Learning how to Learn.

The 10th key to learning.

What is key in learning? This is the tenth of a number of keys that are meant to bring understanding about what learning is and how leaning can be improved by understanding the message of those keys. This key is about how essential 'learning to learn' is in improving learning and making learning possible. This key sets out the beliefs, strategies and skills that make learning more than accidental random occurrences so people can guide their own learning in this ever changing world.

"The only person who is educated is the one who has learned how to learn and change." Carl Rogers

"Oh, that one could learn to learn in time!" Enrique Solari

What is meant by learning to learn?

Learning to learn is meta-knowledge which includes attitudes, beliefs, strategies and a number of hard to learn skills. The practical application of most of what is written on this site can be characterized as learning to learn especially that contained in the sections called the twelve keys to learning.

As explained in the first key "How the World Works" Learning is three different processes which we may be performing simultaneously in any waking moment. Learning is the converting of data or information into knowledge via these three processes. The result is knowledge that is restructured, added to, or generated. 

Restructured means new information does not fit well with our existing model of reality and that we have to change that model in order for the new information to fit. 

Added to means a new piece of information simply slides into place like a piece in a jigsaw. 

Generated means that new knowledge, that has never existed before, is created by two slightly different processes.

Accommodation (Problem, Conjecture, Error Elimination) as learning.

The first type of learning process, and perhaps the main function of the mind, is to produce solutions to the problems created by our needs. When we are young we must learn in order to build our mental model of reality, to draw a map of that reality which will enable us to solve these problems. This is the only way infants can learn. Piaget called this learning process accommodation. It concerns the dissonance between incoming sensory data and the knowledge (facts and theories) already existing in our minds (our current model of reality). It requires that the new information be accommodated. We make the knowledge in the model consistent or consonant with the new incoming data by changing the model. We change our model of reality so the new information will fit, make sense and be understandable with the rest of our model of reality. In the process of doing this our model of reality is restructured. If this is done well, if we restructure our mental model optimally, the new structure has the new data embedded or integrated into the way we habitually process incoming data or information in our everyday interactions with the external world.

Our newly structured map or model of reality becomes the lens through which we then experience external reality. It enables us to anticipate, or have expectations, of what will occur and what we can make occur. It enables us to both predict the future and to understand what cannot be predicted. This temporary nature of our model occludes 'certainty' reducing the models predictions to probabilities, and ones that must continually be adjusted to produce a closer and closer approximation of reality. That is to say that our maps or models of reality are composed of theories and so called facts that are likely to change at any moment. They are transient or in a state of flux.

Perhaps the most important thing we need to learn is how to test these theories and eliminate the errors in them and then produce new theories to replace them. Obviously the better we get at employing this process in our daily lives the better our learning, in terms of building a personal model of reality, will become. 

This model of reality or cognitive structure is a type of learning that is continually being refined. Although some facts and especially theories are essential to this type of learning, how to improve the application of this process is far more useful for this sort of learning than mere facts and theories themselves. As Postman and Weingartner point out in their book "Linguistics" the process by which we learn is what we really need to learn. While facts and theories are the building blocks of our maps or models of reality we have a greater need for special theories about how theories may be tested and how facts may be found and evaluated:

"What students most need to learn in schools is how to learn. ...It has come to be recognized that the facts, definitions, and generalizations of a discipline - its content - are the end products of the learning process, and tend to have little meaning and durability from the student's point of view if the processes of inquiry which produced them are not understood. It is therefore asserted that the basic task of teaching is to help students to learn how inquiries are made. What is important is not that students be given answers - even 'right' answers - but that they learn how the answers are produced, how knowledge is generated, how learning is conducted. As Jerome Bruner remarks in 'Growth of Mind':"

Building a cognitive toolkit. 

It turns out that this process of learning to learn is not a single process but rather a vast array of cognitive tools. In the book "This Will Make You Smarter" John Brockman asked today's leading intellectuals the following question; "What scientific concept would improve everybody's cognitive toolkit?" In other words, "What are the tools that are used in science that could be used to make everyday learning more efficient?" This question provides an excellent introduction to an important part of understanding what it is to learn to learn. A good part of learning to learn is building a cognitive toolkit. 

Meta-strategies.

Learning to learn is first and foremost leaning strategies for making learning easier, more accurate and just plain possible. These are meta-strategies. Evolution has bequeathed to us a very efficient pattern recognizing brain that can perform miracles of learning from the moment we are born. But it is also flawed. The items that make a cognitive toolkit are mostly devices for overcoming and improving on the flaws embedded in our natural or intuitive way of learning.

These meta-strategies can sometimes be boiled down to simple statements but more is needed to make them effective. Even when we remember and understand these strategies we usually fail to apply them in normal life situations. It is not enough to understand these ideas they have to become a working part of our everyday experience, and they have to be transmittable to others so that they too use them in their everyday experience. Below this site has tried, with the help of edge.org, to provide a partial list of such tools and as far as possible also provide ways of preventing such ideas slipping away especially in ordinary everyday situations.   

A list of possible cognitive tools. 

So, what are likely items that might be in a cognitive toolkit? While an exhaustive list of such tools is impossible here are some likely tools mostly from the book "This Will Make You Smarter" which is a compilation of the answers on edge.org. This list is meant to provide a few sample items for inclusion and does not even represent most of the answers that appear in the book or on edge.org. This book does make you smarter, (but then almost any good book will do that). This book, however, makes you very smart, but only while you are reading it and a little while after. For you to become very smart continuously after reading this book, you need to somehow embed these ideas in your game plan for interacting with the world. You are only that much smarter if you are able to use these tools in your normal habitual interaction with reality.  

1. Knowledge is uncertain. Many of the contributors to 'edge.org' explored various aspects of this idea. "The Uselessness of Certainty" by Carlo Rovelli, "Uncertainty" by Lawrence Krauss and "The Pessimistic Meta-Induction from the History of Science" by Kathryn Schulz. This idea has been discussed at considerable length on the "knowing.html" page of this site, so it will be discussed only briefly here. Knowledge is uncertain for three very different reasons. 

   1/ Knowledge is uncertain for each individual person because we simply do not know who or what is scientifically acceptable. This was always a problem, but it is even more so now we use the Internet to find information. 

