Hacker News Reader

Comment by bdamm | Hacker News Reader

Isn't this just the pigeonhole problem in reverse? The four toy group kids played with individual toys longer perhaps because there were fewer toys to play with. So... why would we be surprised with this result? Also, how does it lead to the conclusion that this allows "better focus to explore and play more creatively"? I'm not willing to pay the $40 to find out, did anyone do so and can provide the magical answer for why the authors believe their result shows anything about creativity or attention?

View on HN

Not quite. With 4 toys, kids could still switch toys just as frequently as with 16 toys. They would just be expected to return to a toy after setting it down in ~1/5 as much time under one possible null hypothesis.

No, it's not a big bang result. That is a good thing. For a long time, psychology has had a real problem with studies whose reach exceed their grasp. This study appears to me to be an example of exactly the kind of sober, incrementalist work that we need to see more of in psychology. It takes a big hypothesis ("giving kids a lot of toys is harmful to their attention span in the long run"), picks a smaller sub-hypothesis off of it ("if kids have fewer toys, their individual sessions with each toy will be longer") and then tests just that bit. Like they suggest at the end of the abstract, this result indicates that it would be sensible to proceed to the next iteration.

Call it "lean science" if a buzzword is necessary.

> "if kids have fewer toys, their individual sessions with each toy will be longer"

I must be missing something. Isn't this obvious? One hour of play time / 16 toys is less time per toy then one hour of play time / 4 toys.

They're not counting total time spent with each toy. They're counting the length of each instance of playing with a toy.

So if the kid plays with toy A for 1 minute, then toy B for 1 minute, then toy A for 1 minute again, then toy B for 1 minute again, the number of interest for each toy is 1, not 2.

No, that's not obvious.

I would expect if the number of toys didn't have an impact on creativity or attention span, the following:

"Kids switch toys just as often, not matter how many toys they have" And I would expect that because children have limited attention spans - they want to switch after x time.

Yes, the cumulative play time per toy is obvious, but the individual sessions getting longer isn't very obvious.

The result implies, at the very least, that the kids plan out how much to play with each toy based on how many toys there are

What requires that they play with all the toys in an hour? A kid with 16 toys can play with each of them for 30 minutes at a time; a kid with 4 toys can play with each of them for 15 minutes at a time. "Length of session" != "total play time divided by number of toys"

Btw all the toys were new to them. So probably they just spend a few minutes with each to try it out. You're quicker if you only have to try 4 and pick one.

Maybe not. They could have switched toys just as frequently with 4 as with 16 toys.

Accumulated time would be the longer, but not each session.

But I’m not going to pay to find out what they actually did.

It's still hyperbolic to assume that two data points (4 and 16 toys) extrapolate to a linear correlation though. The results could just as well support a hypothesis that the correlation with toy engagement is a bell curve peaking somewhere between 4 and 16.

They used a Wilcoxon test, so there really wasn't any assumption of linearity.

From the paper:

> The hypothesis that fewer toys in children’s environments would improve the quality of play, measured by three variables, was supported.

But given they only conducted a paired difference test for 4 toys and 16 toys, they can only conclude that there's a statistically significant difference between 4 and 16 toys. This is very different than saying fewer toys correlate to any result, because when one says "fewer toys correlate to X", it implies that the correlation stands for any two numbers of toys, and that's not what the study looked at.

Sure. But if we're going to go that far down the path of pedantry, why not get to the even deeper problem with that statement, which is that, strictly speaking, your alternative hypothesis is never supported; you can only fail to reject the null hypothesis.

I don't think it's that pedantic a point. IMHO, I agree this study is incremental and thus too preliminary to draw generalizing conclusions on. Even the paper itself acknowledges a number of major aspects that further research should focus on.

But consider that threads here are already drawing parallels to Montessori education, personal anecdotes, etc. People are used to big bang results and will happily draw conclusions that aligns with their world view even if the wording in a paper isn't exactly what a scientific study actually means to say.

There's an infinite number of functions that can go through two points in cartesian space. What's the simplest? Generally, the simpler the function, the more plausible it is.

I didn't expect that to get downvoted, since it's a mathematical fact. The more degrees of freedom you have in your hypothesis space, the greater the average distance of any particular hypothesis from the correct one. Curse of dimensionality, Occam's razor, etc.

I wasn't the one downvoting, but my guess is that it was related to your claim about plausibility. Just because something is simpler or more plausible it doesn't mean it's more likely to be correct. If it were, there would be no reason to be conducting studies like this

In this case, I did indeed mean more plausible in the sense of higher probability of being correct. If I remembered more of my Machine Learning classes I'd be able to quote you the mathematical proof, but it matches the intuition of Occam's Razor -- models with fewer parameters are, in general, better. You're less likely to overfit, etc.

> If it were, there would be no reason to be conducting studies like this

I don't understand why. The simplest model is to believe there's no relationship (zero parameters). The study gives evidence of a relationship (one parameter). The other commenter was suggesting a parabolic relationship (two parameters), an unnecessary complexity.

The best policy is to believe the simplest model that is consistent with the evidence. If a new study observes the behavior at 6 toys and 8 toys that doesn't line up with the previous study, then I might believe a more complex relationship. Or might go back to believing no relationship.

http://sci-hub.bz/http://www.sciencedirect.com/science/artic...

Reply on news.ycombinator.com