Date of Conferral

2021

Degree

Doctor of Education (Ed.D.)

School

Education

Advisor

Paul Kasunich

Abstract

Student achievement levels on state standardized tests consistently declined at a high school in the Midwestern United States even after the district established the expectation that teachers use data-driven decision making to guide instruction. The school administration wanted to understand why teachers use data-driven decision making to guide instruction. The purpose of this qualitative study was to understand the reasons and motivations behind teachers’ use of data driven decision making (DDDM) to inform instruction in accordance with district expectations. This study was guided by self-determination theory which focuses on the intrinsic and extrinsic motivations of individuals and the internal and external factors that can affect these motivations. Three research questions guided this study. Semi-structured interviews were conducted with 11 participants, analyzed, and coded to identify themes concerning teachers’ motivation to use data-driven decision making and internal and external factors affecting teachers’ motivations. The results of this study revealed that teachers possessed a low sense of self-efficacy in using DDDM to guide instruction. The findings resulted in the development of a professional development program for the teachers to increase their efficacy in using DDDM to guide instruction. This professional development program may lead to a positive social change by increasing teachers’ motivation and efficacy using data-driven decision making, resulting in greater student achievement and increased graduation rates.

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