Hi!
Just thought I'd add onto snowisawesome's answers with a few diagrams. Skewness is basically used in Futher Math as a qualitative descriptor of the asymmetrical nature of a distribution. Here's a diagram showing how positive and negative skew appear on a probability distribution function.

Although the naming convention may seem counter-intuitive at first, as it does not refer to the direction in which the curve is 'leaning' towards, it is easier to remember if you instead remember that it describes the side with a stretched tail. For example, a positively skewed distribution will have a longer tail towards the more positive end. Also take note of the relative magnitude of the mean, median and mode for each type of skew.
As you mentioned, skew can also be exhibited in box plots.
So yes, as snowisawesome already said, your example is correct, as a negative skew results from a larger amount of data points with a higher value, resulting in an increased mean, whereas the positively skewed set has a much lower mean due to a large amount of data points with lower values. Hopefully these diagrams help it make a little more sense.