   When we are presented with information by (so called) experts or authorities how do we know if we can trust them? How can we know if this information is trustworthy enough for us to decide whether to accept it into our model of reality or not? How can we trust the theories of others sufficiently to be willing to make them our own? How can we trust information coming from outside ourselves that has not been tested by us? How can we discern what is acceptable as knowledge?

   Do you think some information is likely to be true because it is presented in a newspaper? Is it acceptable if it appears in a prestigious scientific journal? Is it acceptable if told to us by someone who's judgment we trust? The answer is no, no and no. But if we can't trust what's in news papers or scientific journals, and we can't trust the judgment of the people we know, what can we trust in? The short answer is that we can't trust any authority, anyone or anything completely.

   2/ Knowledge is uncertain because the tools we use to measure it have limits of exactness. In his answer to the edge question Lawrence Krauss says in part:

   "...uncertainty is a central component of what makes science successful. Being able to quantify uncertainty, and incorporate it into models, is what makes science quantitative, rather than qualitative. Indeed, no number, no measurement, no observable in science is exact. Quoting numbers without attaching an uncertainty to them implies they have, in essence, no meaning."

   3/ Knowledge is also uncertain because neither science nor common sense can produce permanent, certain answers. Science and common sense have always been probabilistic. We just didn't know it. In her answer to the edge question Kathryn Schulz says in part:  

   "Because so many scientific theories from bygone eras have turned out to be wrong, we must assume that most of todays theories will eventually prove incorrect as well. And what goes for science goes in general. Politics, economics technology,law, religion, medicine child rearing education: No matter the domain of life, one generation's verities so often become the next generation's falsehoods that we might as well have a pessimistic meta-induction from the history of everything.

   ...despite its name, this idea is not pessimistic. Or rather, it is only pessimistic if you hate being wrong."

2. Correlation is not a cause.  Most of us are familiar with the idea that a correlation is not a cause, but the idea slips away from us in everyday life, because we have been engineered by evolution to be pattern recognizing creatures.

                   

   The problem is that when we find a correlation between between A and B there are many possibilities. Firstly it could be a coincidence that A and B occur together. To eliminate this possibility we have to check that they occur together fairly often. Secondly there is the possibility that A has caused B. Thirdly there is the possibility that B has caused A even though A seems to have occurred first. Does sleeping make us healthy or does being unhealthy prevent us from seeping? Sometimes A and B occur together because they were both caused by C. Still this is not all the possibilities. A may indeed cause B but only if D also occurs or if E does not occur. 

           

   In this way we can see there may be an almost infinite amount of variables all of which have to be tested in varying combinations to discover what cases what. The more, the number of significant variables involved, the the less likely it is we will discover anything. Outcomes with multiple causes can be difficult or impossible to detect. 

   
   

   As more and more causes are found to be involved our ability to get the same result every time disappears and we are left with a change, a deviation or a result that only happens some of the time. If a change happens fairly consistently this is characterized as being a significant change, a significant deviation or a significant result. But with many variables this becomes imposible and the results are not significant. At that stage scientists have to get lucky to discover anything. What they are dealing with is not a cause or two causes but a causal web.

   

   The terrible thing about cause and effect is our attraction to correlations that any knowledge of science would would immediately disqualify as causes, such as lucky socks, and you have to feel sorry for Mr. Boffo above, whether he bets on the horse with his dog's name or not. It is like our brains are wired to correlate any salient features of the environment that occur simultaneously into a causal belief. The only way to combat this as Sue Blackmore discovered is to turn the idea that 'correlation is not a Cause' into a procedural habit that automatically confronts any perceived correlation. Sue Blackmore, in her answer to the edge question, "Correlation is not a Cause" discovered she could keep the idea from slipping away from her student's minds by beginning each lecture with a strange correlation for the students to consider. She says in part:

   "I soon discovered that this understanding tended to slip away again and again, until I began a new regime, and started every lecture with an invented example to get them thinking.

   "Right", I might say "Suppose it's been discovered (I don't mean it's true) that children who eat more tomato ketchup do worse in their exams. Why could this be?" They would argue that it wasn't true (I'd explain the point of thought experiments again). "But there'd be health warnings on ketchup if it's poisonous" (Just pretend it's true for now please) and then they'd start using their imaginations.

   "There's something in the ketchup that slows down nerves", "Eating ketchup makes you watch more telly instead of doing your homework", "Eating more ketchup means eating more chips and that makes you fat and lazy". Yes, yes, probably wrong but great examples of A causes B — go on. And so to "Stupid people have different taste buds and don't like ketchup", "Maybe if you don't pass your exams your Mum gives you ketchup". And finally " "Poorer people eat more junk food and do less well at school".

   Next week: "Suppose we find that the more often people consult astrologers or psychics the longer they live." "But it can't be true — astrology's bunkum" (Sigh … just pretend it's true for now please.) OK. "Astrologers have a special psychic energy that they radiate to their clients", "Knowing the future means you can avoid dying", "Understanding your horoscope makes you happier and healthier" Yes, yes, excellent ideas, go on. "The older people get the more often they go to psychics", "Being healthy makes you more spiritual and so you seek out spiritual guidance". Yes, yes, keep going, all testable ideas, and finally "Women go to psychics more often and also live longer than men."

   The point is that once you greet any new correlation with "CINAC" [correlation is not a cause] your imagination is let loose."

3. Randomness. Randomness has three laws: 

   Law one states: "There is no such thing as randomness." However, the web of causation for some events is so complex that we can only experience the event as random. There are so many causes and their interaction is so tangled that we have neither the science nor the brains capable of understanding the pattern. However, this does not stop us from trying to discover simple patterns of causation and imposing them on the events. We are driven to do this by our pattern seeking brains.

   Law two states: "Some events are impossible to predict." Singular events always are just a probability and some events have a probability so small that one would think that it was an impossible event. However, as our predictions are probabilities they are therefore not certain. Thus an outlier can occur despite the high probability for it not to occur. Likewise an outlier can occur when there is a low probability for anything to occur. These events simply cannot be predicted. No matter how carefully you follow the causal web acting on the event, you will never be able to predict the event. Despite this, we always expect to keep winning when we are winning, and expect our luck to change when we are loosing.

