Since 2010, at least 36 states have adopted laws requiring principals to undergo regular assessments and increasing the rigor of those reviews, according to the National Conference of State Legislatures. This change is in large part due to demands set on school systems by No Child Left Behind and the later waivers granted by the Obama Administration.
So while principal evaluations are a rarely questioned growing trend, not nearly as much research has been performed about them, meaning that there is a multiplicity of models for principal evaluation in operation across states and districts.
According to Ellen Goldring, a department chairperson at Peabody College of Education and Human Development at Vanderbilt University in Nashville, Tennessee., the widely varying models demand some serious reform. Dr. Goldring did her own review of principal-evaluation legislation passed between 2009 and 2013. She said there was limited information about how the policies are used; a lack of clarity on the consequences for principals and how feedback is to be presented; and a lack of alignment with principals’ evolving roles, in talent management, data analytics, and building-level autonomy.
Following are the most prevalent models currently in use:
- “50-50” Percentage Model: 50 percent of the evaluation score is derived from student-outcome measures, usually student achievement or academic growth. This can include indicators such as graduation and attendance rates. The other 50 percent of the score often comes from a performance rubric, aligned with standards developed by the Council of Chief State School Officers. Example: Georgia
- Matrix Model: In most cases, 50 percent of the evaluation is based on student outcome or growth measures; the other 50 percent of the score comes from a performance rubric. However, the overall score is derived from a matrix table, rather than a percentage formula. Example: Ohio
- Student ‘Data Trump’ Model: Student growth/performance may account for less than half of the principal’s overall score; however, a principal cannot earn the highest rating or be deemed “highly effective” with low student performance/outcome data. In other words, student data “trumps” everything else. Example: Delaware
Goldring, as well as others who have focused on principal evaluations in their research, speculate that one of the most effective ways to improve principal effectiveness is to focus more on a mentoring/collaboration model in which principals are graded more by peers and less by test scores.
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