods of instruction. The tutoring process demonstrates that most of the students do have the potential to reach this high level of learning. I believe an important task of research and instruction is to seek ways of accomplishing this under more practical and realistic conditions than the one-to-one tutoring, which is too costly for most societies to bear on a large scale.”

        David’s post (and especially the remarks about modifying the distributions) reminded me of this…

        The tutoring model does indeed correspond more or less to a *permanent* and *individual* RTI model.

        • Michael Pye says:

          Got to reread the paper with more time and it made a lot more sense and I realised I may have been a bit prejudiced towards Bloom, his ideas are rather pragmatic.

          Made the mistake of looking at some analysis of the paper on the internet though and it seems both knowledge advocates and constructionists claim Bloom for their own.

          The most amusing was a website arguing that Bloom supported constructionist methods quoting results from the paper (page 14 Levan 1979) showing a two sigma increase in teaching higher order skills (here being used as a proxy for inquiry learning despite little info in the paper on the exact method). Naturally they did not mention the control group were not taught any application of the principles they had learnt.

          Bloom had a whole section on page 13 that was advocating inquiry learning (it should be noted he repeatedly emphasis’s mastery of basic knowledge). The paper has no information on the precise methods used and I wonder if any one has gone back and looked at the referenced studies to see if they fit the modern interpretations of inquiry learning.

          As Bloom wrote this in 1984 the debate likely had some differences then in it’s modern context. Certainly a lot of modern research was unavailable to Bloom. I am not convinced with this aspect of his argument (though I do wonder if this is just my backfire effect). His arguments seem only to support the idea that students get good at what they are intensively taught (Intensive here meaning with regular clear feedback and correction). If you want more analysis and application this needs to be emphasised and developed from the mastery of knowledge that students have been taught. If you just teach principles (a subset of knowledge) this will not occur. (Seems blindingly obvious).

          It reminds me of an old computer game at school were we had to build a Norman fort in a fortnight by allocating resources to things like finding food, timber and constructing a mound and moat. My group was the first to realise that allocating resources to anything other then the mound and food was a waste until the mound had been built. We did not win the game which was to construct the fort as fast as possible. We were the second to last group. The last group won, it should be obvious why.

          • Luc Kumps says:

            It looks like the one-to-one tutoring just keeps the students in their Zone of Proximal Development all the time, whatever way that happens…

  14. eanelson2014 says:

    Cognitive scientist Daniel Willingham says fluid intelligence can be changed by “sustained hard work.” See page 10 of great article at http://bit.ly/2pCN3gD

  15. David, this may be an interesting paper, concerning the relation between conceptual and procedural knowledge, also the question regarding the sequence in teaching (e.g. conceptptual or procedural knowledge first?):


  16. Lynn says:

    i don’t doubt that your statement the brain is not like a muscle is accurate, however could you give me a better analogy to help me get “buy in’ to the idea that crystallised intelligence can increase? I think my growth mindset schema needs some adjustment. Thank you

    • David Didau says:

      For the claim ‘the brain is like a muscle’ to be true the brain would have to behave like a leg: if you exercise your leg muscles, you better at everything you use your legs for – the same muscle groups are used whether you’re running, jumping, dancing or sitting in a full lotus. The claim that the brain is like a muscle supposes that doing one kind of mental exercise would make you better at every other kind of mental exercise. As we shall see, the evidence doesn’t really support such a claim.

      Crystallized intelligence increase as you learn more about the world. So, knowing more about, say, Chad, means you ca think more about it. If you only know it’s a country in Africa then your thinking is pretty limited. If you also know it’s a predominantly Muslim country made up of 9 major ethnic groups (and 100s of minor ones) then you can think about more things. Then if you know it’s a land-locked former French colony following a popular islamist uprising which led to a decades long civil war then you can add that into the mix. All this stuff interact with everything else you know about the world and makes for an increasingly potent mix.

      • Lynn says:

        Thank you.

        So crystallised intelligence is not just a measure of knowing more – it’s a measure of being able to apply that knowledge and think more deeply and divergently?

        • David Didau says:

          Yes, precisely. A test of verbal reasoning is a good test of crystallized intelligence.

          • Lynn says:

            So growth mindset means:?

            Learning new material is incremental and limitless.
            Assimilate and engage with new information and accommodate it within the schema already created.
            Learning is stored in domain schemas in long term memory.
            The more you know, the more you can bring to the forefront to think about and apply.
            Thus crystallised intelligence increases?

          • David Didau says:

            Yeah. I don’t really see much point in GM

          • Lynn says:

            Got it!

            My growth mindset schema has just been adjusted accordingly!

            Thank you.

          • David Didau says:

            *ping!* My work here is done.

