The Competence Trap (and Why it Keeps You From Trying New Things) - Deepstash

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The Competence Trap (and Why it Keeps You From Trying New Things)

https://www.scotthyoung.com/blog/2020/09/14/the-competence-trap-and-why-it-keeps-you-from-trying-new-things/

scotthyoung.com

The Competence Trap (and Why it Keeps You From Trying New Things)

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Learning rate and limits to learning

Learning rate and limits to learning

Some people take longer to develop the relevant building-block insights to progress in deep subjects like math. The ability to acquire understanding may vary from person to person.

It is highly unlikely that less intelligent people have a limit to deep subjects. The obstacle to learning advanced mathematics is that it may take you longer than a very smart person.

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The learning barrier

An explanation for learning difficulty is that our motivation, moods, and interest play a large role in how difficult it is to keep learning math.

We have a psychological need for autonomy (doing maths because you want to), competence (you feel capable), and relatedness (your teacher or peers may praise you). Any behaviors that worsen these needs will demotivate you to learn.

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Learning engagement and the need for rewards

The better we get at some things, the more we want to do it. Conversely, the worse we fare in other domains, the less we want to work at it.

If we see our engagement as a way of getting rewards (money, respect, achievement, or just fun) for the time we invest, it can create a trap. The better you get at some things, the narrower your set of interests and hobbies may become.

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The narrowing of interests

Our modern society is the product of specialization. Albert Einstein may have been less able to come up with general relativity if he also had to grow his own food and sew his own clothes. Perhaps time constraints would have prevented him from reaching the depths of thinking required. If we enjoy one thing above another, there isn't a problem.

We can also enjoy learning lots of other things that may be more satisfying and interesting than narrow specialization.

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When Ivan Pavlov and his dogs led to the discovery of learned behaviour through repeated exposure, and Edward Thorndike discovered the Law of Effect that stated that rewarded behaviours tended to increase, many psychologists were impelled to separate psychology from armchair introspection and formulated their theories as mathematical formulas.


  • The Drive x Habit Theory. Clark Hull's formula was sEr = D x sHr, which states that excitatory tendency (E) is the result of the drive (D) combined with the habit (H). The drive is nonspecific, such as hunger or thirst. The habit, however, depends on the stimulus (s) and response (r). But the theory turned out to be wrong and even opposite in many cases. 
  • Expectation x Value Theory. Drawing on ideas in economics and game theory, Edward Tolman and Kurt Lewis formulated an alternative account by evaluating motivation based on expectations. Tolman expressed the ideas as the mathematical formula: Subjective Expected Utility = Probability1 * Utility1 + P2U2 + P3U3 + … where subjective expected utility of an action equalled the motivation to act. But, if you expect a reward, why act and not simply passively wait for the expected reward? 

Motivation as change

Donald Hebb realised that existing theories were too focused on reacting to the immediate environment. Thoughts, ideas and goals could be just as strong for triggering action as sights and sounds.

Together with John Atkinson, they noted that the study of motivation had undergone a "paradigm shift", where motivation couldn't be seen as how actions get started, but how the organism decides to change its behaviour from one thing to another.

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Mastering Basic Phrases at Home First

To learn the basics, find a tool that fulfils the two basic requirements for memorizing: repetition and recall.

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Starting phrases include:

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