In a recent article released in The Journal News, a newspaper serving many suburban New York counties, another common problem is highlighted whereby districts that have adopted the same teacher observational system (in this case as mandated by the state) are scoring what are likely to be very similar teachers very differently. Whereby teachers in one of the best school districts not only in the state but in the nation apparently has no “highly effective” teachers on staff, teachers in a neighboring district apparently have a staff 99% filled with “highly effective” teachers.
The “believed to be” model developer, Charlotte Danielson, is cited as stating that “Saying 99 percent of your teachers are highly effective is laughable.” I don’t know if I completely agree with her statement, and I do have to admit I question her perspective on this one, and all of her comments throughout this article for that matter, as she is the one who is purportedly offering up her “valid” Framework for Teaching for such observational purposes. Perhaps she’s displacing blame and arguing that it’s the subjectivity of the scorers rather than the subjectivity inherent in her system that should be to blame for the stark discrepancies.
As per Danielson: “The local administrators know who they are evaluating and are often influenced by personal bias…What it also means is that they might have set the standards too low.” As per the Superintendent of the District with 99% highly effective teachers: The state’s “flawed” evaluation model forced districts to “bump up” the scores so “effective” teachers wouldn’t end up with a rating of “developing.” The Superintendent adds that it is possible under the state’s system to be rated “effective” across domains and still end up rated as “developing,” which means teachers may be in need of intervention/improvement, or may be eligible for an expedited hearing process that could lead to their termination. Rather it may have been the case that the scores were inflated to save effective teachers from what the district viewed as an ineffective set of consequences attached to the observational system (i.e., intervention or termination).
Danielson is also cited as saying that “teachers should live in “effective” and only [occasionally] visit “highly effective.” She also notes that if her system contradicts teachers’ value-added scores, this too should “raise red flags” about the quality of the teacher, although she does not (in this article) pay any respect or regard for the issues not only inherent in value-added measures but also her observational system.
What is most important in this article, though, is that reading through it illustrates well the arbitrariness of how all of the measures being mandated and used to evaluate teachers are actually being used. Take, for example, the other note herein that the state department’s intent seems to be that 70%-80% percent of teachers should “fall in the middle” as “developing” or “effective.” While this is mathematically impossible (i.e., to have 70%-80% hang around average), this could not be more arbitrary.
In the end, teacher evaluation systems are highly flawed and highly subjective and highly prone to error and the like, and for people who just don’t “get it” to be passing policies on the contrary, is nonsensical and absurd. These flaws are not as important when evaluation system data can be used for formative, or informative purposes whereas data consumers have more freedom to take the data for what they are worth. When summary, or summative decisions are to be made as based on these data, regardless of whether low or high-stakes are attached to the decision, this is where things really go awry.