Overrepresentation, Underrepresentation, and Remediation in State Coordinated Early Intervening Services Efforts

• In Event: Coordinated Early Intervening Services as a Solution for Significant Disproportionality: What Have We Learned?

Abstract

Objectives or Purposes

In contrast to extensive previous research documenting over-representation in special education (see e.g., National Academy of Sciences, 2002), some recent analyses (Morgan et al., 2015) have suggested that the problem of disproportionality in special education is primarily one of under-representation. Both history and extant data suggest that the issue is highly complex. In this presentation, we will present a mixed method analysis of identification data and remediation efforts in one Midwestern state exploring both the complex patterns of disproportionality in special education, and some effects of current federal policy in addressing disproportionality.

Perspectives/Theoretical Framework

The presentation relies upon previous empirical and statistical analyses showing that the issue of special education disproportionality is complex and multiply determined (Sullivan & Artiles, 2011; NAS, 2002; Skiba et al, 2008). These analyses test whether it is possible to make unitary claims or recommendations about disproportionality without considering complex patterns of disparity across racial categories, states, and school districts.

Methods, Techniques, Modes of Inquiry

This presentation describes a mixed-methods examination of identification and remediation of special education disproportionality that includes a) statistical analysis of a state individual-level data-base of special education enrollment used to identify districts as significantly disproportionate according to IDEA disproportionality criteria, and b) results of qualitative interviews with personnel from one district participating in CEIS remediation efforts in order to examine the process and effects of those efforts.

Data Sources, Evidence, Objects or Materials

Child-count (individual level) data for all special education students in a single midwestern state will be analyzed in order to determine the incidence of over- or under-representation in special education and specific disability categories due to race/ethnicity. In addition, the state, in collaboration with the presenters, has implemented a three-pronged remediation model based on district data review, root cause analysis, and attention to cultural responsiveness. Results from interviews with key personnel in one school district will be presented to highlight local efforts based upon federal policy.

Results

Examination of patterns of identification of districts with significant disproportionality reveals a complex pattern indicating both over- and under-representation varying according to both racial/ethnic group and disability category. African American over-representation for Intellectual Disability and Emotional Disability was most common, there was some under-identification among some racial/ethnic groups, and some districts showed over-representation of White students in Autism.

Themes drawn from analysis of interviews with key personnel in one school district that has made significant progress in addressing disproportionality include the importance of leadership commitment, root cause analysis, and hiring district personnel committed to equity.

Scholarly or scientific significance
The publication of findings purporting to show that the problem of racial/ethnic disproportionality is one of under-representation (Morgan et al., 2015) has already created public controversy (Phippen, 2015), and will doubtless continue to do so as Congress approaches IDEA re-authorization. It is critical that the validity of claims that may influence public policy be thoroughly tested in scholarly venues, in order that policy be informed by accurate and appropriately nuanced scientific findings.

Authors

• Russell J. Skiba, Indiana University

• Choong Chung, Indiana University

• Gwen Kelley, Indiana University

• Mariella Isabel Arredondo, Indiana University