Diane Ravitch has taken a strong stance against this kind of bastardized accountability and now so has Linda Darling-Hammond in her article Value-Added Hurts Teaching, she writes:
I was once bullish on the idea of using “value-added methods” for assessing teacher effectiveness. I have since realized that these measures, while valuable for large-scale studies, are seriously flawed for evaluating individual teachers, and that rigorous, ongoing assessment by teaching experts serves everyone better. Indeed, reviews by the National Research Council, the RAND Corp., and the Educational Testing Service have all concluded that value-added estimates of teacher effectiveness should not be used to make high-stakes decisions about teachers.
First, test-score gains—even using very fancy value-added models—reflect much more than an individual teacher’s effort, including students’ health, home life, and school attendance, and schools’ class sizes, curriculum materials, and administrative supports, as well as the influence of other teachers, tutors, and specialists. These factors differ widely in rich and poor schools.
Second, teachers’ ratings are highly unstable: They differ substantially across classes, tests, and years. Teachers who rank at the bottom one year are more likely to rank above average the following year than to rate poorly again. The same holds true for teachers at the top. If the scores truly measured a teacher’s ability, these wild swings would not occur.
Third, teachers who rate highest on the low-level multiple-choice tests currently in use are often not those who raise scores on assessments of more-challenging learning. Pressure to teach to these fill-in-the-bubble tests will further reduce the focus on research, writing, and complex problem-solving, areas where students will need to compete with their peers in high-achieving countries.
But, most importantly, these test scores largely reflect whom a teacher teaches, not how well they teach. In particular, teachers show lower gains when they have large numbers of new English-learners and students with disabilities than when they teach other students. This is true even when statistical methods are used to “control” for student characteristics.