A simple classroom average gain could then be a statistically
biased measure of teacher effectiveness, meaning it would systematically under - or over-estimate a teacher's ability depending on the characteristics of the students assigned to her.
Not exact matches
But if the scores are flawed,
biased, or incomplete
measures of learning or
teacher effectiveness, the models won't pick that up.
More specifically, the district and its
teachers are not coming to an agreement about how they should be evaluated, rightfully because
teachers understand better than most (even some VAM researchers) that these models are grossly imperfect, largely
biased by the types
of students non-randomly assigned to their classrooms and schools, highly unstable (i.e., grossly fluctuating from one year to the next when they should remain more or less consistent over time, if reliable), invalid (i.e., they do not have face validity in that they often contradict other valid
measures of teacher effectiveness), and the like.
Kane's research was,
of course, used to support the claim that bad
teachers are causing the disparities that he cited, regardless
of the fact the inverse could be also, equally, or even more true — that the value - added
measures used to
measure teacher effectiveness in these schools are
biased by the very nature
of the students in these schools that are contributing their low test scores to such estimates.