A Fuzzy Logic Approach to Teacher Performance Measured by Principal Evaluations

Date of Award

Summer 2015

Type

Dissertation

Major

Doctor of Education

Department

Counseling, Foundations & Leadership

Abstract

While principals and current methods used to evaluate teacher performance have been found to accurately identify the teachers with students who have the largest and smallest achievement gains in their schools, they are less able to distinguish among teachers in between these extremes. A majority of states have implemented new reform in teacher evaluation strategies in order to diagnose and improve teacher performance, but unfortunately, have not incorporated a method capable of accurately representing qualitative factors and the relationships between them. The main objective of this study was to examine to what degree a fuzzy logic expert system could elicit and quantify teacher performance using state teacher evaluation methods. Theoretical background is given as a foundation for fuzzy logic expert systems in order to understand their implications to teacher performance evaluation. The experimental results from a case study of one Georgia high school were compared with the traditional state evaluation method. The findings of the study indicate a fuzzy logic expert system may help identify teachers lying at the boundary of two different categories of performance and show potential for a fuzzy logic expert system to provide a more accurate continuum of teacher performance.

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