Why some schools have problems reaching success
Submitted by admin on Thu, 10/27/2011 - 9:57am
Some things seem so obvious after they've been pointed out to you. I was pointed to a Web file from a Boston writer, Glenn MacDonald, a quantitative analyst using quantitative statistical methods, that has a fascinating study of Boston area public schools. After much study of Boston Magazine's ranking of 135 schools, he came up with a load of mistakes that no publication should ever make.
But that was beside the point to me; I don't fret about Boston schools rankings. But what did fascinate me was the factors that he found had the most bearing on the success or failures of public schools. He considered all the usual suspects in comparison with the schools' graduation rankings. This is where the answers should be simply intuitive but don't seem to be.
McDonald started comparing things.
"Per-pupil spending seems like it ought to matter, but it shows very little statistical correlation to quant scores. Student/teacher ratios, sports-team counts and AP classes also seem like they ought to matter, but the numbers don't support this.
"Per-capita income, on the other hand, matters. The percentage of students receiving lunch subsidies matters even more. In fact, this last factor (the precise calculation I used was adding the percentage of students receiving free lunch and half of the percentage of students receiving partially subsidized lunch) is the single best predictor of quant score that I've found so far. This is depressingly unsurprising: poverty at home is hard to overcome: hard enough for individuals, and even harder in aggregate.
"With this in mind, then, I ran a quick linear regression of quant score as a strict function of lunch-subsidy percentage, and used that to calculate predicted quant scores for each district.
"The depressing headline is how small those variations are. In a quant-score range from 1531 to 727, only 10 districts did more than 100 quant points better than predicted, and only 10 districts did more than 100 points worse. If I use the square roots of the lunch-subsidy percentages, instead, only 6 districts beat their predictions by 100, and only 8 miss by 100.
"If I toss in town unemployment rates, Democratic vote percentages in the 2010 Senate election, and town per-capita income, I can get my predictions so close that only one school did more than 100 points better than expected, and only two did more than 100 points worse. This is daunting precision.
"But OK, even if the variations are small, they're there. So surely this is where those aspirational metrics like spending must come into play. Throwing money at students in school may not be able to counteract poverty at home, but doesn't it at least help?
"No.
"Students per Teacher? No.
"AP classes? No.
"Percentage of minority students? No."
Okay, that's all a little dense, but some things stand out --- just as you would expect intuitively. For instance, the fact that schools with the highest percentage of free lunch students were lowest in success. Should be obvious, right, Then the second most important factor for school success is parent income. Of course! Seems obvious, one goes with the other.
But perhaps even more striking is how little class size, per pupil spending, teacher experience etc. matters. I think a lot of school administrators and board members would benefit from reading the entire file (and maybe explaining it all to me).
What can be done about the free lunch category? Beyond me, expect somehow make all parents richer.
