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During our first Significant Disproportionality Summit on November 9 and 10, 2021, IDC brought states and districts together to discuss strategies, processes, and infrastructures related to significant disproportionality. The Summit included a keynote session followed by six plenary sessions focused on topics such as cultivating robust stakeholder teams, conducting root cause analysis, addressing different types of disproportionality, and evaluating improvement strategies. For each session, we present the session title and description, the recorded video, and the link to the PowerPoint slides.

States are identifying districts with significant disproportionality and supporting them to address the root causes of the significant disproportionality. But are states seeing districts show improvement in significant disproportionality? What changes are districts achieving? How are states supporting these districts to improve the schooling experiences that lead to the identified disproportionalities and evaluate their progress? State and LEA panelists shared the small and large changes they have achieved, support strategies they have used, and lessons they have learned. Participants learned about ways states are working with districts to measure increments of change, evaluate progress, and make midcourse adjustments in policy and practice to address significant disproportionality.

Do you wonder how other states make districts aware of and help them understand their data related to significant disproportionality? How do states help districts understand their responsibilities when the state has identified them with significant disproportionality? What kinds of early warning systems do states use so districts understand when they are at risk for significant disproportionality? State panelists answered these questions and more during this IDC webinar. Attendees learned about proactive strategies states are taking to help districts understand and use data related to significant disproportionality, as well as other supports states provide for districts both before and after their identification with significant disproportionality.