The Impact Collaborative Data Analysis has on Student Achievement and Teacher Practice in High School Mathematics Classrooms in Suburban School Districts in the Mid-West Region of New York

摘要

This research study is an examination of ongoing collaborative data analysis among educators and the potential impact it has on instructional improvement as well as student achievement. Collaborative data-driven decision making has been identified in theory and research as a promising model for continuous school improvement yet districts, schools and teachers are hesitant to change traditional practices (DuFour, Eaker u26 DuFour, 2005; Gruenert, 2005; Steele u26 Boudett, 2008). The purpose of this study was to reveal how integrating formative and summative assessments, collecting and analyzing data, and collaborating as teams expands teacher understanding of data driven decision making and leads to improved teaching practices. A mixed methods research design was chosen for this study to better understand the research problem by triangulating numeric trends from quantitative data and the detail of qualitative data. A quasi-experimental approach was used to measure the relationship between collaborative data analysis and student achievement, as well as the progress a school is making with the implementation of data-driven instruction and assessment. At the same time, interviews were conducted to explore teacher’s views on the implementation and effectiveness of collaborative data analysis with respect to their instructional practices and student learning. The findings suggest that when teachers are provided structured time within the school day, meaningful collaborative data analysis that leads to instructional adjustments and targeted student interventions can occur. The need for additional research studies vii that investigate grade level or content area collaborative inquiry teams impact on student performance based on both formative and summative assessments was identified.