Responding to Special Education Disproportionality

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Responding to Special Education
Disproportionality

• A Work Session for School Districts Continuing to
  Address the Concern
• Presenter
• Jack Jorgensen
• 8-5-08

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Special Education Disproportionality

• Looking for answers to complex questions

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Presentation Topics

• Special education disproportionality defined
• Providing a context framing the problem
• One districts story the Madison Metropolitan
  School District
• Examining data to understand the scope and nature
  of the problem
• Using data to inform our conversations and to
  help target areas of improvement

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• Disproportionality
• Discrepancy in the performance or
• representation of one group of students when
  compared to another group.

• Special Education
• Disproportionality
• The overrepresentation of racially,
  culturally and linguistically diverse students in
  special education has been well established in
  over 30 years of research and is emphasized as a
  critical issue in IDEA 04.

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A Context for Disproportionalityframing the
problem

• Is it about

• keeping students of color out of special
  education?

NO!

• improving the evaluation procedures that are
  used to
• determine disability and need for special
  education?

YES

• more stringent application of the eligibility
  criteria,
• including exclusionary factors?

YES

• improving early intervening services and
  strengthening
• student interventions prior to a referral?

YES!!!
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Special Education Disproportionality in the MMSD
One districts response

• Primary Goal
• Eliminate race as a predictor of a child
  being labeled and placed in special education.

• Related Goal
• Eliminate race as a predictor of a child
  with a disability being disproportionately
  excluded from gen. ed., suspended, expelled or
  not completing high school.

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MMSDs use of data to understand the scope and
nature of the problem

• Overall S.E. prevalence rate
• Percentage of students in S.E. by ethnic group
• Risk Ratios
• S.E. referral and placement rates
• Referral and placement data desegregated by
  ethnicity, primary disability, socio-economic
  status
• New students to special education where were
  they coming from?
• Least Restrictive Environment
• Suspension, expulsion, attendance and high school
  completion
• Transfer students

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MMSDs Data

• Understanding the scope and
• nature of disproportionality in one
• Wisconsin school district

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MMSDs Risk Ratio2006-07 Year (Ages 6-21)
Risk ratio compares the risk of one racial/ethnic
group to the risk for all other racial/ethnic
groups combined.
LIAutism, Deaf-Blind, Hearing Impairment,
Orthopedic Impairment, Significant Developmental
Delay, Traumatic Brain Injury, Visual Impairment
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Using Risk Ratio to further understand where
the district is disproportionality represented

• What is Risk Ratio?
• Risk ratio compares the risk of one racial/ethnic
  group
• to the risk for all other racial/ethnic groups
  combined.
• Calculating Risk AA students w/CD 130
• ALL AA students 5,360
• All other racial/ethnic students w/CD
  132
• All other racial/ethnic students
  18,982
• Calculating Risk Ratio 2.43
• 0.70
• Risk AA are 3 ½ times as likely to be
  receiving SE services for CD than all other
  racial/ethnic groups combined.

2.43
0.70
3.49
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Poverty, Race and K-12 Initial 2006-07 Placements
2005-2006
2006-2007
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Going Deeper Into the Data

• Revealing other faces of disproportionality
• in the MMSD
• District Enrollment Percent in Special
  Education
• LRE Comparison (06-07 and 07-08)
• Risk Ratio
• Suspension
• Expulsion
• Attendance
• High School Completion
• Transfer student data

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MMSD District and Special Education
Enrollment Comparison of 2002-03 and 2007-08
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Special Education K-12 Enrollmentby Least
Restrictive Environment(special education
services outside general education classroom)
2005-06
2007-08
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Suspension Rates2006-07 School Year K-12
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Expulsion Rates2006-07 School Year K-12
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Attendance Rates2006-07 School Year
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High School Completion Rates2006-2007 School Year
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ExaminingK-12 Transfer Student Data

• Primary Disability
• Entering and leaving by grade Level
• Outcome of File Review
• Ethnicity
• Improvements

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Outcome of Transfer File Reviews from 9/2007 to
6/2008
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Using Data to Inform our Conversations and Target
Areas of Improvement

• Risk Ratio
• Transfer Students
• School Data Packets
• Professional Development