   Law three states: "Random events behave predictably in aggregate even when they're not predictable individually." In his answer to the edge question Charles Seife "Randomness" says in part:

   "Randomness follows its own set of rules — rules that make the behavior of a random process understandable and predictable.

   These rules state that even though a single random event might be completely unpredictable, a collection of independent random events is extremely predictable — and the larger the number of events, the more predictable they become. The law of large numbers is a mathematical theorem that dictates that repeated, independent random events converge with pinpoint accuracy upon a predictable average behavior. Another powerful mathematical tool, the central limit theorem, tells you exactly how far off that average a given collection of events is likely to be. With these tools, no matter how chaotic, how strange a random behavior might be in the short run, we can turn that behavior into stable, accurate predictions in the long run."

   These three laws etc., if they could be kept uppermost in our minds so that they become part of our habitual interactions with the external world, would indeed be a very useful cognitive tool.

4. Experimentation. In his answer to the edge question "Experimentation" Roger Schank explains that the word experiment has lost its meaning over time. He explains that we tend to associate the word with the experiments we did in science class at school. He goes on to point out that we perform experiments all the time, but because we are unaware that we are performing experiments, we do not apply the rules for good experimentation to those actions. We have in fact allowed a valuable cognitive tool to be disassociated from our everyday experience and we need to reclaim it. In his answer to the edge question Roger Schank say in part:

   "Experimentation is something done by everyone all the time. Babies experiment with what might be good to put in their mouths. Toddlers experiment with various behaviors to see what they can get away with. Teenagers experiment with sex, drugs, and rock and roll. But because people don't really see these things as experiments nor as ways of collecting evidence in support or refutation of hypotheses, they don't learn to think about experimentation as something they constantly do and thus will need to learn to do better.

   Every time we take a prescription drug we are conducting an experiment. But, we don't carefully record the results after each dose, and we don't run controls, and we mix up the variables by not changing only one behavior at a time, so that when we suffer from side effects we can't figure out what might have been the true cause. We do the same thing with personal relationships. When they go wrong, we can't figure out why because the conditions are different in each one.

   Now, while it is difficult if not impossible to conduct controlled experiments in most aspects of our own lives, it is possible to come to understand that we are indeed conducting an experiment when we take a new job, or try a new tactic in a game we are playing, or when we pick a school to attend, or when we try and figure out how someone is feeling, or when we wonder why we ourselves feel the way we do."

   The randomized double-blind control experiment. Richard Dawkins in his answer to the edge question "The Double-Blind Control Experiment" approached this same cognitive tool from a different direction. He suggests that the reason why people do not apply experimental procedure in every day experience may be because they are not familiar with how any good experiment should be designed, that we may be unfamiliar with the biases, randomness, etc. that a well designed experiment is trying to compensate for. He therefore suggests that everybody should learn and understand good experimental procedure as part of their normal learning experience. Dawkins in his answer says in part: 

   "I believe that the double-blind control experiment does double duty. It is more than just an excellent research tool. It also has educational, didactic value in teaching people how to think critically. My thesis is that you needn't actually do double-blind control experiments in order to experience an improvement in your cognitive toolkit."

5. Attention. Attention is how we implement free will. If we do not wish to learn about something we can intentionally not attend to it, and if we do want to lean something we can intentionally attend to it. Jonah Lehrer likens this to moving around a spotlight. Your ability to learn can be more under your control if you control the attention you place on incoming data. In "Control Your Spotlight" Jonah Lehrer says in part:

   "These correlations demonstrate the importance of learning to strategically allocate our attention. When we properly control the spotlight, we can resist negative thoughts and dangerous temptations. We can walk away from fights and improve our odds against addiction. Our decisions are driven by the facts and feelings bouncing around the brain — the allocation of attention allows us to direct this haphazard process, as we consciously select the thoughts we want to think about."

6. The shifting baseline syndrome. How things are in the world is changing all the time, but we are tempted to see how things are at the moment, as what is normal. A baseline is a starting point, the reference point, from which everything else is calculated. Unfortunately baselines seem to be seen as what is normal, and what is normal is seen as how things are when each person first encounters how particular things are in the world. Thus as new people become involved in any project making observations over time the baseline tends to change for that project with their changing perspectives. This is an important cognitive tool. In his answer to the edge question Paul Kedrosky has the following to say in "Shifting Baseline Syndrome" as follows:

   "In 1995 fisheries scientist Daniel Pauly coined a phrase for this troubling ecological obliviousness — he called it "shifting baseline syndrome". Here is how Pauly first described the syndrome:

   "Each generation of fisheries scientist accepts as baseline the stock situation that occurred at the beginning of their careers, and uses this to evaluate changes. When the next generation starts its career, the stocks have further declined, but it is the stocks at that time that serve as a new baseline. The result obviously is a gradual shift of the baseline, a gradual accommodation of the creeping disappearance of resource species…"

   It is blindness, stupidity, intergeneration data obliviousness. Most scientific disciplines have long timelines of data, but many ecological disciplines don't. We are forced to rely on second-hand and anecdotal information — we don't have enough data to know what is normal, so we convince ourselves that this is normal.

   But it often isn't normal. Instead, it is a steadily and insidiously shifting baseline, no different than convincing ourselves that winters have always been this warm, or this snowy. Or convincing ourselves that there have always been this many deer in the forests of eastern North America. Or that current levels of energy consumption per capita in the developed world are normal. All of these are shifting baselines, where our data inadequacy, whether personal or scientific, provides dangerous cover for missing important longer-term changes in the world around us. When you understand shifting baseline syndrome it forces you to continually ask what is normal. Is this? Was that? And, at least as importantly, it asks how we "know" that it's normal. Because, if it isn't, we need to stop shifting the baselines and do something about it before it's too late."

