BLOG AUTHOR
Bruce D. Baker
Bruce
D. Baker is a Professor in the Graduate School of Education at Rutgers,
The State University of New Jersey, where he teaches courses in school
finance policy and district business management. His recent research
focuses on state aid allocation policies and practices, with
particular...
Pondering Legal Implications of Value-Added Teacher Evaluation
LINK
Posted on June 2, 2010
7 Votes
I’m
going out on a limb here. I’m a finance guy. Not a lawyer. But, I do
have a reasonable background on school law thanks to colleagues in the
field like Mickey Imber at U. of Kansas and my frequent coauthor Preston
Green at Penn State. That said, any screw ups in my legal analysis
below are my own and not attributable to either Preston or Mickey. In
any case, I’ve been wondering about the validity of the claim that some
pundits seem to be making that these new teacher evaluation policies are
going to make it easier and less expensive to dismiss teachers.
=====
A
handful of states have now adopted legislation which mandates that
teacher evaluation be linked to student test data. Specifically,
legislation adopted in states like Colorado, Louisiana and Kentucky and
legislation vetoed in Florida follow a template of requiring that
teacher evaluation for pay increase, for retaining tenure and ultimately
for dismissal must be based 50% or 51% on student “value-added” or
“growth” test scores alone. That is, student test score data could make
or break a salary increase decision, but could also make or break a
teacher’s ability to retain tenure. Pundits backing these policies often
highlight provisions for multi-year data tracking on teachers so that a
teacher would not lose tenure status until he/she shows poor student
growth for 2 or 3 years running. These provisions are supposed to
eliminate the possibility that random error or a “bad crop of students”
alone could determine a teacher’s future.
Pundits
are taking the position that these new evaluation criteria will make it
easier to dismiss teachers and will reduce the costs of dismissing a
teacher that result from litigation. Oh, how foolish!
The
way I see it, this new crop of state statutes and regulations which
include arbitrary use of questionable data, applied in a questionably
appropriate way will most likely lead to a flood of litigation like none
that has ever been witnessed.
Why
would that be? How can a teacher possibly sue the school district for
being fired because he/she was a bad teacher? Simply writing into state
statute or department regulations that one’s “property interest” to
tenure and continued employment must be primarily tied to student test
scores does not by any stretch of the legal imagination guarantee that
dismissal based on student test scores will stand up to legal challenges
– good and legitimate legal challenges.
There
are (at least) two very likely legal challenges that will occur once we
start to experience our first rounds of teacher dismissal based on
student assessment data.
Due Process Challenges
Removing
a teacher’s tenure status is denial of a teacher’s property interest
and doing so requires “due process.” That’s not an insurmountable
barrier, even under typical teacher contracts that don’t require
dismissal based on student test scores. Simply declaring that “a teacher
will be fired if he/she shows 2 straight years of bad student test
scores (growth or value-added)” and then firing a teacher for as much
does not mean that the teacher necessarily was provided due process.
Under a policy requiring that 51% of the employment decision be based on
student value added test scores, a teacher could be wrongly terminated
due to:
a) Temporal instability of the value-added measures
Ooooh…Temporal
instability… what’s that supposed to mean? What it means is that
teacher value-added ratings, which are averages of individual student
gains, tend not to be that stable over time. The same teacher is highly
likely to get a totally different value added rating from one year to
the next. The above link points to a policy brief which explains that
the year to year correlation for a teacher’s value added rating is only
about .2 or .3. Further, most of the change or difference in the
teacher’s value added rating from one year to the next is unexplainable –
not by differences in observed student characteristics, peer
characteristics or school characteristics. 87.5% (elementary math) to
70% (8th grade
math) noise! While some statistical corrections and multi-year measures
might help, it’s hard to guarantee or even be reasonably sure that a
teacher wouldn’t be dismissed simply as a function of unexplainable low
performance for 2 or 3 years in a row. That is, simply due to noise, and
not the more troublesome issue of how students are clustered across
schools, districts and classrooms.
b) Non-random assignment of students
The
only fair way to compare teachers’ ability to produce student
value-added is to randomly assign all students, statewide to all
teachers… and then of course, to have all students live in exactly
comparable settings with exactly comparable support structures outside
of school, etc., etc. etc. That’s right. We’d have to send all of our
teachers and all of our students to a single boarding school location
somewhere in the state and make sure, absolutely sure that we randomly
assigned students, the same number of students to each and every teacher
in the system.
Obviously,
that’s not going to happen. Students are not randomly sorted and the
fact that they are not has serious consequences for comparing teachers’
ability to produce student value-added. See:http://gsppi.berkeley.edu/faculty/jrothstein/published/rothstein_vam2.pdf
c) Student manipulation of test results
As
she travels the nation on her book tour, Diane Ravitch raises another
possibility for how a teacher might find him/herself out of a job by no
real fault of actual bad teaching. As she puts it, this approach to
teacher evaluation puts the teacher’s job directly in the students’
hands. And the students can, if they wish, choose to consciously abuse
that responsibility. That is, the students could actually choose to
bomb the state assessments to get a teacher fired, whether it’s a good
teacher or a bad one. This would most certainly raise due process
concerns.
d) A whole bunch of other uncontrollable stuff
A recent National Academies report noted:
“A
student’s scores may be affected by many factors other than a teacher —
his or her motivation, for example, or the amount of parental support —
and value-added techniques have not yet found a good way to account for
these other elements.”
