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Sources of Disproportionality in Special Education: Tracking Minority Representation through the Referral-to-Eligibility Process
Ashley Gibb M. Karega Rausch Russell Skiba Indiana Disproportionality ProjectIndiana University
National Center for Culturally Responsive Educational SystemsFebruary 17, 2006
Overview History Rationale Referral-to-Eligibility Ratio Preliminary Data Challenges in Assessing the
Referral Process
The Indiana Disproportionality Project (IDP) Collaboration of IDOE and Center for
Evaluation and Education Policy at Indiana University Document status of minority
disproportionality in Indiana Use that information to guide change
planning
Project History and Timeline Phase I (1999-2000):
Developing Measures of Disproportionality Phase II (2000-2001):
Understanding What Contributes to Special Ed. Disproportionality
Phase III (2002-Present): Addressing Disproportionality in Local
School Corporations and Addressing Key Research Questions
Findings: Years One and Two Statewide: African American most
severe Mild Mental Disability 3.29 x more Emotional Disturbance 2.38 x more Moderate MD 1.91 x more Communication Disorder 35% less Learning Disabled 6% less
AA underrepresented in LRE Disproportionality not uniformly
distributed
Beyond the Numbers: Where Does It Come From and What Should We Do?To remediate we first have to
understand Literature review of causes – e.g.
National Research Council, Harvard Civil Rights Project
IDP Qualitative Study LEAD Projects in ten corporations
How Do We Measure Progress? Conversation in district
How do we monitor progress? The problem of short term change in
disproportionality.
Solution: Examine representation at various points in the decision-making process
Exploration of Referral to Eligibility
Rationale
The Contribution of the Special Ed. Process NRC (2002) unable to draw firm conclusion High percentage of students referred are
placed (Algozzine, Ysseldyke, & Christensen, 1983)
Referral most important judgment made in assigning students to disability programs (Ysseldyke & Algozzine, 1983)
Teachers quickly form inaccurate impressions, especially of black males (Irvine, 1990)
The Referral-to-
Eligibility Ratio
Referral-to-Eligibility Ratio (RER)
Referral for Assistance Referral to General Education
Intervention Referral to Psychoeducational
Assessment Special Education Placement
Questions to be Addressed Where in the referral to eligibility
process is disproportionality occurring?
How do we know we are making a difference in disproportionality?
Are our specific general education interventions working?
Data Tracking Process Collecting data from administrators
directly working with pre-referral intervention teams or from central office personnel on Excel form
Data at 4 points in the special education decision making process
Analysis of students within and across these stages
How Do We Know there is Disproportionality?
Composition Index Indicates the representation of a group at a particular stage Example: 100 students are referred for assistance and 25
are Hispanic, the composition is 25% Risk Index
Indicates the risk of a group being represented at a particular stage
Example: 100 African American students attend a school and 10 are assessed for services, risk would be 10%
Relative Risk The ratio of risk for one group compared to all other groups Example: Risk of assessment for African Americans is 10%
and all other students is 5%, then the relative risk for African Americans is 2.0
Calculation Considerations Risk relative to all other students
or one group of students (e.g., white)
Numbers contingent on previous step, or population as a whole
Look at all students going through process, or just initial referrals, re-evaluations, etc.
School District Example
Sample District: King Community School Corporation Diverse, Urban District Wide Use of Pre-Referral
Intervention Form varies widely among schools
Follow students through this sample district to understand the calculations and process
A. Student Population CompositionRacial Category
Students in Participating Schools
Composition of Population by Race
Total 5,171African American 2,903 56.1%White 1061 20.5%Hispanic 606 11.7%Multi-Racial 446 8.6%Asian 150 2.9%American Indian 5 0.1%
Population GraphKing Community School Corporation: Racial Make Up of Student Population
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
African American White Hispanic Multi-Racial Asian American Indian
Racial Group
Perc
enta
ge
Student Population
B. Students Referred for AssistanceRacial Category
A. Students in Participating Schools
Composition of Population by Race
B. Number Referred for Assistance
Composition of Referrals by Race
Relative Risk of Referral for Assistance
Total 5,171 356African American 2,903 56.1% 245 68.8% 1.72White 1061 20.5% 63 17.7% 0.83Hispanic 606 11.7% 22 6.2% 0.50Multi-Racial 446 8.6% 23 6.5% 0.73Asian 150 2.9% 2 0.6% 0.19American Indian 5 0.1% 1 0.3% 2.91
Population & Referrals for Assistance
King Community School Corporation: Racial Make Up of Referrals for Assistance
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
African American White Hispanic Multi-Racial Asian American Indian
Racial Group
Perc
enta
ge
Student PopulationReferrals for Assistance
C. Students Referred to GEIRacial Category
A. Students in Participating Schools
Composition of Population by Race
C. Number Referred to GEI
Composition of GEI Referrals by Race
Relative Risk of Referral to GEI