          • Luc Kumps says:

            A mindset is a thinking framework. If you have a growth mindset about mathematics, then you think that it is always possible to increase your capabilities in mathematics. If you have a fixed mindset about mathematics then you think that you’re either “born with a math brain” or… you ‘re not. Your mindset influences the way you react to failures. With a fixed mindset, a failure means you “don’t have it” and you’d better give up and try something else. With a growth mindset you’re convinced that a failure is part of learning and you just try something else or put in more effort. With a fixed mindset you feel threatened by the success of others, with a growth mindset you feel inspired. See https://alumni.stanford.edu/content/magazine/artfiles/dweck_2007_2.pdfhttps://alumni.stanford.edu/content/magazine/artfiles/dweck_2007_2.pdf (this diagram is about “intelligence”, but mindsets apply to a lot things, from “Palestinians/Israeli’s are born murderers” to “I’m clumsy”).
            Here’s one experiment with mindsets: https://www.youtube.com/watch?v=TTXrV0_3UjY

          • David Didau says:

            Yes, except the failure to replicate this stuff is a serious flaw http://www.learningspy.co.uk/psychology/growth-mindset-bollocks/

          • Luc Kumps says:

            “The failure to replicate this stuff is a serious flaw”. In support for this statement, you refer to your page “Is growth mindset bullocks”. I searched for “replication” on that page but I only found “But now it seems that Dweck’s original research is under fire. Yue Li and Timothy Bates have performed faithful replications of her studies but failed to get anything like the same results”.

            I read the Li & Bates “Three failures to replicate” article (in press? to be published?) but it doesn’t appear to be about replication at all. For example, the authors didn’t even attempt to replicate ANY (!) of the results of one of the main articles they are supposedly “replicating” (e.g. Mueller & Dweck, 1998).

            I can’t find a single outcome variable of these three “faithful” (???) “replication” studies that is also present in one of the mindset papers that the authors refer to.

            In short, what’s the definition of “replication” here? What am I missing or overlooking?
            (I’ll also post this on the “bullocks” page allowing other people to comment)

          • David Didau says:

            Not sure what you read, but the Li & Bates paper is definition a detailed account of their attempts to replicate three of Dweck’s experiments. If you find any evidence of successful replication I’d love to take a look.

          • Luc Kumps says:

            Perhaps I’m misunderstanding something, but this is the definition of scientific replication that I’m using: https://en.wikipedia.org/wiki/Reproducibility

            In short, it consists of repeating an experiment as close as possible to the original one. At the very least, one would expect the dependent and independent variables to correspond.

            Li and Bates say they “closely replicated” Study 1 of Mueller and Dweck (1998). Now compare that latter article: http://www.uky.edu/~eushe2/mrg/MuellerDweck1998.pdf
            to what Li and Bates did. It doesn’t even come close to a replication, so it sure isn’t a “close replication”.

            Just have a look at the outcome variable: for Mueller and Dweck, the outcome variable was ATTRIBUTION, For Li and Bates, it is short-term ACHIEVEMENT (which they call “IQ” – based upon a few items of Raven’s matrices), which doesn’t figure anywhere in Mueller and Dweck’s Study 1. Li and Bates don’t even mention attribution, which is at the core of mindset theory…
            As far as I know, short-term effects of mindset on achievement have never been claimed by any theorist working on implicit beliefs.

      • JL says:

        ” an increasingly potent mix”.

        I love this wording. Silly analogy perhaps but I have often thought of this topic in terms of the “primordial soup”. The elements are the facts linking together into increasingly complex organic compounds (schemas). Trying to figure out what sparks creativity is a bit like wondering what sparked life. So far we can’t precisely pinpoint it but we do know the necessary prerequisites for it…

    • Catherine Scott says:

      Personally I think for pupils that image works just fine. Helps them understand the importance of effort in improving thinking and learning. Dweck also points out that because of fixed mindsets effort is the enemy. You need to help students to see the importance and outcomes of putting in some effort. That said you also need to be teaching them skills and strategies to make that effort effective.

      There’s a lot of examples where just having to work harder produces improved cognition. For example a quite old piece of research showed that a powerful predictor of increased cognitive competence in kids is the requirement by adults that they express themselves clearly. That involves thinking about what they are trying to say.

      The best predictor of increase of iq in adulthood is living abroad. Why? Arguably it’s because old habits no longer work and people have to actively work at adjusting.

      Works at the group level. Research has shown that diversity in the workplace is associated with greater creativity. Again the diversity means people have to be more aware and thoughtful.

      I’d advocate ditching iq entirely in favour of using ‘cognitive competence’. Our culturally conditioned preference for fixed explanations has us trying to rescue some part of iq that’s fixed, ie fluid intelligence. We so want to believe there’s an innate something that isn’t influenced by the environment.

Constructive feedback is always appreciated

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