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Teacher Evaluation

  • Are Value-Added Models Objective?

    Written on September 8, 2010

    In recent discussions about teacher evaluation, some people try to distinguish between "subjective" measures (such as principal and peer observations) and "objective" measures (usually referring to value-added estimates of teachers’ effects on student test scores).

    In practical usage, objectivity refers to the relative absence of bias from human judgment ("pure" objectivity being unattainable). Value-added models are called "objective" because they use standardized testing data and a single tool for analyzing them: All students in a given grade/subject take the same test and all teachers’ "effects" in a given district or state are estimated by the same model. Put differently, all teachers are treated the same (at least those 25 percent or so who teach grades and subjects that are tested), and human judgment is relatively absent.

    By this standard, are value-added models objective? No. And it is somewhat misleading to suggest that they are.

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  • Value-Added And Collateral Damage

    Written on July 29, 2010

    The idea that we should "fire bad teachers" has become the mantra of the day, as though anyone was seriously arguing that bad teachers should be kept. No one is. Instead, the real issue is, and has always been, identification.

    Those of us who follow the literature about value-added models (VAM) - the statistical models designed to isolate the unique effect of teachers on their students' test scores - hear a lot about their imprecision. But anyone listening to the public discourse on these methods, or, more frighteningly, making decisions on how to use them, might be completely unaware of the magnitude of that error.

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