Subgroup-Specific Accountability, Teacher Job Assignments, And Teacher Attrition: Lessons For States

Our guest author today is Matthew Shirrell, assistant professor of educational leadership and administration in the Graduate School of Education and Human Development at the George Washington University.

Racial/ethnic gaps in student achievement persist, despite a wide variety of interventions designed to address them (see Reardon, Robinson-Cimpian, & Weathers, 2015). The No Child Left Behind Act of 2001 (NCLB) took a novel approach to closing these achievement gaps, requiring that schools make yearly improvements not only in overall student achievement, but also in the achievement of students of various subgroups, including racial/ethnic minority subgroups and students from economically disadvantaged families.

Evidence is mixed on whether NCLB’s “subgroup-specific accountability” accomplished its goal of narrowing racial/ethnic and other achievement gaps. Research on the impacts of the policy, however, has largely neglected the effects of this policy on teachers. Understanding any effects on teachers is important to gaining a more complete picture of the policy’s overall impact; if the policy increased student achievement but resulted in the turnover or attrition of large numbers of teachers, for example, these benefits and costs should be weighed together when assessing the policy’s overall effects.

In a study just published online in Education Finance and Policy (and supported by funding from the Albert Shanker Institute), I explore the effects of NCLB’s subgroup-specific accountability on teachers. Specifically, I examine whether teaching in a school that was held accountable for a particular subgroup’s performance in the first year of NCLB affected teachers’ job assignments, turnover, and attrition.

The Debate And Evidence On The Impact Of NCLB

There is currently a flurry of debate focused on the question of whether “NCLB worked.” This question, which surfaces regularly in the education field, is particularly salient in recent weeks, as Congress holds hearings on reauthorizing the law.

Any time there is a spell of “did NCLB work?” activity, one can hear and read numerous attempts to use simple NAEP changes in order to assess its impact. Individuals and organizations, including both supporters and detractors of the law, attempt to make their cases by presenting trends in scores, parsing subgroups estimates, and so on. These efforts, though typically well-intentioned, do not, of course, tell us much of anything about the law’s impact. One can use simple, unadjusted NAEP changes to prove or disprove any policy argument. And the reason is that they are not valid evidence of an intervention's effects. There’s more to policy analysis than subtraction.

But it’s not just the inappropriate use of evidence that makes these “did NCLB work?” debates frustrating and, often, unproductive. It is also the fact that NCLB really cannot be judged in simple, binary terms. It is a complex, national policy with considerable inter-state variation in design/implementation and various types of effects, intended and unintended. This is not a situation that lends itself to clear cut yes/no answers to the “did it work?” question.

The Arcane Rules That Drive Outcomes Under NCLB

** Reprinted here in the Washington Post

A big part of successful policy making is unyielding attention to detail (an argument that regular readers of this blog hear often). Choices about design and implementation that may seem unimportant can play a substantial role in determining how policies play out in practice.

A new paper, co-authored by Elizabeth Davidson, Randall Reback, Jonah Rockoff and Heather Schwartz, and presented at last month’s annual conference of The Association for Education Finance and Policy, illustrates this principle vividly, and on a grand scale: With an analysis of outcomes in all 50 states during the early years of NCLB.

After a terrific summary of the law's rules and implementation challenges, as well as some quick descriptive statistics, the paper's main analysis is a straightforward examination of why the proportion of schools meeting AYP varied quite a bit between states. For instance, in 2003, the first year of results, 32 percent of U.S. schools failed to make AYP, but the proportion ranged from one percent in Iowa to over 80 percent in Florida.

Surprisingly, the results suggest that the primary reasons for this variation seem to have had little to do with differences in student performance. Rather, the big factors are subtle differences in rather arcane rules that each state chose during the implementation process. These decisions received little attention, yet they had a dramatic impact on the outcomes of NCLB during this time period.

Annual Measurable Objections

As states’ continue to finalize their applications for ESEA/NCLB “flexibility” (or “waivers”), controversy has arisen in some places over how these plans set proficiency goals, both overall and for demographic subgroups (see our previous post about the situation in Virginia).

One of the underlying rationales for allowing states to establish new targets (called “annual measurable objectives," or AMOs) is that the “100 percent” proficiency goals of NCLB were unrealistic. Accordingly, some (but not all) of the new plans have set 2017-18 absolute proficiency goals that are considerably below 100 percent, and/or lower for some subgroups relative to others. This shift has generated pushback from advocates, most recently in Florida, who believe that lowering state targets is tantamount to encouraging or accepting failure.

I acknowledge the central role of goals in any accountability system, but I would like to humbly suggest that this controversy, over where and how states set proficiency targets for 2017-18, may be misguided. There are four reasons why I think this is the case (and one silver lining if it is).

NCLB And The Institutionalization Of Data Interpretation

It is a gross understatement to say that the No Child Left Behind (NCLB) law is, was – and will continue to be – a controversial piece of legislation. Although opinion tends toward the negative, there are certain features, such as a focus on student subgroup data, that many people support. And it’s difficult to make generalizations about whether the law’s impact on U.S. public education was “good” or “bad” by some absolute standard.

The one thing I would say about NCLB is that it has helped to institutionalize the improper interpretation of testing data.

Most of the attention to the methodological shortcomings of the law focuses on “adequate yearly progress” (AYP) – the crude requirement that all schools must make “adequate progress” toward the goal of 100 percent proficiency by 2014. And AYP is indeed an inept measure. But the problems are actually much deeper than AYP.

Rather, it’s the underlying methods and assumptions of NCLB (including AYP) that have had a persistent, negative impact on the way we interpret testing data.

Assessing Ourselves To Death

** Reprinted here in the Washington Post

I have two points to make. The first is something that I think everyone knows: Educational outcomes, such as graduation and test scores, are signals of or proxies for the traits that lead to success in life, not the cause of that success.

For example, it is well-documented that high school graduates earn more, on average, than non-graduates. Thus, one often hears arguments that increasing graduation rates will drastically improve students’ future prospects, and the performance of the economy overall. Well, not exactly.

The piece of paper, of course, only goes so far. Rather, the benefits of graduation arise because graduates are more likely to possess the skills – including the critical non-cognitive sort – that make people good employees (and, on a highly related note, because employers know that, and use credentials to screen applicants).

We could very easily increase the graduation rate by easing requirements, but this wouldn’t do much to help kids advance in the labor market. They might get a few more calls for interviews, but over the long haul, they’d still be at a tremendous disadvantage if they lacked the required skills and work habits.