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Root Cause Analysis: Using Data to Improve Students' OutcomesThis webinar helped states and local education agencies (LEAs) learn how to use root cause analysis to analyze their 616 and 618 data and use the results to improve student outcomes. States and LEAs should conduct a root cause analysis when these data show that some groups of students are succeeding at lower rates than other groups are. Presenters discussed how to perform a successful root cause analysis in order to identify why performance or achievement gaps are happening and prevent them from reoccurring. Staff from the South Carolina Department of Education presented on the state’s use of the IDC Success Gaps Toolkit for root cause analysis with LEAs and the solutions the LEAs implemented as a result of their analyses.
Format: Guides and Briefs
Measuring Significant Discrepancy: An Indicator B4 Technical Assistance GuideThe TA guide describes the methods a state might use to appropriately determine which of its districts has a significant discrepancy (including a significant discrepancy by race or ethnicity) in the rates of out-of-school suspensions and expulsions totaling greater than 10 days for children with disabilities.
Format: Guides and Briefs
Methods for Assessing Racial/Ethnic Disproportionality in Special EducationThis TA guide addresses the more common methods for calculating racial/ethnic disproportionality in special education. IDC revised the guide, which the Data Accountability Center (DAC) originally published in October 2011, because of a change in SPP/APR Indicators 9 and 10 to remove underrepresentation from the measure.
Format: Guides and Briefs
Collecting and Reporting the New Data Elements Related to the Local Education Agency Maintenance of Effort ProvisionsProduced by IDC and CIFR, this resource discusses each of the four new data elements OSEP is adding related to the LEA MOE provisions of IDEA in the MOE Reduction and CEIS data collection. The resource reviews each new element, presents information about actions the SEA may take to address and answer the questions posed for each of the four data elements, and provides additional support and assistance as states prepare to collect and submit these data.
Format: Quick Reference
A Comparison of Mandatory Comprehensive Coordinated Early Intervening Services (CCEIS) and Voluntary Coordinated Early Intervening Services (CEIS)In December 2016, OSEP finalized new regulations on significant disproportionality (34 CFR §300.646). These regulations enforce the use of IDEA funds for mandatory CCEIS, which LEAs provide upon identification of significant disproportionality, and distinguish use of funds for CCEIS from the use of IDEA funds for voluntary CEIS. This resource is a handy chart that outlines the differences between CCEIS and voluntary CEIS.
Format: Guides and Briefs
Examining Representation and Identification: Over, Under, or Both?Significant disproportionality with regard to identifying children as children with disabilities or as children with specific disabilities is, by definition, overrepresentation. This resource defines overrepresentation and three related terms: over-identification, under-identification, and underrepresentation. States can use this resource, in conjunction with the Success Gaps Toolkit to help identify and address the factors contributing to significant disproportionality (i.e., overrepresentation) within school districts.
Format: Guides and Briefs
Success Gaps Rubric: Addressing Equity, Inclusion, and OpportunityThis rubric allows a team of users from a district or school to systematically examine the root causes of success gaps among groups of students by focusing on equity, inclusion, and opportunity. The recently updated rubric now includes considerations for children as young as preschool age. A complementary white paper provided the research-based background that supported development of the rubric.