7. The base rate. The base rate in statistics is that science's most important tool and the one non statisticians most frequently misunderstand and overlook. It is however essential in considering any statistical phenomenon, which we do in everyday life all the time. In his answer to the edge question "The Base Rate" Keith Devlin explains in part:

   "Whenever a statistician wants to predict the likelihood of some event based on the available evidence, there are two main sources of information that have to be taken into account:

   1. The evidence itself, for which a reliability figure has to be calculated;
   
   2. The likelihood of the event calculated purely in terms of relative incidence.

   The second figure here is the base rate. Since it is just a number, obtained by the seemingly dull process of counting, it frequently gets overlooked when there is new information, particularly if that new information is obtained by "clever experts" using expensive equipment. In cases where the event is dramatic and scary, like a terrorist attack on an airplane, failure to take account of the base rate can result in wasting massive amounts of effort or money trying to prevent something that is very unlikely."

8. Path dependence. Almost 40% of all human actions can be classified as habits. These habits to a large extent exemplify path dependence. With habits the original reason for performing an action has in all likelihood usually been forgotten or repudiated; nevertheless the habit once in place tends to continue and feels normal. In his answer to the edge question John McWhorter in "Path Dependence" explains in part:

   "In an ideal world all people would spontaneously understand that what political scientists call path dependence explains much more of how the world works than is apparent. Path dependence refers to the fact that often, something that seems normal or inevitable today began with a choice that made sense at a particular time in the past, but survived despite the eclipse of the justification for that choice, because once established, external factors discouraged going into reverse to try other alternatives.

   The paradigm example is the seemingly illogical arrangement of letters on typewriter keyboards. Why not just have the letters in alphabetical order, or arrange them so that the most frequently occurring ones are under the strongest fingers? In fact, the first typewriter tended to jam when typed on too quickly, so its inventor deliberately concocted an arrangement that put A under the ungainly little finger. In addition, the first row was provided with all of the letters in the word typewriter so that salesmen, new to typing, could wangle typing the word using just one row."

9. Einstein's blade in Occam's razor. Occam's razor is about the fact that complications that are not necessary should also be unlikely to occur, and is often stated in the form "If a number of theories about an event all seem equally likely in that everything else seems equal, then the simplest theory is to be preferred. Einstein improved on this idea when he restated the idea a little more effectively. In his answer to the edge question "Einstein's Blade in Occam's Razor" Kai Krause draws our attention to this:

         

   "My hesitation towards overuse of parsimony was expressed perfectly in the quote by Albert Einstein, arguably the counterpart "blade" to Ockham's razor: "Things should be made as simple as possible — but not simpler"  Shaving away non-essential conjectures is a good thing, a worthy inclusion in "everybody's toolkit" — and so is the corollary: not to overdo it!" 

    

10. Collective intelligence. We are beginning to become aware in science, that intelligence is actually collective action, that in sufficient numbers, becomes intelligence. In his answer to the edge question Matt Ridley in "Collective Intelligence" expresses the idea that any intelligence including our own may be superior because of emergent collective intelligence rather than individual intelligence:  

    "The key to human achievement is not individual intelligence at all. The reason human beings dominate the planet is not because they have big brains: Neanderthals had big brains but were just another kind of predatory ape. Evolving a 1200-cc brain and a lot of fancy software like language was necessary but not sufficient for civilization. The reason some economies work better than others is certainly not because they have cleverer people in charge, and the reason some places make great discoveries is not because they have smarter people.

    Human achievement is entirely a networking phenomenon. It is by putting brains together through the division of labor — through trade and specialization — that human society stumbled upon a way to raise the living standards, carrying capacity, technological virtuosity and knowledge base of the species. We can see this in all sorts of phenomena: the correlation between technology and connected population size in Pacific islands; the collapse of technology in people who became isolated, like native Tasmanians; the success of trading city states in Greece, Italy, Holland and south-east Asia; the creative consequences of trade."

11. Cumulative error. Cumulative error is about information transformations. The more transformations that information goes through the more likely there is to be errors. With some forms of error these transcription errors can be a source of creativity and improvements as with the mutations in evolution and the embellishment of myths and legends. However, most of these changes are for the worse as the idea is to reproduce information perfectly. It then follows that, if we know that changes are going to occur we try to design systems to compensate for such changes. In his answer to the edge question "Cumulative error" Jaron Lanier says in part:

    "It is the stuff of children's games. In the game of "telephone," a secret message is whispered from child to child until it is announced out loud by the final recipient. To the delight of all, the message is typically transformed into something new and bizarre, no matter the sincerity and care given to each retelling.

12. Falsifiability or refutability. This is the idea that an assertion, hypothesis or theory is scientific only when there is the logical possibility that it can be contradicted by an observation or the outcome of a physical experiment. That something is "falsifiable" does not mean it is false; rather it means, that if it is false, then some observation or experiment will produce a reproducible result that is in conflict with it. Popper points out that no number of confirming instances will ever provide proof (and thus the certainty) of an assertion. At the same time a single anomaly can throw an assertion into serious doubt and (at least) temporarily disprove or refute it. In this way Popper also reveals that knowledge is provisional, temporary and likely to change.

    This idea, as one might guess, was championed by the philosopher Karl Popper and has to stand as the epitome of science for the simple reason that humans are flawed creatures. Humans will, if left without this guide to scientific rigor, seek to try and confirm any hypothesis we may encounter regardless of the paucity of evidence to justify its existence. In his book "Don't Believe Everything You Think" Thomas Kida puts it like this: "Our tendency to confirm is so ingrained in our cognitive makeup that we confirm even if we don't have a prior belief or expectation...". We tend to try and confirm what we believe, what we conjecture, what we are told, and anything else that does not conflict with our current model of reality. In his book Kida provides a wide variety of differing examples of the errors, misguided heuristics, and misunderstandings that this confirmation bias perpetuates.

    If we set out to disprove our hypotheses as a matter of procedural rigor (be they scientific or everyday) instead of setting out to confirm them, it is less likely we will be led astray by confirmation bias. While the history of science may teach us that scientific theories come to be accepted above all because of their successes (as Sokal and Bricmont believe) none the less theories in astronomy are refuted all the time while theories in astrology are never refuted despite a fairly constant stream of incorrect predictions. Astrology does not change but astronomy is in a constant state of flux. Thus by Popper's estimation astrology is not science while astronomy is.

Meta-growth-attitude and meta-self-belief. 

