There are students who say things like “I can’t do the math but I understand the concepts” and this just nonsense. The ones who answer the conceptual questions correctly are almost always those who can do the math.
Why do the they believe what they believe? The simplest two explanations I can think of is that they are mistaken about their grasp on the concepts (when you ask them conceptual-level questions, they answer incorrectly), or they are mistaken about their inability to do the math (they feel insecure before quantitative tests, but score high). Is one of these the case?
There’s a combination of both, but there seem to be far more in this first category. To some extent it seems like it is an example of the Dunning-Kruger effect. And I suspect that some of the people here who are convinced that one can understand physics without understanding the math may be also running into Dunning-Kruger issues.
Given that the Dunning-Kruger effect may be a combination of noisy estimates and hidden, different scales (how do we weight the 1500-2500 separate skills involved in driving when deciding who’s in the top 10%), could we extend competence from both ends toward the middle?
What I mean is that an essentially correct but very fuzzy understanding may constrain your anticipations in many different circumstances, but may not tightly constrain them—anybody knows you’re not going to get a <1ms ping from another continent, and a car coming towards you makes a higher pitched noise than it does going away from you, but most people couldn’t diagnose the 500 mile email or calculate the speed of the car from the frequency change.
On the other side, many people just learning physics can carry out the calculus, as long as they have the formula in front of them and the problem’s explicitly stated; but would have trouble generalizing the formula to all the real-life situations in which it’s applicable.
As the intuition becomes more and more precise, it gets closer to math. As the math becomes more and more intuitive, the situations in which its applications are evident grow.
An engineer is never going to be successful with just intuition, because he needs very precise results. But, depending on your use case, generality may be more useful than precision. This seems more useful than trying to decide which one is “real” understanding.
Why do the they believe what they believe? The simplest two explanations I can think of is that they are mistaken about their grasp on the concepts (when you ask them conceptual-level questions, they answer incorrectly), or they are mistaken about their inability to do the math (they feel insecure before quantitative tests, but score high). Is one of these the case?
There’s a combination of both, but there seem to be far more in this first category. To some extent it seems like it is an example of the Dunning-Kruger effect. And I suspect that some of the people here who are convinced that one can understand physics without understanding the math may be also running into Dunning-Kruger issues.
Given that the Dunning-Kruger effect may be a combination of noisy estimates and hidden, different scales (how do we weight the 1500-2500 separate skills involved in driving when deciding who’s in the top 10%), could we extend competence from both ends toward the middle?
What I mean is that an essentially correct but very fuzzy understanding may constrain your anticipations in many different circumstances, but may not tightly constrain them—anybody knows you’re not going to get a <1ms ping from another continent, and a car coming towards you makes a higher pitched noise than it does going away from you, but most people couldn’t diagnose the 500 mile email or calculate the speed of the car from the frequency change.
On the other side, many people just learning physics can carry out the calculus, as long as they have the formula in front of them and the problem’s explicitly stated; but would have trouble generalizing the formula to all the real-life situations in which it’s applicable.
As the intuition becomes more and more precise, it gets closer to math. As the math becomes more and more intuitive, the situations in which its applications are evident grow.
An engineer is never going to be successful with just intuition, because he needs very precise results. But, depending on your use case, generality may be more useful than precision. This seems more useful than trying to decide which one is “real” understanding.