University or College Study:

[Hawkeye]

Situation Factors and Relevance
It seems clear that what is relevant about a situation is just those features that it shares with other comparable situations - for example, how much something costs is relevant to a purchase decision because cost is something that mostly matters whenever people buy something.

However, determining which features are relevant about a situation requires us to associate it with some set of comparable situations, but the trouble is determining which situations are comparable depends on knowing which features are relevant. This inherent circularity poses what is called the frame problem (think of it as gathering all the relevant information inside a frame). The frame problem was first really noticed in artificial intelligence, when researchers tried to program robots to solve supposedly simple everyday tasks like cleaning a messy room since humans do it everyday, how hard could it be? Very hard indeed, as it turned out because on closer inspection there are literally thousands of interacting factors which vary from day today and room to room which humans take in a glance.

Having said that, when confronting a particular situation, our brains do not generate a long list of questions about all the possible details that might be relevant. Rather, we simply plumb automatically and usually unconsciously our extensive database of memories, images, experiences, cultural norms, and imagined outcomes, and seamlessly insert whatever details are necessary in order to complete the picture. In everyday situations this might be fine but outside that frame we might get it completely and utterly wrong because in this process we may insert details that may not be true for a particular situation. For example, students asked about the colour of a classroom blackboard recalled it as being green (the usual colour) even though the board in question was blue. In cases like this, a careful person ought to respond that he can’t answer the question accurately without being given more information. But because the “filling in" process happens instantaneously and effortlessly, we are typically unaware that it is even taking place; thus it doesn't occur to us that anything is missing, so the frame problem should warn us that when we do this, we are bound to make mistakes, and we do it all the time.

In fact, we make the mistake again and again but sadly, no matter how many times we fail to predict behaviour or events correctly, we can always explain away our mistakes in terms of things that we didn't know at the time, so sweeping the frame problem under the carpet, always convincing ourselves that this time we are going to get it right, without ever learning what it is that we are doing wrong. Indeed the more ingrained our belief system the more we are disposed to be uncritical and ignore or explain away everything that questions it. It is this difference between making sense of behavior and predicting it that is responsible for many of the failures of common sense reasoning. And if this difference poses difficulties for dealing with individual behaviour, the problem gets only more pronounced when dealing with the behavior of groups or nations.

For those who want to go further I recommend the excellent book by Duncan Watts called "Everything is Obvious" (its also available as a eBook)

[Hawkeye]

We all state facts and opinions all the time and here is a note that might help you understand what these ideas mean so that you can better utilise them in your project or dissertation. You might also want to disagree with me or add some ideas of your own.

Facts and what may be deduced from them
We use the idea of “fact” all the time; so what is a fact; how do you know when you have a fact? For example, if I say there is a thing called gravity is that a fact, if I say that 62% of students on my IT course passed is that a fact also? If I look at a fact like "gravity" (called a natural fact) and a fact like "62% of students passed in the May cohort" (called a nominal fact) - is there any difference between these two kinds of fact?

So is it possible to prove a fact; decide whether it is true or not. The answer is that I can find proofs of gravity and I can find proofs of the pass rate. Therefore, a fact can be independently checked in some way. Now for nominal facts you may find that some people will not accept your proof. To take a perhaps extreme example, suppose I say that the existence of God or Allah or Krishna is a fact then I might cite proofs and you might or might not find them convincing but I think you will see that such proofs are not falsifiable (put simply we cannot work out how to test the proposition) and clearly they are not accepted by all as true. Whereas gravity is always true, can be tested by anybody and cannot be ignored by anyone.

Let us say you are a Muslim or Hindu or Christian; that is a nominal fact about you that is true and I accept that fact, but my acceptance of that fact does not mean I also automatically accept that Islam or Hinduism or Christianity as holding the truth. In other words what I do or think based on a supposed nominal fact will depend on me not the fact itself. Notice that with natural facts I cannot, for example, rationally decide that I don’t believe in gravity. But, suppose that I irrationally decide that I don’t believe in gravity, that is a matter for me but what I cannot do is avoid its effects because I do not believe in it. Put simply, you believing something to be a fact is NOT a proof of the fact itself and conversely, you not believing in a natural fact does not free you from it's effects,

Now suppose I ask you IF a fact can change what will you say? A fact is a piece of information that can be independently checked. In simple terms you can get the same information from several places. However, a fact sometimes can be changed and sometime not. Please be careful here; I CANNOT change the pass rate of the May cohort BUT I can in principle change the pass rate for later cohorts. Natural facts like gravity cannot be changed by you but some natural facts do change, for example, if you were asked how many planets there are in the solar system then when I was at school the answer was 9 but now there are more. Similarity, there were thought to be just two species of elephant; African and Asian but quite recently a third species has been found.

