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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 of Part B and Part C indicators. Questions posed included: What is the difference between student outcomes and program performance? Can your data tell you which states, districts, or programs are performing better? What policy questions would you like to know about that your data currently cannot answer?

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 all groups of children and outcomes for some groups are different than outcomes for most groups. The toolkit, with its process and materials, provides a manageable and defined way for districts or schools to identify success gaps that are present and their root causes and then make a plan for addressing the gaps. The success gaps may be the graduation rate of students who are English learners compared to the rate of all other children, the out-of-school suspension rate of children who are Black compared to the rate of all other children, the identification of children who are Hispanic as children with specific learning disabilities compared to the identification of all other children, and other gaps.

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 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.

Many schools and districts have been identified as low performing or disproportionate because of disparities between subgroups on a variety of success measures. Other schools and districts are proactively trying to address identified success gaps. Presenters from IDC demonstrated IDC's Success Gaps Toolkit that can help schools and districts 1) prepare all of their students for success in college and careers by addressing success gaps, 2) collect and use quantitative and qualitative data for the purpose of root-cause analysis of those success gaps, and 3) focus attention on those root causes for the benefit of children and students in the lowest performing subgroups.

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.

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.

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 certain groups of students. Helpful handouts are included.