Date of Conferral

2-15-2024

Date of Award

February 2024

Degree

Doctor of Education (Ed.D.)

School

Education

Advisor

Anissa Harris

Abstract

The problem in this study was that first- and second-grade teachers are not using relevant and timely data, specifically running records, analysis of oral reading errors, self-correction rates, and word accuracy, as well as the student zone of proximal development (ZPD) in guided reading instruction. The purpose of this qualitative case study was to explore how first- and second-grade teachers use data-driven decision-making (DDDM) and ZPD to inform guided reading instruction. The conceptual frameworks in this study were DDDM and ZPD, as they collectively provided a lens for gathering rich data on instructional decision-making processes. Research questions addressed how first- and second-grade teachers used ZPD and DDDM, respectively, to plan/implement and determine next steps in guided reading lessons. Semistructured interview and lesson plan data were collected from 12 teachers who met the criteria and volunteered. Data were analyzed with an inductive approach, using a priori, open, and axial coding. Thematic findings indicating that participants individualized planning for guided reading based on students’ ZPD by implementing specific teaching strategies that targeted their individualized needs. Additionally, teachers used DDDM to determine next steps in guided reading by using continuous data analysis to individualized instruction. Thus, the findings may support positive social change by informing administrators of specific teacher experiences in using DDDM to inform guided reading instruction and the benefits of providing growth opportunities and professional development for early childhood and elementary teachers to expand their collective and individual DDDM for guided reading instruction.

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