Nominal facts are important because they crop up all the time and we can in principle do something about them, change them in some way. For example: with a nominal fact I can ignore it, try to forget about it or just regard it as of no value (consider that we cannot do that with natural facts like gravity). We can take active steps to change a nominal fact. For example if I am not satisfied with a 62% pass rate for my students I can try to change the course or students on it in some way to get that pass rate up (or even down or unchanged).

Facts and Decisions
One important idea associated with all this is that there is a tenuous link between a fact and a decision. That is we cannot be sure that a given fact will always generate a certain decision. This means we might arrive at a whole series of possible decisions from a given fact or set of facts. It follows that there is not necessarily a logical link between a fact and a given decision. In simple terms, if I tell you the pass rate for your cohort is 62%, that is a fact, but I cannot know what decision you might make based on that bit of information. So any fact may lead to any number of different decisions, even diametrically opposite ones.

Opinions and why they are different from facts
In contrast to a fact an opinion is person's personal beliefs, thoughts or feelings about something; these may be rationally held and based on facts or quite irrational. Notice that you cannot independently check an opinion as you could a fact. For example, if someone tells you their birthday is 26 April 1942 then you can independently get that checked. In contrast if you ask someone do they like birthday parties then you cannot check that by some other route, you can ONLY reliably get such an answer from one source? You might also notice that we might reasonably make a decision on a fact but we would be much less sure of ourselves if we made the same decision based on an opinion.

A good way to keep in mind that it is all too easy to confuse fact and opinion is to recall the aphorism - "Always state the opinion on which your facts are based"

[Hawkeye]

Explaining the curse of work (see http://www.newscientist.com/article/mg20126901.300)

Here is another perspective on leadership and working relationships and its about the famous Parkinson's Law. It is 1944, and there is a war on. In a joint army and air force headquarters somewhere in England, Major Parkinson must oil the administrative wheels of the fight against Nazi Germany. The stream of vital paperwork from on high is more like a flood, perpetually threatening to engulf him. Then disaster strikes. The chief of the base, the air vice-marshal, goes on leave. His deputy, an army colonel, falls sick. The colonel's deputy, an air force wing commander, is called away on urgent business. Major Parkinson is left to soldier on alone. At that point, an odd thing happens - nothing at all. The paper flood ceases; the war goes on regardless. As Major Parkinson later mused: "There had never been anything to do. We'd just been making work for each other."

That feeling might be familiar to many working in large organisations, where decisions can seem to be bounced between layers of management in a whirl of consultation, circulation, deliberation and delegation. It led Major Parkinson - in civilian dress, C. Northcote Parkinson, naval historian, theorist of bureaucracy and humourist - to a seminal insight. This is "Parkinson's law", first published in an article of 1955, which states: work expands to fill the time available for its completion. Is there anything more to that "law" than just a cynical slogan? Physicists Peter Klimek, Rudolf Hanel and Stefan Thurner of the MUV think so. They have recreated mathematically the kind of bureaucratic dynamics that Parkinson described anecdotally 50 years ago. Their findings put Parkinson's observations on a scientific footing, but also make productive reading for anyone in charge of organising... well, anything.

Parkinson based his ideas not just on his war experience, but also his historical research. Between 1914 and 1928, he noted, the number of administrators in the British Admiralty increased by almost 80 per cent, while the number of sailors they had to administer fell by a third, and the number of ships by two-thirds. Parkinson suggested a reason: in any hierarchical management structure, people in positions of authority need subordinates, and those extra bodies have to be occupied - regardless of how much there actually is to do.

Parkinson was also interested in other aspects of management dynamics, in particular the workings of committees. How many members can a committee have and still be effective? Parkinson's own guess was based on the 700-year history of England's highest council of state - in its modern incarnation, the UK cabinet. Five times in succession between 1257 and 1955, this cabinet grew from small beginnings to a membership of just over 20. Each time it reached that point, it was replaced by a new, smaller body, which began growing again. This was no coincidence, Parkinson argued: beyond about 20 members, groups become structurally unable to come to consensus. A look around the globe today indicates that the highest executive bodies of most countries have between 13 and 20 members. "Cabinets are commonly constituted with memberships close to Parkinson's limit," says Thurner, "but not above it." And that is not all, says Klimek: the size of the executive is also inversely correlated to measures of life expectancy, adult literacy, economic purchasing power and political stability. "The more members there are, the more likely a country is to be less stable politically, and less developed," he says.