This
report generally urged caution regarding overemphasis of student
value-added test scores in teacher evaluation – especially in high
stakes decisions. Surely, if I was an expert witness testifying on
behalf of a teacher who had been wrongly dismissed, I’d be pointing out
that the National Academies said that using the student assessment data
in this way is not a good idea.
Title VII of the Civil Rights Act Challenges
The
non-random assignment of students leads to the second likely legal
claim that will flood the courts as student testing based teacher
dismissals begin – Claims of racially disparate teacher dismissal under
Title VII of the Civil Rights Act of 1964. Given that students are not
randomly assigned and that poor and minority – specifically black –
students are densely clustered in certain schools and districts and that
black teachers are much more likely to be working in schools with
classrooms of low-income black students, it is highly likely that
teacher dismissals will occur in a racially disparate pattern. Black
teachers of low-income black students will be several times more likely
to be dismissed on the basis of poor value-added test scores. This is
especially true where a statewide fixed, rigid requirement is adopted
and where a teacher must be de-tenured and/or dismissed if he/she shows
value-added below some fixed value-added threshold on state assessments.
So,
here’s how this one plays out. For every 1 white teacher dismissed on
value-added basis, 10 or more black teachers are dismissed - relative
to the overall proportions of black and white teachers. This gives the
black teachers the argument that the policy has racially disparate
effect. No, it doesn’t end there. A policy doesn’t violate Title VII
merely because it has racially disparate effect. That just starts the
ball rolling – gets the argument into court.
The
state gets to defend itself – by claiming that producing value-added
test scores is a legitimate part of a teacher’s job and then explaining
how the use of those scores is, in fact neutral with respect to race. It
just happens to have the disparate effect. Right? But, as the state
would argue, that’s a good thing because it ensures that we can put
better teachers in front of these poor minority kids, and get rid of the
bad ones.
But,
the problem is that the significant body of research on non-random
assignment of students and its effect of value added scores indicates
that it’s not necessarily differences in the actual effectiveness of
black versus white teachers, but that the black teachers are
concentrated in the poor black schools and that student clustering and
not teacher effectiveness is leading to the disparate rates of teacher
dismissal. So they weren’t fired because they were precisely measurably
ineffective, they were fired because they had classrooms of poor
minority students year after year? At the very least, it is
statistically problematic to distill one effect from the other! As a
result, it’s statistically problematic to argue that the teacher should
be dismissed! There is at least equal likelihood that the teacher is
wrongly dismissed as there is that the teacher is rightly dismissed. I
suspect a court might be concerned by this.
Reduction in Force
Note
that many of these same concerns apply to all of the recent rhetoric
over teacher layoffs and the need to base those layoffs on effectiveness
rather than seniority. It all sounds good, until you actually try to go
into a school district of any size and identify the 100 “least
effective” teachers given the current state of data for teacher
evaluation. Simply writing into a reduction in force (RIF) policy a
requirement of dismissal based on “effectiveness” does not instantly
validate the “effectiveness” measures. And even the best “effectiveness”
measures, as discussed above, remain really problematic, providing
tenured teachers reduced on grounds of ineffectiveness multiple options
for legal action.
Additional Concerns
These
two legal arguments ignore the fact that school districts and states
will have to establish two separate types of contracts for teachers to
begin with, since even in the best of statistical cases, only about 1/5
of teachers (those directly responsible for teaching math or reading in
grades three through eight) might possibly be evaluated via student test
scores (see:http://schoolfinance101.wordpress.com/2009/12/04/pondering-the-usefulness-of-value-added-assessment-of-teachers/)
I’ve
written previously about the technical concerns over value-added
assessment of teachers and my concern that pundits are seemingly
completely ignorant of the statistical issues. I’m also baffled that few
others in the current policy discussion seem even remotely aware of
just how few teachers might – in the best possible case – be evaluated
via student test scores, and the need for separate contracts. But, I am
perhaps most perplexed that no-one seems to be acknowledging the massive
legal mess likely to ensue when (or if) these poorly conceived policies
are put into action.
I’ll
save for another day the discussion of just who will be waiting in line
to fill those teaching vacancies created by rigid use of test scores
for disproportionately dismissing teachers in poor urban schools. Will
they, on average, be better or perhaps worse than those displaced before
them? Just who will wait in this line to be unfairly judged?
For a related article on the use of certification exams for credentialing teachers, see:
Green,
P.C., Sireci, S.G. (2005) Legal and Psychometric Criteria for
Evaluating Teacher Certification Tests. Educational Measurement: Issues
and Practice. Volume 19 Issue 1, Pages 22 – 31
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