Skip Navigation

Phase II: Data and Root Cause Analysis

Description of Phase Two: Data and Root Cause Analysis
Phase Two activities are focused on engaging in a programmatic self-assessment process to reveal the root cause(s) of disproportionality, and planning for implementation of Coordinated Early Intervening Services (CEIS) that address the root cause(s) identified.

Activity One: Complete a Local Educational Agency Initiative Inventory
Conduct a review of local educational agency (LEA) initiatives. Aligning and integrating the significant disproportionality improvement process with other LEA initiatives builds supports for the work of the LEA and coordinates positive outcomes for all students. For this activity, please use the Local Educational Agency Initiative Inventory analysis sheet provided in the Phase Two: Featured Tools and Resources section.

Activity Two: Choose and Complete a Programmatic Self-Assessment Tool
A programmatic self-assessment should include the following elements:

  • Selection and completion of one or more of the self-assessment options described in the Phase Two: Featured Tools and Resources section
  • Thorough and reflective analysis of a broad range of student-level data with a focus on ethnic/racial, discipline, disability, and placement disparities
  • Reflective review of information on policies, procedures, and practices (beyond questions of compliance)
  • Review of existing LEA-wide and schoolwide initiatives
  • Review summary of self-assessment results with the stakeholder group

The programmatic self-assessment options in the Phase Two: Featured Tools and Resources section describes methods to analyze LEA practices to reveal information about significant disproportionality. Each option contains methods the LEA may use to better understand characteristics which may have caused the significant disproportionality.

Activity Three: Conduct Reflective Data Analysis
Through the self-assessment process, analyze the identified data elements. Use tools in the self-assessment material provided in the Phase Two: Featured Tools and Resources section. A thoughtful and comprehensive programmatic self-assessment will produce both qualitative and quantitative data to reveal a great deal about current conditions in the LEA and at specific school sites. The assessment process should engage the leadership team and stakeholder group in conversations about student outcomes, as well as the policies, procedures, practices, and beliefs that contribute to those outcomes. In these conversations, participants begin to share hypotheses about the causes of disproportionality, and consider these hypotheses in relation to the data they are reviewing. The next step is a more systematic root cause analysis.

Activity Four: Determine Root Cause(s) Based on Data
A root cause analysis is a process that leads to a narrowing of potential causal factors of a problem to specific areas of focus. From the determined area(s) of focus, leverage points may be identified which lead to the greatest impact for change. The most important function of this process is for the LEA to use evidence and data to gain a deeper understanding of the possible cause(s). At the end of the process, the LEA should be able to briefly describe the area(s) of focus and leverage points that they have identified for improving student outcomes. These conclusions will inform and guide the selection of area(s) of focus, a theory of action, and the development of a data-driven Programmatic Improvement Action Plan.

LEAs may find the research article by Dr. Edward Fergus, “Distinguishing Difference from Disability: The Common Causes of Racial/Ethnic Disproportionality in Special Education,” helpful in this process. The article describes some of the commonly identified root causes of disproportionality based on work completed through the Metropolitan Center for Urban Education over six years using a data-driven process. The article also provides information on potential remedies for these common policies, practices, and beliefs that place racial/ethnic minorities and low-income students at risk. This article is available at  (4.5MB).

Return to Top

Comments are closed.