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Format: Guides and Briefs
Operationalizing Your SSIP Evaluation: A Self-Assessment ToolThe purpose of this tool is to lead those within a state responsible for implementing their SSIP evaluation through the process of operationalizing their SSIP evaluation plan in tandem with implementation efforts. State staff can use this interactive self-assessment to gauge their team’s progress on key components necessary for fully executing their SSIP evaluation plan and to identify action steps needed to realize the greatest benefit from their evaluation efforts.
Format: Toolkits
Data Meeting ToolkitThe Data Meeting Toolkit is a suite of tools that groups can use to guide conversation around data and support data-based decisionmaking. The toolkit provides resources to support success before, during, and after data meetings.
Format: Quick Reference
SPP/APR Indicator Sampling Plan ChecklistStates are allowed to use sampling for collecting data for select Part B State Performance Plan/Annual Performance Report indicators. Sampling can provide an effective means for targeting resources for data collection and improving data quality. However, there are important requirements that states must consider when designing and implementing their sampling plans. States can use this interactive self-assessment tool to determine whether their state’s sampling plan addresses Office of Special Education Programs sampling requirements for best practice and to identify action steps to improve their sampling procedures.
Format: Quick Reference
Checklist to Identify and Address SSIP Data Quality IssuesIn State Performance Report/Annual Performance Plan (SPP/APR) reports, states are required to identify data quality issues that may have arisen during their Indicator 17 State Systemic Improvement Plan (SSIP) work. Using this checklist can help state staff who are responsible for the SSIP apply the principles of high-quality data to identify any data quality issues that the state should report. The checklist includes questions that states can ask themselves to recognize data quality issues that may exist. It provides potential consequences of the issues and offers suggested actions that states can take to address the issues.