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Response to Concerns Risk Ratio

• Secured a WI Department of Public Instruction
  mini-grant to examine root causes as to why
  African American and American Indian students are
  at greater risk of being labeled EBD and SLD
• Entered into multi-year partnership with National
  Institute for Urban School Improvement - NIUSI
• Focused on greater adherence to the eligibility
  criteria, especially for overrepresented groups
  (e.g., African American students)
• Continued

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Response to Concerns Risk Ratio

• Examined more carefully transfer students to MMSD
  and the effect on our disproportionality.
• Using DPI grant funds, employed university
  personnel to develop a process and tool to assist
  with addressing the exclusionary factors
  Culturally Responsive Practices in Schools The
  Checklist to Address Exclusionary Factors When
  Considering Special Education Eligibility
  Determination.

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Response to Concerns - Transfer Students

• Dedicated psychologist allocation to review all
  transfer student special education records to
  determine if an evaluation was warranted
• In-state transfers were referred to school as
  reevaluations
• Out-of-state transfers were referred for initial
  evaluations
• Improved version of exclusionary factor checklist
  tailored specifically for the review of transfer
  records
• Eligibility criteria checklist developed for each
  disability area are now used in the transfer
  student record review process

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Response to Concerns - School Data Packets

• Individual School, Level, District Data
  Disaggregated by
• Referral Placement Data
• Ethnicity
• Gender
• Class
• Socio-Economic Status
• Least Restrictive Environment Data
• Ethnicity
• Gender
• Socio-Economic Status
• Risk Ratio Data
• Achievement Gap Data
• Behavior Data (e.g., expulsions, suspensions,
  etc.)

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A Sample of Questions You Might Ask

• Examining your referral/placement data by
  ethnicity, is there a high rate of referrals
  coupled with a low rate of placements in any of
  the groups?
• If so, what actions might you consider?
• How does our data compare with district data and
  other schools?
• What might account for differences in our
  schools data

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Response to Concerns - Professional Development

• MMSDs Educational Framework where does
  disproportionality fit? EIS and RTI?
• National Institute for Urban School Improvement
  (NIUSI) - a partnership to address
  disproportionality
• Created a Student Intervention Monitoring System
  (SIMS) and provided corresponding professional
  development

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Closing The Achievement Gap
Comprehensive System Supporting Positive Behaviors
Early Intervening Services Response to
Interventions
Race Equity
Kronenberg Training
SIMS
Mixed ability Classrooms Inclusive Education
Team Infrastructure
Disproportionality
Instructional Design
Developing Inclusive High Performing
Middle School Leadership Institute
LRE Data
Risk Ratio w/EBD SLD
ExclusionaryFactor Checklist
Parent/ Community Involvement
Suspension Expulsion Data
Non-biased Multicultural Assessments
UW Grant
Parent Survey
Spec. Ed. Advisory Council
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How does NIUSI support the MMSD Framework and
related initiatives?
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The Goal of our Partnership with NIUSI

• The goal of our partnership with NIUSI is to
  eliminate race and culture as predictors
• of success in MMSD (including the risk of
  referral and placement to special education) by
  using research based racially and culturally
  responsive practices to support Engagement,
  Learning, and Relationships.

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10 Elementary Schools Selected to Partner with
NIUSI Focus on Professional Development

• Leadership Teams and Culturally Relevant
  Practices
• Disproportionality
• Instructional Design
• Co-teaching and co-planning for collaborative
  instructional teams

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In closing where do you begin to address
disproportionality?

• Critically examine your district data and provide
  your schools with their own data to discuss
  understand the problem!
• Race and Equity are you ready to have
  courageous conversations?
• Develop a multi-year, comprehensive improvement
  plan that addresses all facets of
  disproportionality (EIS, RTI, non-bias/multi-cultu
  ral evaluations, etc.)
• Professional development learn together!

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As Diversity Grows, So Must We a quote by
author Gary Howard

• School leaders should also model for their
  colleagues inclusive and nonjudgmental
  discussion, reflection, and engagement strategies
  that teachers can use to establish positive
  learning communities in their classrooms

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Questions/Comments