Participate and share: Poster 
When done correctly, quality assessments create data that can be used to make sound educational decisions. For that to happen, educators must have a solid understanding of their assessments, including what they measure, what they don’t measure and what the results actually mean. It’s not enough for a classroom teacher to identify a cluster of students who didn’t perform well on an assessment. That teacher must also understand why the students are clustered there and what changes need to be made to improve their achievement. The session offers a step-by-step method for achieving this.
Assessment Data 101
Patterns of Need Intro*
Discovering Patterns of Need
Identifying Patterns of Need and Instructional Strategies
Root Cause Analysis Intro*
Potential Root Causes
Root Cause Analysis Protocols*
Some of the ideas in this presentation come from new research on the impact of data-driven decision-making on school improvement. Recent reports supporting this approach include:
David Ronka, Robb Geier and Malgorzata Marciniak, PCG Education, 2010
Kim Schildcamp, Educational Research, 2019
2020 Data Inquiry Guide, Washington Office of Superintendent of Public Instruction
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