Document Type

Dissertation

Degree

Doctor of Philosophy

Major

Education, Educational Leadership & Policy Studies

Date of Defense

10-19-2018

Graduate Advisor

Matthew Davis

Committee

Keith Miller

Thomasina Hassler

Phyllis Balcerzak

Matthew Davis

Abstract

This study investigated the teacher evaluation model used by Concept-managed charter schools. The STEM-focused, college preparatory Concept Schools is a management company that manages 31 charter schools in seven different states in the U.S. The Concept Schools (CS) teacher evaluation model was based on the Danielson Framework and has been used in all CS-managed schools since 2011. This dissertation used data from three years of consecutive teacher evaluations scores to create a predicting model for K-12 school districts. The model analyzed an individual teacher’s performance growth and predicts future performance. The study used both qualitative and quantitative methods. The researcher interviewed seven teachers and six principals. For analysis of interview data, the thematic analysis method was used. The quantitative part of research was used to collect teachers’ evaluation scores and students’ standardized math and reading scores. The Structural Equation Modeling (SEM) and Analysis of Moment Structures (AMOS) used for statistical calculation included estimation of fit indices, errors, and model parameters. The study findings indicated that there was no overall significant relation between teacher evaluation scores and student standardized test scores. However, between year-two and year-three teachers there was a relation between evaluation scores and student standardized test scores. This study also highlights the importance of open dialogue between teacher and principal, meaningful feedback, non-core subjects training, and clears rubrics to support trust building between teachers and principals. Finally, findings indicated targeted or need-based professional development plans for teachers that could have more potential in an area of improvement.

OCLC Number

1100473242

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