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The Success Gaps Toolkit presents a process for using data and the Success Gap Rubric to identify root causes of gaps between groups of children in districts or schools. These success gaps occur when the education system is not meeting the needs of...

This 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...

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...

This online learning module provides a general overview of how the methods and design of data collection and analysis affect interpretation of the data. The module presents the different links in the data chain (e.g., defining the question...

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...

Produced 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...

The presentation provides a self-assessment rubric that can help states and local districts view their school/district programs and practices with an "equity" lens and help states and LEAs understand the reasons for discrepancies in outcomes between...

This white paper focuses on elements of equity, inclusion, and opportunity that can minimize or eliminate success gaps among different groups of students. It provides the research-based background that guided development of a complementary rubric...

Validity is about more than results—it is determined by the question asked, the data collection design, and analysis. In this session, presenters led a discussion on what the data can, and cannot, say about outcomes, using examples from a selection...

Presenters introduced a research-based guidance document and self-assessment rubric designed by OSEP's Disproportionality Priority Team to help districts and schools identify the root causes of "success gaps" for some groups of students, thereby...