The Evaluation of Teachers and Schools Using the Educator Response Function (ERF). Mark D. Reckase Michigan State University. Background. Current educational policy is built around goal of helping students reach educational goals specified by the states.
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The Evaluation of Teachers and Schools Using the Educator Response Function (ERF)
Mark D. Reckase
Michigan State University
CI distribution for students assigned to the teacher.
Note that most of them are below 100. This is not a very challenging group of students.
Proficiency levels of students as a function of CI.
Most of those with a low CI are proficient.
The two-parameter logistic model is fit to the data for the teacher.
EPL = 100
This means that the probability of this teacher helping a student with CI = 100 reach proficiency is .5.
Standard error is 3.9.
Most of these students have CI values above 100. This is a more challenging teaching assignment than the first teacher.
EPL estimate is 120 with a standard error of 6.1. The teacher has a higher EPL because students with high CI values were proficient.
Error is larger because division is not as distinct.
Y = 174.092 + 0.791*Read3 – 6.103*ED – 9.090*SWD – 3.830*ELL + e
Where Read3 is the state test in Reading for Grade 3;
EDis a 0/1 variable indicating Economic Disadvantage (free or reduced lunch):
SWDis a 0/1 variable indicating Students with Disabilities;
ELLis a 0/1 variable indicating English Language Learner;
and e is the error term in the regression model.
Mean = 96.6
SD = 17.8
Extreme values at left were mostly teachers with only one student, but one teacher had 14 students with none proficient.
At right is one teacher with 27 students, all of whom reached proficient.