Why should this be? To find out, the researchers constructed a simple network model of a committee. They grouped the nodes of the network - the committee members- in tightly knit clusters with a few further links between clusters tying the overall network together, reflecting the clumping tendencies of like-minded people known to exist in human interactions. To start off, each person in the network had one of two opposing opinions, represented as 0 or 1. At each time step in the model, each member would adopt the opinion held by the majority of their immediate neighbours. Such a process can have two outcomes: either the network will reach a consensus, with 0s or 1s throughout, or it will get stuck at an entrenched disagreement between two factions. A striking transition between these two possibilities emerged as the number of participants grew. Groups with fewer than 20 members tend to reach agreement, whereas those larger than 20 generally splinter into subgroups that agree within themselves, but become frozen in permanent disagreement with each other.

One curious detail in the computer simulations was that there is a particular number of decision-makers that stands out from the trend as being truly, spectacularly bad, tending with alarmingly high probability to lead to deadlock: eight.

Where this effect comes from is unclear. But once again, Parkinson had anticipated it, noting in 1955 that no nation had a cabinet of eight members. Intriguingly, the same is true today, and other committees charged with making momentous decisions tend to fall either side of the bedevilled number: the Bank of England's monetary policy committee, for example, has nine; the US National Security Council has six. So perhaps we all subliminally know the kind of things that Parkinson highlighted and the computer simulations have confirmed. As Parkinson noted, we ignore them at our peril. Charles I was the only British monarch who favoured a council of state of eight members. His decision-making was so notoriously bad that he lost his head.

Bibliography
Parkinson's Law, or The Pursuit of Progress by C. Northcote Parkinson (Pub. Murray, 1958)
Parkinson's Law by Leo Gough, (Pub Infinite Ideas Ltd) ISBN 978-1-906821-34-0 (this is a modern day evaluation and guide)

[Hawkeye]

Before pressing on with my posts on common sense, it is worth taking a moment to think a little about logic and argument. There are two kinds of argument forms: deduction and induction. These are easy to look up in Wikipedia but not so easy to use in practice and often students get in a mess over them, particularly in projects or dissertations.

1. A deductive argument guarantees that the conclusion is true if the premises are true. For example:

If your salary is greater that £5000 and your Tax code is CQ199 then you are entitled to a 10% rebate on your salary.

2. An inductive argument makes it probable the conclusion is true if the premises are true.

It has rained every Thursday for the last 5 weeks, therefore it will rain this Thursday.

Three crucial elements are involved:

Soundness - meaning an argument is sound if and only if the argument is valid and all of its premises are true. For instance:

All men are mortal.
Socrates is a man.
Therefore, Socrates is mortal.

The argument is valid (its form) and the premises are in fact true, therefore the argument is sound. The following argument is valid but not sound:

All organisms with wings can fly.
Penguins have wings.
Therefore, penguins can fly.

Since the first premise is actually false, the argument, though valid, is not sound.

Not Begging the Question - that is the reason you believe the premises to be true MUST be independent of the conclusion otherwise you can always guarantee a particular conclusion. For example, if I say "Either God exists or I'm a monkey's uncle, I am not a monkey's uncle therefore God exists. The ONLY reason this works is that the you believe the first premise '..God exists' but obviously that is ALSO the conclusion. People fall into this trap because they want to believe the conclusion more than you want the truth.

The examples I have used are simple but the arguments you may want to use or understand may be much more subtle and you may miss the fact they are badly formed and have seemingly plausible premises. The trouble I suppose is that often we either don't want to know the truth because it upsets our belief or we are so desperate to 'prove' that we are right we in essence lie to ourselves or suppress our own misgivings. In the long run these kinds of delusion can be very damaging to our thought processes.

Plausibility
In life we are often confronted with arguments where the premises are not necessarily 100% certain - does God exist, is the Bible the Word of God, does my wife love me... In these situations one considers whether the argument is more plausible than its denial - therefore, in general, for an argument to be a good one, we don't require 100% certainty of the truth if the premises. Of course what one person regards as plausible another may totally deny.

