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Data-Driven Decision Making about Single-Sex Instructional Grouping at an Elementary School

Administrators at a Southeastern elementary school eliminated single-sex instructional grouping in 5th-grade classes without a proper analysis of all available data and later reflected upon whether this instructional model should be revived. Because data-based decisions may positively improve teaching and learning for all stakeholders, the purpose of this qualitative case study was to explore all available data leading to this decision, inform stakeholders about the decision-making processes in the local school, and provide data to inform future decisions. Conceptually framed with Mandinach's data-driven decision making (DDDM) model, the guiding question for the study focused on perceptions of teacher, administrator, and leadership team member about the DDDM process related to single-sex instructional grouping in the local venue. The data were collected using 8 interviews with administrators, teachers, and school leadership team members involved in the instructional decision. Data from interview were transcribed, analyzed, and coded for emergent themes, types of data and decisions, decision making processes, and stakeholder perceptions. The findings showed a gap in DDDM practice and affirmed the value of data for informed decision making. The findings guided recommendations for a professional development series created to increase data literacy and DDDM best practices. Improving DDDM for teaching and learning may promote positive social change by developing educational stakeholder skill sets for all decision-making as well as providing targeted, data-driven instruction for learners whether in multi- or single-sex instructional grouping.

Identiferoai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-7765
Date01 January 2019
CreatorsSorrells, Michelle Lynnette
PublisherScholarWorks
Source SetsWalden University
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceWalden Dissertations and Doctoral Studies

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