These meta-self-beliefs are what we believe about our ability to change ourselves and the world around us. It is what has elsewhere been called a growth mindset. This belief has been studied extensively by Carol Dweck and her colleagues. Dweck discovered that people, depending on their upbringing, their nurturing, their environmental contingencies, tended to fall fairly evenly into two categories of belief about change. This is not to say that the people in each group strongly believed one way or the other but that people held a wide spectrum of various beliefs that averaged into one group or the other. Some people tended to believe that they could change themselves and the world around them by means of effort, hard work and persistence. This group she called the growth mindset group. The other people tended to believe their lot was fixed at birth and that they could do nothing to change themselves or their world. This group she called the fixed mindset group.

Dweck discovered, that whichever beliefs about change these people held, had an enormous impact on their lives. Those with a growth mindset she discovered were better off in every way. They were happier, more productive, more successful etc. However, what is most significant to us here is that those with a growth mindset learned better. Why did they learn better? Two reasons. They learned better because they understood that they needed to make an effort to learn. Those with a fixed mindset tended to see making an effort to learn as an indicator of low intelligence. Secondly, they learned better because they believed they could learn. They believed that no skill or area of knowledge was beyond them, and that all they needed to do in order to learn was to put in sufficient effort or hard work.

Dweck also discovered that these groups were not stable, and that people could easily be shifted from one group to the other by means of simple interventions. This is an incredibly important discovery because it allows people to chose which group they wish to be in. It is not just an accident or random occurrence which group they are in. It is not just a matter of what was done to nurture them in the past. It is possible with this meta knowledge to place oneself in the growth mindset group as an act of freewill.

Unstable beliefs. 

People usually tend to think their personal beliefs are very stable entities that do not vary at all. There is some reason to believe, however, that our personal beliefs might be quite unstable. Beliefs may in fact change from moment to moment. Good arguments, solid evidence etc. may cause us to change our minds, if only for a moment, till we can marshal counter arguments and evidence to rejustify our original beliefs. Sure we can find out the beliefs of one person today and check again years later, and those beliefs may be exactly the same. However, it simply does not follow that beliefs once installed are permanent stable entities. Those beliefs need not have remained unchanged all that time. Those beliefs may have drifted back and forth and even have radically changed back and forth during that time. When we have certain beliefs we tend to place ourselves in circumstances that reinforce those beliefs thus we see those beliefs as unchanging. We do this often by reiterating our beliefs to ourselves and others. However, when we run into circumstances that refute those beliefs we may in fact have our beliefs considerably changed, at least temporarily.

This being the case long term change in what we believe may simply be a change in the circumstances of our environment which after some time nudges us to reinforce different beliefs to our previous beliefs over a further long period of time. Change the environment permanently and the beliefs change sort of permanently. Rather than an epiphany being necessary for a mind to change, a change may occur because the temporary change in our beliefs keeps happening till eventually it becomes so pressing that we have to integrate it with our other beliefs. The dissonance may cause us to restructure our model of reality so it is fully integrated into that model.  

Priming. 

Very simple interventions have been shown in various social psychology research experiments to change, not only our beliefs, but how we feel, how we walk and what we think, all on a temporary basis. This type of research is called priming. In priming research it has been shown that very small interventions (environmental changes) can make us susceptible to certain beliefs. For instance it can enable us to overcome our prejudice temporarily. Simply by being reminded of the achievements of blacks we can become less prejudiced against them. Thus watching black people winning at the Olympics can temporarily enable us to become less prejudiced against them. These temporary influences if made a permanent part of our environment would enable us to change and become better and morally stronger people. A few well placed words or pictures can change us for the better if often repeated.

Primed for growth. 

Most importantly for our purposes, experiments in priming show us how little is needed in the form of intervention to change our beliefs and in the case of Dwecks two mindsets how easily people can be channeled (nudged) toward one set of beliefs rather than the other. Indeed Dweck's experiments involved very little in the way of intervention often no more that a couple of spoken words that changed praise of a person into praise of effort. In other words we can prime our children to be more oriented toward growth and and to believe, that they can through effort and hard work, change the world around them. Also we can with the knowledge of how this priming intervention works take control of our own beliefs and thus be able to perpetuate, change and sculpt our own beliefs so that we too believe that through effort and hard work we can change the world around us.

Sculpting our beliefs. 

These remarkable interventions are neither complex nor difficult to perform, although they are somewhat counter intuitive. It is just a matter of having the environment so organized as to show the absolute superiority of the ability to learn over any other ability. If your environment continually shows you that you are improving at whatever you are learning then you will believe you can continue to learn. If your environment continually shows you that working hard at learning enables you to accomplish great things you will want to continue to work hard at learning and thus accomplish. If your environment continually shows you that effort to learn pays off with increased skills and ability, you will want to make the best effort you can in all you are trying to do. If your environment continually tells you that persisting in trying to learn and trying to do brings results, eventually you will persist more and learn more. It's all about determining and forming these beliefs and embedding them so completely they the become part of our mental model of reality.

Meta-belief interventions. 

Dweck and colleagues invented many ways to perform this sort of intervention. As this is discussed in detail on the self-theories page it will only be discussed here briefly Firstly, the mere presentation of the mindset concept by itself was found to significantly move people toward a belief that the world could be changed by them.  

1. Science. Dweck discovered that nature nurture debate in the science of intelligence and genius had a significant influence on whether people believed they could change the world or not. Those who believed that their fate was determined by their genes also tended to believe that they were limited by those genes and thus were not motivated to try hard. Thus a simple small article that produced evidence for the nurture argument could temporarily orient people to believing they could change the world.  

2. Praising. Dweck discovered, counter intuitive though it seems, praising people tended to produce a belief that people could not change the world. On the other hand she found that praising hard work, effort and persistence tended to reinforce a belief that people can learn anything and change the world.  

3. Criticizing. Although we tend to want to bolster people's by telling them they have done well, even if they havn't, this is counter productive to producing a growth belief. Dweck and coleagues found, again, counter intuitively, that criticism worked to promote a growth belief. She discovered that criticizing effort, and hard work, if people's efforts were weak or they did not work hard, was likely to induce a belief that the world could be changed and anything learned. 

4. Drawing attention to improvement. Likewise, Dweck and her associates found that drawing attention to progress or improvement similarly induced a belief that any skill would eventually be learned and any ability would eventually be learned.

Creativity as learning. 

