Read the following root cause analysis summary paragraphs. Then answer the questions below.
Based on our root cause analysis, we understand that educators have varied assessment practices and standards that result in discrepancies in student achievement (or proficiency) levels. Within and across schools, educators have different understandings and standards for proficiency in our focal areas. We have concluded that we must collaboratively develop agreed upon definitions, understandings and criteria for proficiency in the ELA, Mathematics and Science standards. Therefore, we are prioritizing the establishment of common proficiency criteria within and across schools, based on our content standards.
Our root cause analysis showed that there is a misalignment of expectations from the high school's sending schools that result in varied levels of math achievement and experience. Students entering from one middle school are more ready to tackle algebra content than the other school, despite all students being recommended for high school level algebra. We have concluded that we must establish agreed upon expectations for advancement to algebra at the high school with the middle schools and ensure our high school curriculum is vertically aligned with the middle school curriculum. Therefore, we are prioritizing a commitment to vertical and horizontal alignment by establishing a cross district math PLC.
Use the Atlas Protocol to look at the data you used in Question 5 and 6. Write a root cause analysis paragraph. Read the sample root cause analysis paragraphs in the Text Based Reflection for samples.
Use the Fishbone Diagram to analyze the data you looked at in Question 6. Write a root cause analysis paragraph. Read the sample root cause analysis paragraphs in the Text Based Reflection for samples.
Use 5 Why’s method from the toolkit to analyze the data you looked at in Question 6. Write a root cause analysis paragraph. Read the sample root cause analysis paragraphs in the Text Based Reflection for samples.
Analyze School Union’s Continuous Improvement Team decided to divide into smaller data analysis teams. Despite a very organized plan, two teams ended up inadvertently analyzing the same set of data with the same focus area.
When the whole team came back together to share results, they discovered the mix up and that the root cause analysis paragraphs from each group contradicted one another.
What advice would you give to the team? Should those involved in the original analysis be involved again or should there be all new participants? How is it possible that the same data sets and focus area led to two different root cause analysis statements?
Browse the Colorado Department of Education’s Root Cause Analysis Tool Kit to find practical tools to use in analyzing root causes.