Knowledge valuation network
All granular pieces of knowledge processed by the brain are instantly evaluated for their relevance, coherence, and value. We instantly know if information is understandable and useful. We also often instantly notice when it is inconsistent, incoherent or irrelevant.
Unusual and surprising bits of knowledge are highly valued, however, the probability isn't the best reflection of value from the brain's point of view. There are highly unlikely events of low significance (e.g. asteroid strike in a remote planetary system), and likely events that change one's life (e.g. the answer to "Will you marry me?").
The emotional brain and the rational brain
Knowledge valuation network is an evaluation system based on a resultant of emotional and rational valuations. Emotional valuations will connect information with rewards in primitive brain centers responsible for hunger, thirst, sex drive, etc. Rational valuations will be knowledge-based. An example of pure emotional valuation comes from an answer to "Where is the nearest fast food shop?". Knowledge-based valuations may be more complex and highly networked, i.e. dependent on a network of subvaluations. Answer to "Which book is best for my exam?" is evaluated through one's goals that include passing exam leading to getting a degree affecting job prospects and contributing to lifetime goals. Emotional and rational valuations segregate anatomically. The emotional valuations come from what has metaphorically been described as older portions of the triune brain: reptilian and paleommamalian structures. For example, a specific stimulus processed by the thalamus may send separate signals to the amygdala for an emotional valuation and to the neocortex for a rational valuation. The emotional brain is philogenetically older. Personality and education determine if rational valuations can control or override emotional valuations.
Decision tree in fast thinking
Knowledge valuation network is the network of memory connections that determine the value of an individual piece of knowledge. If learning is interpreted as a task, valuation network will determine the perceived task value.
In computational terms, knowledge valuation network can be compared to a decision tree. Goals and emotions determine core values at the root of the tree. Semantic connections between pieces of knowledge can be interpreted as fractional value transfer from goals to details. Well-organized semantic network of well-consolidated and well-chosen knowledge needs milliseconds to make expert decisions. This is what Kahneman calls automatic "fast thinking" (if you are interested in tough problems that require slow problem solving, see How to solve any problem?). The same kind of processes, that underlie decision making or problem solving, participate in knowledge valuation. Like many expert decisions, the valuation is fast and it is often running with low participation of conscious intentionality. In short, we sometime die to know things without fully being able to explain why. This process is hardly under our own control, let alone the control of the teacher at school. For efficient learning, valuations must be high.
Figure: xefer is a tool that helps understand knowledge as a network. It relies on semantic links between Wikipedia articles.Try it
Valuation network in education
The brain builds a valuation network in the course of learning over years and decades. Through optimization in sleep and via forgetting, the network is polished and smoothed up for efficient operation. This makes it easy to take valuation shortcuts. A student choosing a book may no longer see his exam in the full context of his whole life. He might have developed a quick shortcut: "In the next 3 months, all I want to do is to pass geology".
Knowledge valuation network is highly specialized and very different from individual to individual. The balance between reason and emotions will differ. The balance between goals will differ. The valuation network will shape differently in the mind of a criminal, and differently in the mind of a researcher with lofty goals based on the good of mankind.
The development of the network will depend on the personality, lifetime experience, and the environment. Some personality characteristics, e.g. short temper, may favor developing a more criminal mindset. Some traumatic events in early life may favor developing biased networks based on single-minded obsessions. The environment and the available knowledge will determine passions, interests, goals, and network subvaluations.
I believe that the ideal path towards developing healthy network valuations is a childhood sheltered from trauma and chronic stress, with no external stressors shaping emotional valuations, and plenty of play, and self-learning. All strategies that promote healthy brain development will also promote rich, highly-individualized, and efficient valuation network. Those will underlie a sparkling learn drive. All educators agree that we want to help kids have a good grip on their emotional life and build smart, creative, and knowledgeable brains.
The chief problem of educational system is a cookie-cutter approach in which all kids are fed the same knowledge in an industrial fashion with little respect to the key component of efficient learning: the learn drive. Learn drive is a perfect computational device that matches the current status of the semantic network representing knowledge in the brain with current input produced by the knowledge valuation network in response to information available in the environment. If the kid insists he must see that YouTube video, his own brain is the best authority. All interference will affect future independence and creativity.