One can present a bad argument for a true conclusion. A person may reject your premise because of misinformation, or ignorance of the evidence, or a fallacious objection or the person does not like the conclusion.

[Hawkeye]

Following on from an introductory note on induction and deduction I want to go a little further. Most students can easily recite what these terms mean but only very rarely have I come across students who can use them with confidence. What I mean by this is that if I ask a student "in your project are taking a deductive or inductive stance" they will usually say one or the other and sometimes they will perversely say both (meaning they both have a theory and don't have a theory at the same time!). However, when I ask how does the choice of induction or deduction affect your choice of data I am universally faced with silence - meaning of course that those students don't really know what these terms mean because they cannot use them. These two terms; induction and deduction, need to be thought about when doing a project/dissertation because they help you to know how you are actually thinking about the problem you are trying to solve.

Be honest and ask yourself - "If my study is inductive, how would that help me define the data". Similarly ask yourself, "if I were deductive, how would that help me define the data". If you do not understand the implications of your choice of induction or deduction on the primary data you define and collect then it probably means you have a serious weakness in your research plan.

Some Examples
1. To be very simple, suppose a crime has been committed somewhere along the A3458 road in West Yorkshire. If he were inductive then the Chief Inspector of police would say to his forensic staff “walk along the road looking for evidence” but if he was deductive he would say to his staff “walk along the road looking for a pair of blood stained overalls and black gloves”. You might now like to think about these two ways of thinking and ask why the one is inductive and the other deductive.

2. Suppose I want to show that the “Lose Weight Quick” diet works. I can do this by getting volunteers and putting them on the diet and observing if there is any weight loss over some time period. Assuming that there is some weight loss I can use induction (roughly meaning “more of the same”) to infer or predict let us say that usually the diet works. Now you must understand that this is NOT proof; meaning I cannot say on the basis of my observations that the diet will work for everyone, anywhere and for all time. So all I am really able to do here is infer or predict (that its looks likely) that the diet will work in many cases or if you like I have reduced the level of uncertainly about the efficacy of the diet.

You need now to note that no amount of simple weight observations will tell us WHY the diet works. The only way to find out “why” is to have a theory about it and then form a hypothesis and test it. So I might decide that my theory is that obesity is caused by hormonal malfunctioning triggered by the consumption of particular types of carbohydrate containing foods which lead to insulin secretion and that causes fat to be stored. Armed with this theory I can now devise a way to test it and so this now becomes deductive in nature because I am not just inferring a result I am attempting to explain it in a way that I can test.

You might further note that when we used induction it obviously cannot be used to infer or predict that some other diet called “Fight the Flab” will also work. However, once we have a theory that has been substantiated it might then be possible to indeed say that “Fight the Flab” might work because it is based on the same theory.

[Hawkeye]

Social learning
It is better sometimes to learn from others than to muddle along on your own although no one quite knows how it works but in essence we copy behaviours from what we see around us or perhaps from what we read. However, if we only copy there is a catch because we need innovation to help us cope with change - one cannot copy everything blindly because the information may be wrong, outdated or unavailable. Possible models for social learning might be the:

Conformist Transmission Model - where we copy what is common not what is rare or to put it more simply we as it were follow the crowd.

Copy an expert – this is or can be an excellent strategy; because one hopes that by doing this you feel confident that you are learning the best practice or most relevant and current knowledge.

Copy the most successful – here you might look around and follow those who appear successful and whatever they do therefore might well be good for you. There are obvious dangers here, for example because the latest ‘celeb’ endorses diet X implies nothing about their actual practices or knowledge?
Social learning is in some way underpinned by an implicit trust in others. However, this has its own difficulty perhaps best illustrated by the famous Prisoners Dilemma which shows how in certain circumstances what happens when members of a group trust each other; they can choose a course of action that will bring them the best possible outcome for the group as a whole. But without trust each individual may well aim for his or her best personal outcome - which can lead to the worst possible outcome for all.

In the Prisoner's Dilemma two participants as prisoners who have been jointly charged with a crime (which they did commit) but questioned separately. The police only have enough evidence to be sure of a conviction for a minor offence, but not enough for the more serious crime. The prisoners made a pact that if they were caught they would not confess or turn witness on each other. If both prisoners hold true to their word they will only be convicted of the lesser offence. But the dilemma occurs when the police offer each prisoner a reduced prison term if they confess to the serious offence and give evidence against the other prisoner. This sounds like a good deal, confess and you get the minimum possible term in jail - although your partner will get the maximum. But then you realise that if both you and your partner confess then both will be given the maximum term in prison. So the dilemma is whether you trust your partner to keep quiet - and if you do, should you 'stitch them up' to get out of jail quicker?

