1. I think the data is better than no data, and I do think that most professionals would take it into thoughtful consideration. I would treat them as valid and reliable, insofar as testing data generally is. For example, the psychometrics are not substantially different in quality than, say, the linking data for predicted achievement between the WISC and the WIAT, or the KABC and the KTEA (not as good at that between the WJ Cog and Ach, which are truly co-normed), which are the basis for the kind of aptitude-achievement discrepancy analyses used in several learning disability diagnostic models.
2. I would agree that this is probably easier to discuss in the particular than in the general...so here's an anecdotal example, using SBLM data (which is, of course, based on a completely different quantitative model of IQ, but just for the sake of discussion...). A sibling group was assessed with scores in the GT range, with a range of scores on the same instrument upwards of 40 points. An illustration of the functional difference in educational needs, using a simple metric: the lowest scoring individual finished K-12 education with four years acceleration, while the highest scoring person reached that milestone accelerated eight years.
Here's another example, with better group data: some years ago, Lubinski & Benbow published research compiling a selection of outcomes for a cohort of students scoring in the top one in 10,000, which includes some comparisons to the top 1%.
http://www.appstate.edu/~webbrm/jap2001.pdf
Of course, in making educational decisions, more than IQ ought to be considered, but it certainly suggests some starting points for discussion. In the first example, while one can propose a situation in which the most-accelerated person might possibly have been maintainable with fewer skips, it is extremely unlikely that the least-accelerated person could have handled four more years of acceleration.
Last edited by aeh; 01/04/20 08:25 AM.
