By Carol Cannerelli, J.D.

Correcting the issues surrounding disproportionality are complex and time-consuming. 

But the overall benefits to both your general education and special education students are without question. Failure to correct lingering issues could result in closer examination and penalties by the Office of Civil Rights, which establishes national guidelines for State Departments of Education to identify significant disproportionality.

Even with Data Teams in place at K-12 Districts, the complexity, requirements, and processes are labor-intensive and require ongoing skill and attention to many details.

Our consultants are working within K-12 Districts to guide, counsel, and advise your data teams on approaching and mitigating disproportionality issues.

To review from my previous blogs on this subject:

Significant disproportionality covers several groups and subgroups and occurs in the following areas:

• • Over or under-representation of specific groups in special education when compared to the representation of that subgroup in the overall enrollment of the district.

• • Under-representation of specific subgroups in specific programs, such as gifted programs or honors or advanced placement (AP) courses.

• • Over-representation of specific subgroups in more restrictive placement settings.

• • Over-representation of specific subgroups who are the subject of discipline, particularly more severe forms of student discipline such as out-of-school suspension.

For a detailed discussion of disproportionality, please see two previous 2022 blogs that provide a history and specific information about the specific subgroups and categories and how significant disproportionality is determined. 

Addressing Warnings & Notifications Concerning Disproportionality from the DOE

Many districts are currently beginning to receive corrective actions or notifications from the Department of Education (DOE) that they have been identified as having significant disproportionality. If a district is found to have three years of such warnings, they are placed under corrective action and required to commit 15 percent of grant funds from the Individuals with Disabilities Act toward Coordinated Early Intervening Services (CEIS).

The result is diverting 15% of their special education funds to pre-eligibility services. CEIS requires districts to identify and track at-risk students who may be referred for special education eligibility and services and provide them with intervention resources that hopefully will avoid the need for special education. CEIS-funded programs aim to ensure students are appropriately identified as eligible for special education services.

In addition, through the State Office of Special Education (OSEP) monitoring programs, districts are being asked to review their identification practices to ensure compliance with all legal requirements for specific eligibility categories and for the least restrictive placement of students who are eligible for special education.

The DOE has a three-year warning system prior to identifying a district as experiencing significant disproportionality. DOE will identify for your district-specific subgroups such as students of particular racial/ethnic backgrounds, English Learners (ELs), etc., who may be over- or under-represented in special education or gifted programs or who may be subject to more significant forms of discipline based upon the information districts report to the State in their Fall or end of year submissions as well as their reporting to the DOE on student discipline. The DOE is using your district’s submitted data to determine this.

Not Knowing What You Don’t Know – Why Having a Data Team to Address Disproportionality May Not Be Enough

Since districts submit this data multiple times per year, they often have their own data teams to begin to identify internal practices that may result in such significant disproportionality.

However, many of them fail to include people familiar with the State’s requirements in relation to significant disproportionality, nor do they know the kinds of data to analyze to identify these issues early on.

Other challenges include:

• • The data teams are not familiar with the district practices, particularly Child Study Team identification practices, which could result in such disproportionality.

• • Correction requires specialized training for the data teams concerning the elements of significant disproportionality and training of I&RS teams and CST members in specific eligibility identification practices.

• • Data teams need to know the various categories the DOE is analyzing when determining significant disproportionality.

• • They then need to gather specific data related to the more than 90 combinations of categories by which such determinations are made.

• • They must analyze such data in their own buildings and meet together with data teams from other buildings to identify broader patterns that transcend individual buildings.

• • The CST members also need to review this data and delve deeply into their identification practices. What is the overall classification rate of the district? Is it high when compared to the State and national averages? What factors are contributing to high levels of identification?

Often, our consultants hear explanations for significant disproportionality, such as, “We have many immigrant families where English is not their primary language” or “We are a high-poverty district.”

Yet, the IDEA, the Office of Civil Rights, the DOE, and the publishers of the various test instruments used by CST members all warn that these factors must be carefully considered to exclude students from possible eligibility. Thus, CST and I&RS members need training to analyze the impact of such environmental factors on eligibility decision-making. This will become even more important should the pending proposed legislation to eliminate the discrepancy formula from consideration when identifying specific learning disabilities pass.

As part of MTSS, districts must have building data teams in place.

These data teams should:

 

• • Review their building’s data about who gets referred for possible special education eligibility.

• • Identify which students are eligible for gifted or advanced courses.

• • Identify who is being subjected to the more severe forms of discipline and for what types of infractions.

• • At least annually, data teams should meet with other buildings’ teams to identify patterns unique to specific buildings as well as global patterns across your entire district.

To learn more about managing disproportionality and identifying disparities in your district or to get help with your data analysis, reach out to us at [email protected]