August 8, 2008

Prediction Time

Following up on my last post on Charles Murray's new book, real education, it's time to see what Murray predicts will be the results from the grand experiment he proposes:

On measures involving interpersonal and intrapersonal ability. I expect statistically significant but substantively modest gains. On measures of actual knowledge, the experimental group will score dramatically higher than the members of the comparison group, perhaps 30-plus percentile points higher (technically more than a standard deviation). On measures of reading and math achievement, the differences will be no more than 15 to 20 percentile points (about half a standard deviation). Three years after the experiment ends, all of the differences will have shrunk. The differences in reading and math will be no more than 8 to 12 percentile points (no more than a third of a standard deviation) and may have disappeared altogether.

More formally, I predict that the magnitude of each academic effect will be a function of the g loading of the measure. Measures of retention of simple factual material have the lowest g loadings and will show the largest gains. For highly g-loaded measures such as reading comprehension and math, what has been accomplished by the last half-century of preschool and elementary school will be shown to be about as good as we can do, no matter how much money is spent.


This is a decent prediction. The I think that Murray overestimates the ease at which facts can be taught to and retained by low-IQ students and underestimates their ability with respect to math and reading comprehension.

Facts are difficult to learn because facts must be mostly learned on a case by case basis which is not readily amenable to acceleration. Math and reading (decoding and comprehension) are easier to teach because these skills, can be accelerated (even though teaching language and vocabulary remain problematic). But I knew that from the Follow through and the Baltimore Curriculum Project data. The data shows that we can get at least about three-quarters to a standard deviation improvement on average by the end of elementary school, better if we discount the schools that are so incompetent that they are unable to implement well-tested programs with fidelity.

Murray's point with respect to fade-out is well taken, but I'll leave that for another post.

4 comments:

Anonymous said...

>>For highly g-loaded measures such as reading comprehension and math, what has been accomplished by the last half-century of preschool and elementary school will be shown to be about as good as we can do, no matter how much money is spent.<<

KD: I assume you disagree with the above quote.

Also, good instruction can change g--at least the way it is currently measured-- correct?

In my experience with Direct Instruction Corrective Reading Comprehension B this is almost certainly true.

KDeRosa said...

We have data up to about fifth/sixth grade that says otherwise, so I do disagree.

Past fifth grade the data is scant, so I have no basis for agreeing or disagreeing. I do think that most kids going through even a good instructional program like DI will continue to need compensatory instruction for learning to continue at the same pace.

What we need, as Murray suggests, is a follow through program that takes us to 8th or 12th grade.

I am dubious that goo instruction can substantiaklly affect g after age 10 or so. I do, however, think that kids with low-g can learn more than they currently do with improved instruction.

Anonymous said...

okay, I give . . .

what's a layman's explanation of a g-load?

TangoMan said...

what's a layman's explanation of a g-load?

Here's a simple example that you can even field-test.

Digit Span versus Reverse Digit Span.

There is little correlation between g and remembering a string of numbers but there is a significant correlation between g and remembering those numbers in reverse order and processing them in the same time-frame as the forward digit span.

All mental tasks are not equal in complexity.