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Inclusion Through A Different Logic Model PowerPoint Presentation
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Inclusion Through A Different Logic Model

Inclusion Through A Different Logic Model

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Inclusion Through A Different Logic Model

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    1. Inclusion Through A Different Logic Model Wayne Sailor University of Kansas Washington, DC September 19 & 20, 2008

    2. Inclusion The Good News Better educational and social outcomes as verified from research Better fit with federal policy (i.e., ADA; IDEIA) Consistent with Supreme Court decisions challenging LRE

    3. Inclusion The Bad News Disconnected from general curriculum Velcro-aide (dedicated paraprofessional) blocks natural interactions Disruptive to general education class Driven by special education with little or no participation from general education

    4. A BETTER APPROACH (Perhaps) Integrate all school resources for the benefit of all students Accomplish de facto inclusion through collaborative instruction Driven by general education with support from special education

    5. Competing Logic Models Contemporary logic Medical Model Teaching/learning informed by psychology Locus of academic/social failure of child Pathologizing process (i.e., LD; EBD; etc.) Diagnostic/prescriptive remedy Requires quasi-medical industry to service referrals Emphasizes place rather than need (congregate service delivery)

    6. Competing Logic Models (cont.) Suggested logic RTI Model Teaching/learning informed by sociology and anthropology (in addition to psychology) Locus of academic/social failure is ecology of the child Addresses measured needs of child rather than assesses pathology Addresses prevention rather than remediation Integrates specialized resources so all students benefit Reduces referrals for IEPs (special education)

    8. Schoolwide Applications Model (SAM) (www.samschools.org) Transformation from medical to RTE logic models Comprehensive school reform

    9. SAM Features Full integration of all resources and supports (i.e., no special classes) Implementation fidelity tool (SAMAN) Good psychometrics Samples 15 indicators Assessments twice per year 1 day per assessment per school Predicts proximal and distal outcomesacademic and social (from regression)

    10. SAM Features (cont.) Data-based decision making process Screening for risk (academic/social) Progress monitoring for students below benchmark (academic) or with office referrals (behavior) Interventions for all students at level-1 Group and individual interventions at levels 2 and 3 Community-school processes Parent partnerships Community partnerships

    11. 2008-2009 Academic Year 8 elementary schools in Washington DC School District