Total 5,171 343African American 2,903 56.1% 238 69.4% 1.77White 1061 20.5% 59 17.2% 0.80Hispanic 606 11.7% 21 6.1% 0.49Multi-Racial 446 8.6% 23 6.7% 0.76Asian 150 2.9% 1 0.3% 0.10American Indian 5 0.1% 1 0.3% 3.10
Population and Referrals to GEI
King Community School Corporation: Racial Make Up of Referrals to GEI
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
African American White Hispanic Multi-Racial Asian
Racial Group
Perc
enta
ge
Student PopulationReferrals to GEI
D. Students Referred for AssessmentRacial Category
A. Students in Participating Schools
Composition of Population by Race
D. Number Referred for Assessment
Composition of Asment Referrals by Race
Relative Risk of Asmnt
Total 5,171 187African American
2,903 56.1% 121 64.7% 1.43
White 1061 20.5% 42 22.5% 1.12Hispanic 606 11.7% 10 5.3% 0.43Multi-Racial 446 8.6% 11 5.9% 0.66Asian 150 2.9% 2 1.1% 0.36American Indian 5 0.1% 1 0.5% 5.55
Population and Referrals for Assessment
King Community School Corporation: Racial Make Up of Referrals for Assessment
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
African American White Hispanic Multi-Racial Asian American Indian
Student PopulationReferrals for Assessment
E. Students Eligible for Special Education
Racial Category
A. Students in Participating Schools
Composition of Population by Race
E. Student found Eligible
Composition of Students Eligible by Race
Relative Risk of Eligibility
Total 5,171 109African American
2,903 56.1% 68 62.4% 1.30
White 1061 20.5% 26 23.9% 1.21Hispanic 606 11.7% 5 4.6% 0.36Multi-Racial 446 8.6% 8 7.3% 0.84Asian 150 2.9% 1 0.9% 0.31American Indian 5 0.1% 1 0.9% 9.57
Population and EligibilityKing Community School Corporation: Racial Make Up of Students Found Eligible
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
African American White Hispanic Multi-Racial Asian American Indian
Racial Group
Perc
enta
ge
Student PopulationStudents found Eligible
Analysis of RRR’s I. Incidence rate: Student found eligible from
total population (eligible/population) II. Assessment hit rate: Students found
eligible from those assessed (eligible/tested) III. Process outcomes: Students found eligible
from those referred (eligible/referred) IV. Process contributions: Compare III with
referral RRR (difference in RRR between initial referral and outcome of process)
I. Incidence Rate:Students Eligible from Population (E/A)Racial Category
A. Total Students in Participating Schools
E. Number Eligible
Percent Eligible of Student Population
Relative Risk of Eligibility from Population
Total 5,171 109 2.1%African American
2,903 68 2.3% 1.30
White 1,061 26 2.5% 1.21Hispanic 606 5 0.8% 0.36Multi-Racial
446 8 1.8% 0.84
Asian 150 1 0.7% 0.31American Indian
5 1 20.0% 9.57
II. Assessment Hit Rate (E/D)Racial Category
D. Number of Students Assessed
E. Number Eligible
Percent Eligible of Those Assessed
Relative Risk of Eligibility from Assessment
Total 187 109 58.3%African American
121 68 56.2% 0.90
White 42 26 61.9% 1.08Hispanic 10 5 50.0% 0.85Multi-Racial
11 8 72.7% 1.27
Asian 2 1 50.0% 0.86American Indian
1 1 100.0% 3.29
III. Process Outcomes:Students Eligible from Referred (E/B)Racial Category
B. Number of Students Assessed
E. Number Eligible
Percent Eligible of Those Referred
Relative Risk of Eligibility from Referral for Assistance
Total 356 109 30.6%African American
245 68 27.8% 0.75
White 63 26 41.3% 1.46Hispanic 22 5 22.7% 0.73Multi-Racial
23 8 34.8% 1.15
Asian 2 1 50.0% 1.64American Indian
1 1 100.0% 3.29
IV. Relative Risk Ratio (RRR) Through the Referral to Eligibility Process
Racial Category
Referred for Assistance RRR
Referred to GEI RRR
Referred for Assessment RRR
Eligibility Decision RRR
African American
1.72 1.77 1.43 1.30
White 0.83 0.80 1.12 1.21Hispanic 0.50 0.49 0.43 0.36Multi-Racial
0.73 0.76 0.66 0.84Asian 0.19 0.10 0.36 0.31
RER Process Graph
King Community School Corporation: Relative Risk through the Referral to Eligibility Process
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1.80
2.00
Referred for Assistance Referred to GEI Referred for Assessment Eligibility Decision
Stage in Process
Rel
ativ
e R
isk African American
WhiteHispanicMulti-RacialAsian
School Level Data (Trends in RRR)Race Referred
for Assistance
Referred to GEI
Referred for Assessment
Eligibility
School IAfrican American 1.99 2.14 1.33 3.10White 0.66 0.61 1.24 0.53Hispanic 0.62 0.62 0.68 0.90School IIAfrican American 3.15 2.11 1.77 1.36White 0.57 0.57 0.84 0.93Hispanic 0.66 0.69 0.77 0.72
General Conclusions
Within the Process Compare contribution of each stage
to representation of group Compare one group’s
representation at specific stage to representation of other groups
Investigate different outcomes Assessment hit rate, Process
outcomes, Incidence rate
Schools & District Comparisons Which schools are contributing to
over/under representation? How do the schools’ numbers
compare to the district as a whole? How does the process differ across
schools? Leads to questions about the
contextual factors not necessary captured in data form
Challenges in Assessing the
Referral Process
Issues Encountered Calculations based on Small
Numbers
Nature of the Beast
Logistical Challenges
Approaches to Addressing Challenges LEAD Project: Culture
Competence
Technical support
Build in-house systems and ownership
Contact Information Ashley Gibb, Russ Skiba, Karega Rausch
Center for Evaluation and Education Policy509 E. Third St. Bloomington, IN 47401812-855-4438acgibb@indiana.eduskiba@indiana.edumarausch@indiana.edu
IDP Website: http://ceep.indiana.edu/ieo/idp/index.shtml