Following up on the 2010 study, Jaeggi and University of Michigan people have run a Single N-back study on 60 or so children.
- Abstract: http://www.pnas.org/content/early/2011/06/03/1103228108.abstract
- PDF: http://www.pnas.org/content/early/2011/06/03/1103228108.full.pdf
The abstract is confident and the mainstream coverage unquestioning of the basic claim. But reading it, the data did not seem very solid at all - I will forbear from describing my reservations exactly; I have been accused of being biased against n-backing, however, and I'd appreciate outside opinions, especially from people with expertise in the area.
(Background: Jaeggi 2011 in my DNB FAQ. Don't read it unless you can't render the above requested opinion, since it includes my criticisms.)
My primary objection is: perhaps some of the students in both groups got smarter (these are 8-9 year olds and still developing) for reasons independent of the interventions, which caused them to improve on the n-back training task AND on the other intelligence tests (fluid intelligence, Gf). If you separated the "active control" group into high and low improvers post-hoc just like was done for the n-back group, you might see that the active control "high improvers" are even smarter than the n-back "high improvers". We should expect some 8-9 year olds to improve in intelligence or motivation over the course of a month or two, without any intervention.
Basically, this result sucks, because of the artificial post-hoc division into high- and low- responders to n-back training, needed to show a strong "effect". I'm not certain that the effect is artificial; I'd have to spend a lot of time doing some kind of sampling to show how well the data is explained by my alternative hypothesis.
It's definitely legitimate to look at the whole n-back group vs. the whole active control group. Those results there aren't impressive at all. I just can't give any credit for the post-hoc division because I don't know how to properly penalize it and it's clearly self-serving for Jaeggi. It's borderline deceptive that the graphs don't show the unsplit n-back population.
It's unsurprising (probably offering no evidence against my explanation) that the initial average n-back score for the low improvers is higher than the initial average for the high improvers; this is what you'd expect if you split a set of paired samples drawn from the same distribution with no change at all, for example.
Also, on pg 2/6, I don't understand how the t statistics line up with the group sizes.
The groups are ((16 high improvement+16 low improvement)+30 control), so why is it (15), t(15), t(30), and then later t(16)? Does t(n) not mean that it's a t statistic over a population of n? I'm guessing so. I assume the t is an unpaired student's t-test, which of course assumes the distributions compared are normal. I'm not sure if that's demonstrated, but it may be obvious to experts (it's not to me).
Disclaimer: I did dual n-back for a month or so, and got stuck at 5. I haven't resumed, though I may do so in the future.
Not usually. Numbers in brackets after a well-known statistic normally represent parameters for that statistic's distribution; in the case of a t-test the bracketed number would be the number of degrees of freedom, which might be one less than the sample size (for a one-sample t-test) or two less than the sum of sample sizes (for an equal variances two-sample t-test).
(Disclaimer: I haven't read the paper.)
[Edited for unambiguity.]