Creativity is the second type of learning process. Of course creativity plays a part in updating our model or map of reality. We must be creative in order to to invent new conjecture needed to resolve the incompatibilities in our map of reality. In this way creativity requires many of the same cognitive tools as are required for updating our models of reality. These same tools inform the processes of propagating new, novel, unique knowledge. 

Creativity requires large amounts of facts and theories. Unlike mere trial and error adjustment of our model of reality, creativity requires that we hold vast amounts of data in our brains. It does not matter much what this data is only that we have large amounts of data that we can recall and it is woven intricately together so that it is part of our personal model of reality. This large database of knowledge is the essential requirement for any type of expertese and is one of the most important preconditions for creativity. The bigger the database of subject knowledge the more likely a person is to be creative.  

From inspiration to contribution. While creation is always involved in the solving the problems of satisfying our needs, creation is also about what motivates us to be creative. What we need to know in every sphere of subject matter is what was going on in the minds of those who made discoveries or produced the ideas in the past; why were they looking in that area, what were the problems they were trying to solve. This not only relates facts, generalizations and theory to reality, but turns, that which is essentially boring to the mind (facts and theories) into an adventure of discovery, an exciting game or story, which will interest and perhaps inspire those learning, to not only want to learn more, but to maybe contribute. This is not only learned from others but also can be learned by stepping back and examining our own actions in learning. 

The transient nature of facts and theories. If the knowledge found in our personal maps of reality were not enough to covince us that all facts and theories are mere impermanent and temporary constructs, then creativity makes us certain of this. Every act of creativity creates new knowledge that continually replaces, improves and refines the knowledge it replaces. In this way although large amounts of subject knowledge are essential for creativity it becomes clear that it is the questions and not the answers that are truly important. The questions, the arguments, and the how of finding the answers remain when facts and theories are altered or erased. The facts, theories (the major content of our maps of reality) are ephemeral and insubstantial, ever changing and becoming something else. They are here one moment and maybe gone the next.

Creativity for the love of conjecture and creativity. There is a kind of creativity that is not about changing our map of reality to accommodate information that currently does not fit, nor is it really about problem solving as such. It is about generating something new, novel and unique not to solve a problem but rather simply for its own sake. If we are unafraid of being wrong we can explore scenarios that we know to be wrong. This kind of creativity is a special kind of learning that can only be performed if we are willing to ignore the dogma within and formulate conjecture for the love of conjecture. We can formulate conjecture when our personal map of reality or our theories have been partially invalidated or we can also formulate them when there is a problem, but with this kind of creativity our theories have not been disconfirmed in any way, nor is there any problem. We can even form conjectures when there is no problem at all and no disconformation of our maps of reality.

All creative generation starts with somehow ignoring the rush to judgment, the dogma within, and this type of creativity is no different. This type of creativity is called by many names, day dreaming, free associating, or as Kelly describes it as loosening of the constructs. Creativity for the love of it happens when our maps of reality are mostly ignored or temporarly restructured into alternate usually unlikely realities. This type of creativity is in a sense doing the very opposite of taking a conjecture tested in reality and accomodating it into our maps of reality, thus revising those maps. It is rather about evisioning, imagining new realities and then testing those against reality. This kind of creativity requires the blurring of thought boundaries. It is about the bleeding of ideas one into the other. It is about the enabling of temporary chaos from which a new order may be carved. This is the creativity that can be brought about by combining things that have no reason to be brought together and which are illogical to be brought together. This kind of creativity is creativity for its own sake, bringing about the new novel and unique when no need for it exists. This does not mean, however, that it has no use. Indeed it might solve problems that we had not even thought of and might never have thought of. This is the kind of creativity that helps us despite our not knowing what we need to know it.

Creative meta-strategies and meta-beliefs. 

These meta-beliefs and meta-strategies to enhance creation are covered in the pages of this site concerned with creativity and thus will only be discussed here briefly. 

Inborn potential for creativity and genius and meta-strategies for how to preserve it.

There are inborn potentials to being creative that most people lose through our current socialization processes that could be encouraged instead of being discouraged. The thesis of the genius page is that we are nearly all born with the potential to be great, a genius, eminent or highly creative and that social conditions in our lives are such that for most of us this does not happen. Some potential abilities are lost because social circumstances conspire to prevent or hinder their development. These potentials seem to be very difficult to try to reacquire later in life, although perhaps not impossible.  

Meta-strategies for creative self improvement and the facilitation of the same in others.

There are strategies that if made part of our cognitive toolkit that would ensure that almost every human was creative. This is discussed fully on this site's creativity page. The main things to understand about creativity are: 

1. Firstly, that it has to be intrinsically motivated and that attempts to motivate it by others will fail. Creativity only takes place in environments that are self-determined. Any attempts to control creativity will fail. 

2. Secondly, that it requires about 10,000 hours to acquire the skills and knowledge needed to be able to make a significant contribution. The importance of the creativity varies with this skill and domain knowledge.

3. Thirdly, creativity is 'order' generated out of 'chaos' and requires the ability to bring disparate ideas together into a gestalt of something new and unique. Thus creativity generally cannot be achieved by staying within a single field. Indeed to increase the likelihood of creativity one should expose one's self to differing knowledge domains and indeed change who you talk to and where you go as much as possible. In other words expose yourself to ideas outside your comfort zone.

4. Fourthly, creativity takes place mostly in the unconscious. Thus unconscious processes need to have time and place allowed for them.

5. Fifthly, creativity requires postponement of judgment both by ones self and by others.

Meta-strategies for implementing social conditions that induce greater creativity in societies.

There are social conditions, that if in place, tend to make people creative by means of how they interact with one another. In his book "Where Good Ideas Come From" Steven Johnson lays out most of these social conditions for creativity. This is also covered on this site's sociocreativity page.

1. Adjacent possible. Innovations can only happen when all the pieces are in place for them to happen. This is elaborated on in the answer to the edge question "The Koliedoscopic Discovery Engine" by Clifford Pickover in which he says in part:

   "When we examine discoveries in science and mathematics, in hindsight we often find that if one scientist did not make a particular discovery, some other individual would have done so within a few months or years of the discovery. Most scientists, as Newton said, stood on the shoulders of giants to see the world just a bit further along the horizon. Often, more than one individual creates essentially the same device or discovers the same scientific law at about the same time, but for various reasons, including sheer luck, history sometimes remembers only the more famous discoverer." 

