Value-Added Versus Observations

Value-Added Versus Observations, Part One: Reliability

Although most new teacher evaluations are still in various phases of pre-implementation, it’s safe to say that classroom observations and/or value-added (VA) scores will be the most heavily-weighted components toward teachers’ final scores, depending on whether teachers are in tested grades and subjects. One gets the general sense that many – perhaps most – teachers strongly prefer the former (observations, especially peer observations) over the latter (VA).

One of the most common arguments against VA is that the scores are error-prone and unstable over time – i.e., that they are unreliable. And it’s true that the scores fluctuate between years (also see here), with much of this instability due to measurement error, rather than “real” performance changes. On a related note, different model specifications and different tests can yield very different results for the same teacher/class.

These findings are very important, and often too casually dismissed by VA supporters, but the issue of reliability is, to varying degrees, endemic to all performance measurement. Actually, many of the standard reliability-based criticisms of value-added could also be leveled against observations. Since we cannot observe “true” teacher performance, it’s tough to say which is “better” or “worse,” despite the certainty with which both “sides” often present their respective cases. And, the fact that both entail some level of measurement error doesn’t by itself speak to whether they should be part of evaluations.*

Nevertheless, many states and districts have already made the choice to use both measures, and in these places, the existence of imprecision is less important than how to deal with it. Viewed from this perspective, VA and observations are in many respects more alike than different.

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Value-Added Versus Observations, Part Two: Validity

In a previous post, I compared value-added (VA) and classroom observations in terms of reliability – the degree to which they are free of error and stable over repeated measurements. But even the most reliable measures aren’t useful unless they are valid – that is, unless they’re measuring what we want them to measure.

Arguments over the validity of teacher performance measures, especially value-added, dominate our discourse on evaluations. There are, in my view, three interrelated issues to keep in mind when discussing the validity of VA and observations. The first is definitional – in a research context, validity is less about a measure itself than the inferences one draws from it. The second point might follow from the first: The validity of VA and observations should be assessed in the context of how they’re being used.

Third and finally, given the difficulties in determining whether either measure is valid in and of itself, as well as the fact that so many states and districts are already moving ahead with new systems, the best approach at this point may be to judge validity in terms of whether the evaluations are improving outcomes. And, unfortunately, there is little indication that this is happening in most places.

Let’s start by quickly defining what is usually meant by validity. Put simply, whereas reliability is about the precision of the answers, validity addresses whether we’re using them to answer the correct questions. For example, a person’s weight is a reliable measure, but this doesn’t necessarily mean it’s valid for gauging the risk of heart disease. Similarly, in the context of VA and observations, the question is: Are these indicators, even if they can be precisely estimated (i.e., they are reliable), measuring teacher performance in a manner that is meaningful for student learning?

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