While a lecturing teacher may spend 45 minutes to feed a child with a long string of symbols that produce low valuations, and negligible memories, the same kid, with access to Google, within 3-5 minutes, will identify pieces of information with high valuations, and easy coding for lifetime retention. For kids well trained in the process, the efficiency of knowledge acquisition may be an order of magnitude higher in self-learning. When I say "order of magnitude", I am just being modest and conservative. I do not want to run into accusations of hyperbole. I included a couple of examples of specific comparisons in this text elsewhere (e.g. 13 years of school in a month or 1600% acceleration of learning during vacation).
Where I speak of golden nuggets of knowledge, Peter Thiel speaks of the power law: a small set of core skills honed to perfection can produce power returns.
Knowledge valuation that affects the course of life
I have my own striking example of the power of the valuation network in confrontation with the education system:
In 1985, I computed the approximate function of optimum intervals for knowledge review needed for developing long-term memories. This was the birth to SuperMemo. Originally, the function was applicable using a pen and paper. Within a few months, I realized the system was extremely powerful. I knew I could double its power with the use of a computer. However, I did not know anyone who could write learning software based on my math. In those days, the entire population of programmers in Poland was made of old timers doing Fortran or Cobol on mainframes, or a growing mass of amateur enthusiasts working with microcomputers such as ZX 81, Commodore 64, or ZX Spectrum. I decided to write the program myself. I had no programming skills though. I was a student of computer science and I asked my teachers for help. However, our only course of programming was the assembly language of Datapoint. Those skills were great for playing with registers and coming up with 11*11=121. I wanted to learn something more useful for programming SuperMemo. My school kept demanding that I learn to compute the resistance of an electronic circuit, or learn symbolic integration. My knowledge valuation network produced a simple output: programming skills -> SuperMemo -> faster learning (in all fields, incl. electronics or calculus). I was determined to learn programming. My school was determined to stop me (by loading other compulsory courses). In desperation, I enrolled in University of Economics, which had a course of algorithmic languages. The course focused on Pascal. I had to do my normal load of classes and do my Pascal in extra time. That course was nice, but we did all learning in theory. On paper. There were very few PCs at Polish universities in those days (1986) and most practical applications run on mainframes called Odra (produced for Soviet block in Poland as of 1960). When I finally got my first computer: ZX Spectrum (Jan 4, 1986), I could finally start learning programming languages. Before the computer arrived, I started writing my first program! On paper. It was a program for organizing my day (sort of Plan in SuperMemo). Not much later, I was able to learn Pascal too. First I had to reduce the bad impact of school and cut the load of classes. I struck a deal with my teacher of electronic circuits. I would do some high-pass filter calculations for him, and this would be a chance to improve my Pascal skills. The program took many hours to write and was a monumental waste of time. It was a perfect example of bad learning. I hardly understood how my own program worked. However, it was still better than just learning diagrams. For programming, the learning was good and I improved my skills a lot.
It is hard to express it in words to those who do not know programming, but the difference of knowledge valuations between university courses and doing one's own programming is comparable to the size difference between the plum and the Jupiter. While my colleagues suffered through boring lectures in electronics and metrology, I could make my start. I would learn nothing at school. I would learn a bit in my extracurricular course of Pascal. However, only the practical knowledge backed up by passion and clear goals mattered. By December 1987, my effort culminated in writing the first version of SuperMemo, which totally changed the course of my life. Open mind of my supervisor Dr Zbigniew Kierzowski let me devote my whole Master's Thesis to the subject of SuperMemo. Happy 80th birthday Professor Kierzkowski! It was pretty unusual for a student to make his own determination on that scale, and then compound it with the fact that the thesis was written in English. This fact is not unusual today, but it involved a big administrative and tactical battle back in 1989.My school almost destroyed SuperMemo, i.e. the major source of my present joy. There was no malice involved. Most of my college teachers were fantastic people. It was the system that was designed to squeeze students through a rigid curriculum rather than give them space for creative expression that is the best basis of education.
My school was actively trying to block me from accomplishing the most important thing that underlay my entire professional life and future. If I was a bit more compliant, more conformist, more prone to social pressures, I would be a "better" student, invest more time in the theory of electronic circuits, calculus, metrology, and abstract algebra. As a result, this article would have never been written. This site would not exist.
I would not trade my present life for any other type of career in research or industry. I survived the denial attack by providing resistance based on strong knowledge valuation network.