Date of Award

4-2016

Degree Name

Doctor of Philosophy

Department

Educational Leadership, Research and Technology

First Advisor

Dr. Louann Bierlein Palmer

Second Advisor

Dr. Jessaca Spybrook

Third Advisor

Dr. Thomas Reeder

Keywords

Professional Learning Communities (PLC), student achievement, Hierarchical Linear Modeling (HLM), PLC Survey, Middle School, student achievement, variables

Abstract

For nearly two decades, schools throughout the United States and beyond have utilized the Professional Learning Community (PLC) model to foster teacher collaboration in hopes of improving student achievement outcomes. At the turn of the century, much of the research suggested a positive relationship between student achievement outcomes and the implementation of PLC’s in the school setting. The more recent research suggests little to no relationship between PLC’s and student achievement outcomes.

In an effort to bring clarity to the conflicting research, data was collected from a sample of 12 schools which included 275 teachers and nearly 6,000 students. Teacher survey data was collected using Olivier, Hipp, and Huffman’s (2010) Professional Learning Community Assessment – Revised (PLCA-R) survey instrument, which deconstructs PLC’s into six elements. Student state assessment data in mathematics and reading in grades seven and eight was also collected. Analysis of variance (ANOVA) revealed statically significant differences between the 12 buildings in both PLCA-R and state assessment data; therefore, hierarchical linear modeling (HLM) was used to determine whether any of these differences could be attributed to any of the six PLCA-R elements. After controlling for the effects of student and school-level covariates, HLM analyses revealed that none of the variance in student achievement data could be attributed any of the six PLCA-R elements. The analyses also indicated low socioeconomic status had a profound impact in explaining student achievement variance.

Future studies should consider a multi-region or multi-state sample to capture more variation between buildings. Moreover, future researchers would be wise to consider a six to ten point Likert scale to capture what may potentially be a larger degree of PLC implementation variance.

Access Setting

Dissertation-Open Access

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