Data-driven decision making for differentiated instruction

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2020-05

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Abstract

This insider action research study examined how educator confidence and capacity can increase to provide data-driven, targeted, campus-based, research-based best practices for student intervention. Targeted, individual student intervention is becoming more prominent and required by today’s classroom. Educators must understand what is needed to accomplish effective intervention and how to do it. The third grade through fifth grade elementary campus that was involved in this study has historically struggled to meet state accountability in the area of reading. By providing targeted professional development for the staff on this campus, the staff involved will have the opportunity to provide differentiated lessons to meet the needs of all students to increase reading achievement on the campus. This study incorporated multiple design-based school improvement intervention design principles and strategies by Mintrop (2016) and utilize insider action research methodology design as describes by Coghlan and Brannick (2014).

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Keywords

Data driven, Differentiation, Professional learning communities (PLC), Collaboration, Leadership, Teacher development, Lesson planning, Lesson presentation, Lesson rubric, Lesson cycle, Data analysis, Data literacy, Intervention, Shared vision, Collaborative teams, Teacher competency, Instructional leadership, Instructional leader, Instructional leadership teaming capacity, Teacher confidence, Professional development

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