In terms of construct validity, construct is referring to something that can’t be directly observed but measured by observing other things that are associated with it. In order to measure the construct validity of a test, we are determining if the test as a whole measuring the concept that it is intended to measure. An example would be a test measuring quality of life. Quality of life is more of an abstract construct and not a specific, black and white, construct. Construct validity makes sure that the test is actually measuring quality of life as a whole and not just the child’s pain, social economic status, level of mobility, etc. Most research looks at construct validity because you can do a comparison with a “gold standard” test and if there is an association then we can typically say that the tests are measuring the same construct.
Content validity is measuring whether or not the test is representative of all aspects of the construct. We determine if there are any aspects missing from the test or if there are irrelevant aspects included in the test.
As for p-level vs p-value, I believe these are the same thing. The term p-value is more commonly used and it determines the level of significance. Are you thinking about alpha level vs p-value? The alpha level is the number we choose to evaluate the p-value against. Typically, the alpha level is set at 0.05. You compare the p-value with the alpha level to determine whether or not the data are statistically significant.
Let us know if you have any other questions about this!