2. Liquid networks. Innovation and creativity happens through the modeling of skills and communication of ideas. In times gone by this meant putting more and more people in one place like a city. These days with telephones and the Internet ideas can often be communicated better and easier when people never meet physically.

3. The slow hunch. Creativity comes slowly not with two bits of information coming together but with many bits of information coming together thus providing another reason for communication and people being connected. 

4. Error. Innovation depends on society's to make and tolerate errors which is an important part of serendipity. Some of the most important innovations and creative works were mistakes which highly creative people were able to recognize as being informational rather than just wrong.

5. Serendipity. Fortunate accidents are the most important social generators of creativity. There are various ways to induce chaos and thus serendipity such as brain storming and De Bono's ideas. These ideas do not work unless they are part of your normal interaction with the world. Brainstorming is constrained by peoples fear of looking stupid. In his answer to the edge question Jason Zweig suggests that we all can increase the likelihood our coming up with creative ideas by intentionally exposing ourselves to areas of knowledge that are not part of our habitual style of interaction with the world. "Structured serendipity". Jason Zweig

6. Exaption. Creativity works best at the interface between domains of knowledge where knowledge in one domain illuminates information in a different domain. Ideas are hijacked from one domain to another.

7. Platforms. This is where one technology opens up the possibility of a new type of creativity. Computers for instance opened up the possibility of programing them with software rather than have the programs wired in. A whole new type of creativity was possible that was dependent on the existence of computers.

8. The fourth quadrant. As more and more people are able to be creative the need for any extrinsic motivation becomes less and less necessary and this greases the creative wheels because creativity works better with intrinsic motivation and extrinsic motivation, for the most part, is detrimental to it.   

9. The commons. Creativity works best in open systems where all people have full access to all the information available. As all new ideas are built on old ideas the access to any and all information becomes essential. Structures like patents and copyright which essentially suppress the flow of information are a blight on creativity. Open systems. Thomas A. Bass

Prodigies and meta-strategies for helping them achieve their full potential.

There are special people who for whatever reasons show early creativity. Prodigies are discussed fully on this site's giftedness page. Prodigies can be encouraged and mentored to reach their full potential.

(1) Do not discourage inborn potentials. Instill in gifted people the belief they can with effort learn anything. 

(2) Facilitate creative strategies in prodigies. Remember the first rule of creation is to enable intrinsic motivation.

(3) Do place prodigies in creative communities. Remember creativity comes from sharing our own ideas and sharing the ideas of others in return.

The assimilation of culturally heritable common knowledge as learning. 

The third type of learning process is what teachers and parents more usually understand to be learning. That is the absorbing or assimilating of the information currently in the body of knowledge accepted by our culture. That is to say it is passing of our culture's world view on to the next generation. It is this kind of leaning that makes us different to other animals and gives us our main evolutionary advantage.

There is, however, an assumption about this kind of learning. It is assumed that because others have found this knowledge to be mostly consistent it can simply be added to what is in a person's current mental model without causing any conflict or dissonance. It is assumed that this knowledge is additive and does not require any restructuring of the mental model or map. It is assumed that because the common knowledge model of reality is consonant, personal models of reality should not find it inconsistent with themselves. It is assumed the information can simply be memorized. These unfortunately are false assumptions.

Sometimes reversion to accommodation. 

This kind of learning of our cultural heritage of knowledge then, sometimes is a simple absorption or assimilation process, as has been assumed. But at other times, for whatever reason, the new information does in fact conflict with the information already in our mental model and has to be accommodated. This is a problem because we usually have no way we could test this new knowledge ourselves and yet we are expected to restructure our mental models on the basis of it. Also the testing of so much information would be so time consuming as to allow only the tiniest amount of such information to be absorbed. 

This heritable body of common knowledge can be divided into 4 distinct types, (1) so called facts, (2) theories, (3) the skills by which facts and theories are arrived at or found when we need it (meta skills), (4) the meta facts and meta theories that allow us to determine which data is true facts and theories. They allow us to discriminate between fact and fiction, theory and pseudo theory.   

Facts. Of these of these types of knowledge facts are the least important. Facts are items that stand alone and are not well connected to anything else. They are extremely difficult to remember, and are mostly useless in memory except where they are embedded as part of a skill or knowledge base and often work best unconsciously. When they are used consciously it is not necessary that they be recalled from our memories, and the shear amount of them precludes that we can store and recall many of them. However, they are easily found, when they are needed,  Facts can be used as needed by means of recall not from our personal memories but from an external memory that is part of our heritable knowledge (Poppers third world) held in cyberspace for us on the web and accessed by means of search engines, those miricales of modern day technology.

As Postman and Weingartner point out in their book "Linguistics"  facts are becoming obsolescent with increasing quickness.

"'Fact Obsolescence' is one of the most vivid signs of our times. What are students to do with a random collection of obsolete facts? How do students learn to evaluate what they know? What have they been taught that will enable them to ask the questions that need to be asked? How will they continue to learn?"

Not so long ago the amount of knowledge in the world was not so great that a great man might feel himself able to encompass it all or at least not feel he needed any special knowledge about how to go about learning. But our cultural heritage of common knowledge grows in this age as a geometric progression, and no one, genius or not, can keep pace with it. Because of this, the skills involved in the learning process have become the most important thing we can learn. Instead of learning what the latest facts are we have to start learning how those facts came into being what people did and why they did it to discover them. In other words learning not what but how it was done. In their essay in "Learning for Tomorrow" Howard Kirchenbaum and Sydney Simon had this to say:

"...in a world in which the amount of knowledge increases geometrically, and in which no one can keep pace with it, we need to change the emphasis from what to learn to how to learn. The new curriculum projects have emphasized the process of the discipline, the ways in which the historian or scientist goes about investigating his subject. The shift has been from content to process. Learning how to learn has become more important than the specific facts and concepts learned."

