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Measuring and Modeling Growth in a High Stakes Environment. John Cronin, Ph.D. Director The Kingsbury Center @ NWEA. Measuring and Modeling Growth in a High Stakes Environment. Presenter - John Cronin, Ph.D. Contacting us: Rebecca Moore: 503-548-5129 E-mail: [email protected]
John Cronin, Ph.D.
The Kingsbury Center @ NWEA
Presenter - John Cronin, Ph.D.
Rebecca Moore: 503-548-5129
E-mail: [email protected]
This PowerPoint presentation and recommended resources are available at our website: www.kingsburycenter.org
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Is the progress produced by this teacher dramatically greater or less than teaching peers that deliver instruction to comparable students?
Our nation has moved from a model of education reform that focused on fixing schools to a model that is focused on fixing the teaching profession.
All students count when accountability is measured through growth.
One district’s change in 5th grade math performance relative to Kentucky cut scores
Number of 5th grade students meeting math growth target in the same district
Measurement design of the instrument
Many assessments are not designed to measure growth. Others do not measure growth equally well for all students.
Grade 6 New York Mathematics
“Among those who ranked in the top category on the TAKS reading test, more than 17% ranked among the lowest two categories on the Stanford. Similarly more than 15% of the lowest value-added teachers on the TAKS were in the highest two categories on the Stanford.”
Corcoran, S., Jennings, J., & Beveridge, A., Teacher Effectiveness on High and Low Stakes Tests, Paper presented at the Institute for Research on Poverty summer workshop, Madison, WI (2010).
Instability of results
A variety of factors can cause value-added results to lack stability.
Results are more likely to be stable at the extremes. The use of multiple-years of data is highly recommended.
Reliability of teacher value-added estimates
Typical r values for measures of teaching effectiveness range between .30 and .60 (Brown Center on Education Policy, 2010)
Control for statistical error
All models attempt to address this issue. Nevertheless, many teachers value-added scores will fall within the range of statistical error.
Tests should align to the teacher’s instructional responsibilities.
Assessments must align with the should be instructionally sensitive.
There are a variety of models in the marketplace. These models may come to different conclusions about the effectiveness of a teacher or school. Differences in findings are more likely to happen at the extremes.
Lack of random assignment
The use of a value-added model assumes that the school doesn’t add a source of variation that isn’t controlled for in the model.
e.g. Young teachers are assigned disproportionate numbers of students with poor discipline records.
Uncovered Subjects and Teachers
High quality tests may not be administered, or available, for many teachers and grades. Subjects like social studies may be particularly problematic.
In self-contained classrooms, one or two idiosyncratic cases can have a large effect on results.
Security and Cheating
When measuring growth, one teacher who cheats disadvantages the next teacher.
Proctoring both with and without the classroom teacher raises possible problems.
Documentation that test administration procedures were properly followed is important.
The use of testing data for high stakes personnel decisions does not yet have a strong, coherent, body of case law.
Expect litigation if value-added results are the lynchpin evidence for a teacher-dismissal case until a body of case law is established.