There's a typo in that pdf that I just noticed. For average standard error, the formula is missing a square. You can find the correct formulas here:
"Average Standard Error" is the only formula that is different than you might expect. It might be better called "Root-Mean-Variance." We used this formula instead of a simple average because this formula is more directly comparable to the RMS.
Yes, you would want to compare the RMSE between EBK and IDW.
A large root-mean-square-standardized usually indicates the model is unstable. The most common reason for this is because the Gaussian semivariogram is very unstable if the nugget is very small, compared to the sill. Note that Stable with parameter=2 and K-Bessel with parameter=10 both correspond to the Gaussian semivariogram (it's a special case of both).
EDIT: Oh, I understand what you were asking. It doesn't make much sense to compare RMS and average standard error from different models, but it is useful to compare them within the same model because if the difference between them is large, it indicates that the model may have problems.