Part 3—First approximations: Very large “achievement gaps” exist in American schools.
In yesterday’s main report, we looked at the range of scores in Grade 8 math on last year’s NAEP math test. We refer to the National Assessment of Educational Progress, the 43-year-old federal program which is widely regarded as out most reliable testing program.
Students took the NAEP last year. Based on conventional rules of thumb, a very wide range of math achievement is suggested by these scores:
Average scores, Grade 8 math, 2013 NAEPJust for the record, ten percent of tested students scored below that lowest score. Ten percent of tested students scored above 331.
90th percentile: 331
75th percentile: 310
50th percentile: 286
25th percentile: 261
10th percentile: 237
When conventional rules of thumb are applied, those scores suggest a very wide range of achievement levels among the nation’s eighth graders. As we all know, these gaps don’t appear completely at random among our students.
To a significant degree, these gaps in achievement correlate with family income and race. In recent weeks, major journalists seemed eager to underplay, avoid or deny that highly salient fact.
In a 10,000-word piece in The Atlantic, Nikole Hannah-Jones found a hundred ways to underplay the savagery of the achievement gap which faces low-income black kids. Meanwhile, in the New York Times and the Washington Post, Eduardo Porter and Professor Perry seemed to imagine a more pleasing world, a world in which black kids are “disproportionately” represented in public school gifted programs because they have been “channeled” or “funneled into a lower-quality education.”
Hannah-Jones made the same pleasing suggestion in her fascinating report about Tuscaloosa’s schools. For reasons we’ll detail in coming weeks, we think such journalism is a bit on the heinous side, though your results may differ.
Your results may differ! If so, we’ll suggest your results could be wrong.
For today, let’s start to define the size of the gaps by family income and also by race. How large are the achievement gaps based on income and race?
Again, we’ll use data from last year’s National Assessment of Educational Progress, the widely-praised federal testing program. Let’s start with family income.
In its public data, the NAEP employs a fairly crude measure of family income. It divides students into two large groups—those who qualify for free or reduced-price lunch, and those who don’t qualify.
This is not a measure of poverty, though journalists often present it as such. As a rough measure, a student qualifies for reduced price lunch if his family’s income is roughly twice the federal poverty level.
At present, this measure divides the nation’s student population roughly in half. According to NAEP data, exactly 50 percent of eighth-graders tested in math last year qualified for free or reduced price lunch. Fifty percent did not.
We’ll refer to these two groups as “lower-income” and “upper-income students.” Below, you see the average scores in Grade 8 math recorded by these two groups:
Average scores, Grade 8 mathA gap of 27.17 points separated the average scores of those two groups of kids. By a very rough rule of thumb which is often applied to NAEP scores, that represents an achievement gap approaching three academic years.
Public school students, 2013 NAEP
All students: 283.62
Higher-income students: 297.13
Lower-income students: 269.96
That is a very rough rule of thumb, as we constantly note. We’d love to see the nation’s “education reporters” interview NAEP officials and other experts, if any exist, to estimate the range of achievement suggested by those average scores.
That said, a second point is very much worth noting—those are the average scores for students in each income group. Roughly half the upper-income students scored somewhere above 297. Roughly half the lower-income group scored somewhere below 270.
Considered that way, those average scores suggest a fairly large “achievement gap” based on family income. We’ll discuss some of the ways such gaps arise in the weeks ahead.
That said, the gaps between our major “racial” and ethnic groups were somewhat larger than that. Using the language of the NAEP, these are the average scores recorded by the four major groups:
Average scores, Grade 8 mathThe gap between white kids and black kids was slightly larger than the gap between higher-income and lower-income students. Meanwhile, our Asian-American kids made everyone look bad.
Public school students, 2013 NAEP
All students: 283.62
Asian/Pacific Islander students: 305.92
White students: 293.19
Hispanic students: 271.02
Black students: 262.73
Tomorrow, we’ll break these scores down further. We’ll look at the average scores of lower- and higher-income kids within each of the four “racial”/ethnic groups.
Before the week is done, we’ll also take a quick look at Alabama’s statewide scores. Here’s why:
Hannah-Jones’ lengthy Atlantic piece dealt with Tuscaloosa’s public schools. In the main, she discussed Tuscaloosa’s high schools, past and present, dating back to the 1960s.
In its so-called Trial Urban District study, the NAEP produces scores for twenty-one cities around the nation; Tuscaloosa isn’t part of this program. But when we look at the size of the gaps for Alabama as a whole, we may start to gain a new perspective on some of Hannah-Jones’ suggestions and representations, past as well as present.
What’s happening in Tuscaloosa’s schools? The question is very important.
Those schools are full of deserving kids. They want to live good lives; they want to serve and achieve.
In many ways, we thought Hannah-Jones’ representations were pleasing for the adult crowd but perhaps a bit less than respectful of those children’s interests. Your results may differ, of course. But are you real sure that they should?
Tomorrow: The size of the gaps, presented in more detail
To access all NAEP data: To access the NAEP data cited above, click here, then click on MAIN NDE (Main NAEP Data Explorer).
Click again to agree to terms; from there, you’re on your own. You’d never know it from reading newspapers, but mountains of data exist.