Most of them learn randomly. First a child experiences a problem: I touched the stove, and I got hurt. Very soon she learns a solution to prevent such problems: Don’t touch stoves. Then she experiences similar problems and begins to improve her solution: Don’t touch things that make fire or turn red. This new solution works for more than the just problems with stoves -- it helps her in dealing with far more problems than her first solution did. So with solutions, problems are easier to understand which means that with solutions, problems are more easily controlled, even if one has never experienced a specific problem before.
Then she learns a logic: Beware of electric and gas lines and machines because our flesh is conductive and not flame-retardant. Notice that a logic works for more than one solution; some logics apply to only a few solutions while others apply to billions or more. So with logic, solutions are easier to understand which means that problems are even more controllable, solutions are more easily understood, the task of determining which solutions to apply in certain problems is made much simpler, and finally solutions are more effortlessly applied in those problems.
But this process of learning is far too chaotic. There is far too much entropy, i.e. the amount of chaos, in this method of learning. More chaos means more possibilities for error. Consider language. The more possibilities that a statement could be interpreted into, the more ambiguous the statement is. More ambiguity equates to more error in understanding, which slows the learning process. So how do we make this less random? How do we reduce entropy in the learning process?
Let’s revisit the process of learning. First a newborn learns problems like, ‘When I touch the stove, I get hurt.’ Imagine these as points in the empty space of a newborn’s mind (see Figure 1). Then they learn more problems and they begin to learn some solutions like, ‘Don’t touch hot things.’ These are vectors in the space (see Figure 2).
A vector is a geometric entity that has both length and direction; think of it as an arrow. Note that when a solution
changes from ‘Don’t touch the stove,’ to ‘Don’t touch things that make fire or turn red,’ this change is represented as the lengthening and/or realigning of a vector.
Note that the more similar problems you learn, the more likely you are to realize that you should make a new solution, i.e. the more points you’ve learned that lie along a straight path in your 'knowledge network', the more likely you are to realize that you should put a vector along that path. If you make this realization,
then a new vector is installed along that line. Hence you’ve learned a new solution by projecting and more importantly, you’ll be able to tackle new similar problems that you’ve never experienced nor heard of previously. Then the newborn learns logic as in, ‘Beware of electric and gas lines and machines because our flesh is conductive and not flame-retardant.’ This is represented by the localized superstructure of vectors (see Figure 3).
Note that the more similar solutions you learn, the more likely you are to realize that you should make a new logic, i.e. the more vectors you’ve learned that are connected with each other, the more likely you are to realize that you should make a superstructure of the those vectors. If you make this realization, then a new superstructure of logic is installed along those vectors. Hence you’ve learned a new logic by projecting and more importantly, you’ll be able to tackle new similar problems and solutions that you’ve never experienced nor heard of previously.
With a logic, solutions and problems are less necessary to be learned because they can now be projected instantaneously, i.e. on the fly. What does it mean to be able to project solutions and problems? Well most of this article is my mind's projections. I did not learn these things from a teacher, nor by reading. Instead, I learned them by projecting. The more logic one learns, the more accurately she will be able to project solutions and problems, i.e. learn solutions and problems without the help of teachers or even reading. So how does the mind learn logic? Or rather, how does the mind learn knowledge? First lets look at some examples of various terminology in various fields regarding knowledge.
What is knowledge?
Knowledge is all that can be learned by a mind. Therefore, knowledge is the entire set of problems, solutions, and logic in the Universe. So a person’s knowledge is the complete set of problems, solutions, and logic learned by their mind. Each mind has its own set of problems, solutions, and logic as its knowledge set. Think of knowledge as the untapped raw material from a mine; untapped only by newborns that is. Note that the mine occupies an N-dimensional space.
- Problems are points in this space; problems are 0th order knowledge.
- Solutions are the vectors that project points; solutions are 1st order knowledge.
- Logic is the superstructure of the vectors; logic is 2nd order knowledge.
- The Knowledge Network is the graphical representation of all the points and vectors representing all knowledge in the universe (see Figure 4).
- A person’s knowledge set is that person’s version of the knowledge network.
- Note that all knowledge is connected either directly or indirectly to all other knowledge, i.e. all knowledge is connected. What connects it? Logic.
- It stands to reason that all logic is at least partially the same since logic is pure, i.e. it is completely void of problems and solutions. Well, not all logic is void of field-specific terminology though. It seems we must define 2 types of logic.
- 2nd order knowledge containing field-specific terms is....................... Field-specific Logic
- 2nd order knowledge void of field-specific terms is................................... General Logic
- 0th, 1st, and 2nd order material of a specific field is.................. Field-specific Knowledge
- 0th, 1st, and 2nd order material irrespective of any field is................ General Knowledge
- It stands to reason that we could interchange 0th and 1st order general knowledge with 0th and 1st order field-specific knowledge in order to postulate new knowledge in other fields; that is to say that we could interchange solutions and problems from one field into those of another while keeping the logic constant.
- Every general logic should be applied to every problems and solution in a field before dubbing that general logic as unusable for said problems or solution in said field. This is the Socratic Method, a negative process of hypothesis elimination.
- More specifically, every field-specific logic should be converted into its general form, and then systematically attempted in other problems and solutions in all other fields.
------------------------------------------------------------------------------------------------------------------- -- Dated Mar/2013
Note that problems, solutions, and logics are all ideas. Humans think with ideas. This means being able to notice contradictions between ideas. When someone notices a contradiction between ideas, he knows that one or both of them is wrong, and he continues by making a judgement call about which one that is. The way that we make judgment calls is by considering the contradicting ideas as rival theories -- only one of them can be right. Actually, since both of them might be wrong, we might need to brainstorm a new theory. And the way to adjudicate between the rival theories is to consider the reasons for each, and to criticize the reasons, and to criticize the criticisms. (Note that each criticism is an explanation of a flaw in an idea. Note also that noticing a flaw in an idea is a type of noticing a contradiction between two ideas.)
Learning is an iterative process of (1) noticing a problem, (2) solving that problem, and then possibly noticing another problem in the last solution, which brings the person back to step (1). And this continues step-by-step from birth until death, from problem to problem to problem.
Its important to note the difference between an abstract problem and a human problem. An abstract problem is like this: 2+2=?. A human problem is like this: I don't know the solution to the abstract problem, 2+2=?, and I want to know the solution. So for this example, the solution to the human problem is 'To acquire the knowledge that 2+2=4' and the solution to the abstract problem is '4'. A problem is a conflict between two or more ideas. And its solution resolves the conflict. This is true for both abstract problems and human problems.
For example, Einstein noticed a conflict between Newton's laws and Maxwells laws. This is the abstract problem. And Einstein wanted to solve it, so this is his human problem. He solved it with his Special Theory of Relativity (it resolved the conflict between Newton's laws and Maxwells laws.) A human problem means that a person is interested in solving an abstract problem. This raises the question: What happens to the learning process when a person is not interested in solving an abstract problem? It grinds to a halt because the person is not interested in thinking about the problem. Learning works best when the person is interested.
What are the implications on understanding each other? Answer here and here.
What are the implications on parenting and education? Answer here and here. -------------------------------------------------------------------------------------------------------------------