It is easy to see from the above how in group leaning you may sadly always find there are individual who sponge on the group, lurking in the background scooping up what others have done but adding little or nothing themselves. Therefore with the above dilemma in mind we may state broadly three ways to learn:

Innovate by individual learning – this means you have to put in the hard graft and in so doing produce something new; not necessarily intrinsically new but you have uncovered the knowledge or worked hard to acquire the skill by your own dedicated and persistent effort - this perhaps is the most rewarding way to learn and has the most lasting benefits.

Observation - acquire new learning by social learning, implying there is a sense of trust from and toward you and a sharing in some sense of the burden involved. It is worth saying here that this form of leaning may easily become total exploitation where you take but give nothing.

Formal Teaching – one must not forget the role of formal teaching where there is an intensive effort to pass on skills and knowledge in a defined setting.

In all learning you must take time out to rest and reflect and just let the learning ‘sink’ in. Research suggests that this might be up to 1/5 of the available time thus you space out learning by thinking about pay offs or tradeoffs. One final point is that in social learning there is a kind of parasitic dimension because eventually you run out of things to copy and then someone has to do the hard graft to gain new skills or knowledge that can then be copied. It follows it only pays in the long term to do social learning if there are some innovators around

Finally, when you copy, other individuals have probably filtered the stuff for you so you have to weight up the relative costs and benefits of sticking to a behaviour you have or inventing/copying a new one. As humans of course we are aware of how quick information gets outdated or a skill lost or no longer needed but you can look to the future, talk about what might happen and consider consequences.

[Hawkeye]

Shared Knowledge and Experiences
Learning is not private, there is a whole community that you can access; a community that values learning and where you can give and take. There is a vast amount of information literally at your finger-tips and its all more or less free, a kind of gift to you from Socrates, Newton, Al Gazali, Hodja, Hawkin, Darwin, Churchill, Feynman, Turing, Von Neumann, the Beatles, Mozart, Bobby Moore, the list is endless and awe inspiring when we think of such giants gifting their thinking to you! Sharing is a vital aspect of learning. One might recall what the Dali Lama said “share your knowledge; it’s a way to achieve immortality”.

In some communities some books or authors are regarded as off limits but this I think is unwise, if you cannot listen to the arguments then you cannot understand them, refute them or even accept them. If you limit your learning in this way then you actually may well let error in. In life when we come across something new we can rationally do one of several things:

1. Modify/update in some way what we already know in the light of new information.
2. We can accept it as completely new information and just add it into our store of knowledge.
3. We can accept the new and that may mean we have to totally throw out something we though previously was sound.
4. Lastly you can examine the new and reject it as unsound.

Of these item 3 is probably emotionally the most difficult to come to terms with because we may well have invested a lot of effort learning something - but it must be done if we are to move forward. Obviously in technology this particular item is a more or less everyday occurrence although it happens in all branches of knowledge where a new bit of information 'forces' you to see a new interpenetration or shows that your current understanding is faulty.

Although this is hard there is nothing worse than showing your ignorance - for example, I was once at a conference and a speaker was presenting a paper on what is called SSM and it was going quite well until one section and almost everyone in the room then knew he was way out of date - don't let that happen to you.

You should always discuss what you find with almost anyone who will listen but obviously it is far better to discuss it without someone who actually knows what he or she is talking about - always be wary of people who tell you what you should or should not study when they themselves are not experts.

If we examine the latest research in social grouping of various kinds, you will learn that we are all influenced by those around us and also more surprisingly those around them. It’s as if a virus is let loose so good humour, kindness and a shared attitude can spread through a group just as much as grumpiness, hate, selfishness and unkindness. So be mindful of your social grouping and inject good things into it and its more or less certain you will be rewarded. Go where the knowledge is and it need not be in your current community but above all don't feel nervous about this but instead feel excitement and wonder. Finally two quotes, the first a warning and the second a shaft of light:

Francis Bacon - The human understanding is not composed of dry light, but is influenced by the will and the emotions, a fact that crates fanciful knowledge, man prefers to believe what he wants to be true

Jacob Bronowski - Knowledge is an unending adventure at the edge of uncertainty

[Hawkeye]

Conspiracy Theories and Denial of the Evidence - You may find this interesting and it has been copied from New Scientist 15th May 2010. Interested to hear what you think or perhaps you have examples? We all need to be aware of these essentially dishonest tactics and not get taken in by them and instead vigorously oppose them, indeed if you look though this board or others you may spot some of these tactics being used.