Theories. Theories are what hold facts together and thus many facts can be derived from them. They are highly interconnected and connected and so are easier to remember. They are both useful and used. Even as facts become temporary and less important than the skills involved in finding and evaluating them so have theories. Instead of learning what the latest theories are we have to start learning how those theories came into being what people did and why they did it to create them. In other words learning not what but how it was done. Theory replaces facts and how to find and evaluate theories replaces both of them.

The meta-skills of learning to learn.

Learning how to learn has always involved learning a number of these meta-skills. These skills are essential for learning at a high level to take place. They include the following; learning to talk, learning how to read, learning how to write, learning how to use a computer, learning how to find books and other stored information such as searching the Internet. 

Meta-skills. 

As time goes by the importance of these various meta-skills is changing. Some skills like learning to use search engines are becoming more and more important. All meta-skills were less important in the past, where all the information we needed to know could be memorized and and recalled to be used when we needed it. But now, what we need to know is vast and not permanent during our lifetimes. It is so much and changing so fast that there is no way we can keep it all in our heads. Our whole way of knowing and using this knowledge is very different to how people knew and used knowledge in the past. Now we need to be able to find information when we need it and be able to convert it into knowledge we can use on the spot.    

"In a world that is constantly changing, there is no one subject or set of subjects that will serve you for the foreseeable future, let alone for the rest of your life. The most important skill to acquire now is learning how to learn." futurist John Nesbit

Learning how to find data when we need it. 

We can improve the economy of storage in our minds by omitting nearly all these transient facts and a lot of transient theory. We can concentrate on process and especially the skill of finding information and assembling it into knowledge on the fly. In terms of vocation facts no longer really need to be remembered. (Who needs a multiplication table in these days of pocket calculators?) To a very large extent theories no longer need to be remembered in detail either. These things can be stored in books and more especially in computers and drawn upon as needed. Knowing where to find facts and theories and how to find them is what is now important.

Learning in the current age is very different to what has gone before. These days computer and Internet savvy children no longer have to rely on their memories to dredge up specific information. Facts and even theories do not have to be remembered. All that has to be remembered is what key words can be used to access that information from the Internet. The memories of these students, what Don Tapscot calls Net Geners, are very different in that their memories carry much less specific factual or theoretical information. Their memories contain very general information mostly relating to where specific information can be found and particularly where to find it on the net. Net Geners tend to actually feel stupider when they are away from their computer because they no longer have that specific information at their fingertips. It is no wonder that the new cellphones that have Internet access are so popular with Net Geners. That way they are never cut off from access to facts and theories when they might need them.

Of course we never did have to remember every little fact or theory even in the quite distant past. Although the way we were tested often gave the impression that we needed to remember every little bit of information. There was always the possibility of looking information up in books and journals. But now with the Internet we have the ability to find information so quickly that it takes virtually the same time as if we were remembering it. As Marshall McLuhan might say the Internet has truly become an extension of our central nervous system.  

Piaget in "To Understand is to Invent" called into question why exams were concerned almost totally with memorizing and that what was tested was the ability to recall. He pointed out that a student was simply regurgitating answers: "(...as if he were condemned never to be able to use his books once he was out of school!)."

Perhaps the most important type of learning to learn or meta learning that we now perform is the learning of how to to find the information that we need when we need to find it and learning the meta-skill of being able to convert such information into usable knowledge quickly and efficiently as we need it on the run.

Learning how to deternine if data can be trusted.  This in a sense is the most important knowledge we need to learn. Despite this we will only look at here briefly, because we have thoroughly dicussed this subject on this site's page called "knowing" which can be reached by clicking here.  

"You can learn new things at any time in your life if you're willing to be a beginner. If you actually learn to like being a beginner, the whole world opens up to you." Barbara Sher

We still need to remember large amounts of facts and theories. 

In his book "Curious" Ian Leslie suggests that some education reformers have misunderstood the message above and somehow have come to believe that the purpose of education is only to teach children how to learn. He says in part: 

"The contemporary version of this progressive philosophy is associated with the phrase 'learning skills' (sometimes called 'higher order skills', 'thinking skills' or more recently, twenty-first century skills... The proponents of 'learning skills' are more concerned with how schools prepare pupils for the world of work. They share the progressive belief that schools should spend less time on teaching specific knowledge of specific subjects. Instead, they argue, schools should focus on abstract skills like creativity, problem-solving, critical thought and curiosity. Such skills it is said will equip children for whatever the future throws at them." 

The implication is that somehow the learning of all other facts and theories need not be persued until we have use for them. This site is not sure if such a reformist idea does indeed exist, but it clearly cannot be correct if it does. Despite the change in the kind of knowledge being held in people's memories, it should be obvious that a certain amount of facts and theories still have to be learned as they have an important part to play.

1. Firstly our personal maps or models of reality are constructed out of facts and theories. Without facts and theories there would be no personal maps of reality. 

2. Secondly creativity requires large fields of data to be packed into our memories. Without large amounts of data availible to be manipulated within our brains we could not create anything. 

3. It is only when we are absorbing the massive data that has been accumulated by our ancestors over billions of years and bequethed to us, that we realize that it is simply beyond our capacity to absorb it all. Despite the above, all this information is still available to us and we can access it as needed from the external memory devices where it is held.

The desire for life long learning as a superior life script. 

Learning how to learn ultimately is the meta-learning of life long learning. It is this that provides us with, not just the intrinsic pleasure of feeling competent, not merely that we have the skills to cope with whatever life throws at us, but also gives us a kind of meta-competence confidence, the feeling that we can shoot for the stars and succeed. This is the confident feeling that we are competent at learning itself. It is the feeling that life is our oyster or a feast from which we can pick and choose as we please. These feelings of competence and meta-competence are what makes learning efficient and also a delight. There is nothing more frustrating in life than trying to learn and seemingly never getting anywhere. The efficient learning, that is the result of having learned well how to learn, and the belief that we can learn anything and everything, enables greater more than usual satisfaction in learning, and thus provides us with euphoric pleasure. Both the enjoyment provided by this meta-learning and the added joy that is obtained from feeling competent at learning are essential in motivating us to continue our academic and skill learning through our entire lives. Not only that, but this learning to learn is in itself an addictive way of living our lives. In a way learning to learn is the ultimate habit that ensures we become life long learners who are well satisfied with their lives. Thus we become people with a superior script for living our lives.