Now that your students have taken an assessment, it’s time to start analyzing your data. But where do you start?
This article will explore two data analysis processes to help dissect and analyze your students’ assessment data: Patterns of Need and Root Cause Analysis.
What are Patterns of Need?
Patterns of need are meaningful patterns that emerge when data are visualized or organized in a way that supports data analysis and decision-making. First and foremost, patterns and needs should be initially thought about separately.
Patterns are common results in data for a group of students. A pattern should be specific and allow you to target instruction where it is needed. For example, you might notice that although the average on an assessment was 85%, more than 70% of students missed questions 3, 4, and 5—indicating a pattern in your data.
Needs are areas that impact student performance. Continuing with our same example, we might find that questions 3, 4, and 5 were the only three questions that focused on one particular standard. Areas of need may be skilled-based or content-based. Need does not necessarily mean an area of weakness; there could be a need for enrichment if there is a pattern of student strength.
When looking for patterns of need, we want to look for clusters of students. Doing so is not only more efficient and effective, but also provides opportunities for answering “big picture” questions and examining teaching practices. When we focus our attention on clusters of students, it highlights a weakness in our instruction, curriculum, or another broader area.
Identifying patterns of need provides educators with two invaluable opportunities:
(1) gaining a deep understanding of trends in students’ challenges and strengths
(2) brainstorming collaboratively around instructional strategies for enriching students’ strengths and building on areas where instruction can improve.
Let’s take a look at an example:
First, we review the data to look for our patterns, or clusters of students. Then, we articulate what we observe in our data (characteristics) and the specific data that display those findings (the evidence). An example is shown below, focusing on the Period 2 class.
As you complete this work, you may find a number of clusters of students or patterns of needs. However, not all patterns of need are equally important. As a team, determine which patterns of need stand to provide the highest impact if solved. These will be your priorities to address first.
Once a priority pattern of need is identified, we feel a great deal of pressure to act. Solutions may be mandated, sometimes before a problem is truly identified. But without alignment to need, solutions treat the symptoms of a problem—not the problem itself. Root cause analysis helps us address the true problem underlying a pattern of need, instead of just symptoms.
What is Root Cause Analysis?
Root cause analysis is a structured approach to uncovering the factors that resulted in a previously identified positive and/or negative pattern of need.
The Massachusetts Department of Elementary and Secondary Education refers to a root cause as “an underlying factor or condition that creates a problem and that, if addressed, would eliminate or dramatically alleviate the problem.”
Too often, we focus on a symptom or quick fix to address an issue, only to find that the issue returns. Root cause analysis helps dissolve the actual problem, not just the symptom. It eliminates patching and wasting effort. Root causes represent the deepest underlying factor(s) that lead to a pattern—whether positive or negative. These may be either supports or barriers to student learning. If these root causes are addressed, educators can prevent negative recurrences and replicate and build upon positive effects.
The purpose of root cause analysis is to determine:
(1) What happened and why it happened
(2) A course of action to eliminate the true need or root cause
Root cause analysis can help transform a reactive culture into a proactive culture that solves problems before they occur or escalate. It’s important to note that root cause analysis is not intended to place blame on anyone. Rather, it’s intended to understand where the most energy and attention should be placed in order to get different results.
Root Cause Analysis Template
So how do we actually go about the process of root cause analysis?
There are a number of protocols that teams can follow. Protocols are based on the premise that adult behavior and district processes impact student learning outcomes. If we believe that all students can learn, and our data show us that students aren’t currently learning successfully, then we need to determine what we can do differently.
For our purposes here, we’ll highlight a frequently used protocol called the Fishbone Diagram Protocol:
Here, teams generally pick 6 possible categories and brainstorm potential root causes for the pattern of need. Examples categories include: curriculum, assessment, instruction, professional knowledge and craftsmanship, culture and climate, school processes, individual teacher, individual learner, or external factors.
From here, the group eliminates any ideas that aren’t root causes—or are root causes that are out of the team’s control. Only some of the causes are controlled by the school, and we must focus solutions on the causes that we can influence in order to be effective and efficient.
Next, they prioritize and choose a root cause area to address. Problems usually have multiple causes—and not all causes are equally important.
Finally, they start to drill down to the underlying problem by continuing to ask, “Why?” From here, the group is able to design a plan to address the root cause they have identified.
Illuminate supports districts nationwide with data analysis and professional learning that yields high-impact data-driven decisions. To learn more or to receive additional protocols, reach out.
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