It will not be easy to see them unless you are on your guard and are prepared to find out the truth and the reason is simple, we all have a tendency to lean towards things we want to be true or support our beliefs and so we sweep under the carpet our doubts but that is a destructive and disreputable route so don't take it.

May Martin McKee, an epidemiologist at the London School of Hygiene and Tropical Medicine who also studies denial, has identified six tactics that all denialist movements use. "I'm not suggesting there is a manual somewhere, but one can see these elements, to varying degrees, in many settings," he says (The European journal of Public Health, vol 19, p2).

1. Allege that there's a conspiracy. Claim that scientific consensus has arisen through collusion rather than the accumulation of evidence.

2. Use fake experts to support your story. "Denial always starts with a cadre of pseudo-experts with some credentials that create a façade of credibility," says Seth Kalichman of the University of Connecticut.

3. Cherry-pick the evidence: trumpet whatever appears to support your case and ignore or rubbish the rest. Carry on trotting out supportive evidence even after it has been discredited.

4. Create impossible standards for your opponents. Claim that the existing evidence is not good enough and demand more. If your opponent comes up with evidence you have demanded, move the goalposts.

5. Use logical fallacies. Hitler opposed smoking, so anti-smoking measures are Nazi. Deliberately misrepresent the scientific consensus and then knock down your straw man.

6. Manufacture doubt. Falsely portray scientists as so divided that basing policy on their advice would be premature. Insist "both sides" must be heard and cry censorship when "dissenting" arguments or experts are rejected.

[Hawkeye]

I wonder what you think of 'doubt'. Is it a good thing or something to be avoided? Certainly, in some circles it is often regarded as bad form to show any doubt and often this extends to ones teachers in that they cannot be questioned. But doubt is the engine for knowledge, its the thing that drives us to find the truth, without the facility of doubt we would end up believing anything. Here are some thoughts:

Rowan Williams said "doubt makes you aware of your capacity for self-delusion, for coddling yourself, making it easy, then the negative moment is essential even within faith."

It does seem that we are made so we live on the edge of certainty and that is what keeps us alive, keeps us thinking, keeps us searching because it is absolutely obvious that we do not know everything about anything. That is why we have to be careful with teachers who have 'found' the answer and then stop looking.

Now of course one can take this too far and you become a pest who simply wants to ask questions without any consequent desire to gain knowledge. But at the same time in Science for example, all knowledge is regarded as provisional, meaning that any scientific fact is in principle open to falsification. There was a time when almost everyone believed in a thing called phlogiston but in the end it was abandoned because there was no evidence for its existence. Similarly, we see Einstein in 1911 proposing his theories which were subsequently shown to be true and they in turn in effect updated Newtons Laws and who knows with all the work at CERN whether Einstein's laws may need modification?

[Hawkeye]

Knowledge – what is it?
There is a difficult topic and philosophers for many centuries have wrestled with the idea but loosely it comes about in two ways: by perception (when we see) and by reasoning (when we think). Plato suggested that in order for something to count as knowledge at least three criteria must apply: a statement (or you can say action) must be justified, must be true, and believed although we do also require that the statement was not arrived at through a defect, flaw, or failure (Blackburn) in which case of course it was not in fact true. However there is general agreement that the following ideas are useful.*

Tacit - this is knowledge that more or less equates to experiences or in simple terms knowledge that you cannot write down in order to pass it on. So it cannot be learned directly from a book it must be practiced and developed by use. For example, it might be possible to read a description of how to ride a bike but you will never have real knowledge of that until you master it yourself by riding a bike.

Implicit – this is rather like tacit knowledge; it is something like instinct, intuition or vibes, we just somehow know something and we did not explicitly learn it or practice it.

Explicit – this is knowledge that is easily (in principle) shared as we have a common language medium by which to disseminate it. That is you can pick up for example a book and gain knowledge about Anglo Saxon’s in England. Notice that one is not learning a skill here as there is no practicing of the knowledge as such.