Title
Using Data-Driven Decision-Making to Drive Instructional Decisions with High School Mathematics Teachers
Date of Award
Winter 12-15-2018
Document Type
Restricted Dissertation
Degree Name
Doctorate of Education, Ed.D.
College
College of Education
Department
Education
First Advisor
Belle Booker-Zorigian, Ph.D.
Second Advisor
Michael Hixon, Ed.D.
Third Advisor
LaToya Thomas-Dixon, Ed.D.
Abstract
A qualitative, single case study design was utilized to investigate high school mathematics teachers’ confidence in analyzing and interpreting student achievement data to drive instructional decisions in the classroom. The school district studied by the researcher had provided teachers with prior training in the data-driven decision-making process and was located in a Northeastern portion of the United States. Given the presumed previous training and experience in mathematics courses needed to analyze and interpret student achievement data, it was essential to explore whether this specific subsection of high school mathematics teachers was confident in the application of mathematical knowledge as it relates to the analysis of student achievement data. Sources of data for this research study were collected through a paper survey, two focus group meetings, and individual participant interviews to facilitate the triangulation of data. It was uncovered that high school mathematics teachers were confident in the mathematical skills needed to analyze and interpret student achievement data. Participants’ responses from the paper survey, two focus group meetings, and individual participant interviews identified the need for the allocation of time dedicated to analyzing student achievement data, additional training on the process of analyzing and interpreting student achievement data, and accessibility to the resources to obtain relevant student achievement data affected participants’ confidence in effectively using data to drive instructional decisions in the classroom. Data culture clearly defined by district administration was identified in this study as necessary to the success of the high school mathematics teachers in the data-driven decision-making process.