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The Individuals with Disabilities Education Act (IDEA) requires states to monitor and enforce IDEA Part C and Part B requirements, with a primary focus on those requirements that are most closely related to improving results and functional outcomes for infants, toddlers, and children with disabilities. To support states to carry out these monitoring responsibilities, A State Guide on Identifying, Correcting, and Reporting Noncompliance with IDEA Requirements describes the IDEA requirements related to identifying noncompliance, making findings of noncompliance, correcting and verifying correction of noncompliance, and federal reporting on compliance and correction of noncompliance in the state’s SPP/APR. This guide is based on the Office of Special Education Programs (OSEP) Memo 09-02: Reporting on Correction of Noncompliance in the Annual Performance Report Required under Sections 616 and 642 of the Individuals with Disabilities Education Act and the OSEP Frequently Asked Questions on Identifying and Correcting Noncompliance and Reporting on Correction in the SPP/APR.

This companion resource to A State Guide on Identifying, Correcting, and Reporting Noncompliance with IDEA Requirements summarizes the responsibilities of local early intervention programs or Local Education Agency, state Lead Agency or State Educational Agency and data that needs to be reported to OSEP on compliance, correction of noncompliance and verification of correction for SPP/APR indicators.

There is a continuous need for state education agencies (SEAs) and local education agencies (LEAs) to collect and report comprehensive, high-quality data and ensure they report data accurately and in a timely fashion. The customizable IDC LEA Data Processes Toolkit is a new instrument that can improve decisionmaking about children and youth with disabilities by ensuring data are of high quality and processes are clearly defined and documented, while also providing data staff a map for documenting data processes within local districts.

This resource provides a summary of findings from 28 states’ publicly available LEA determinations processes. States can use this resource to learn more about the data elements, calculation methodologies, and determination category criteria these 28 states used for making LEA determinations. This information can be particularly valuable for those states considering revisions and updates to their own LEA determinations processes.

The LEA EDFacts Edit Check and Data Display Tools allow states to identify potential business rule errors or errors in category sets, subtotals, or totals prior to submitting the data to OSEP via the EDFacts Submission System. The tool also provides states with user-friendly data summaries.

The Interactive Institutes 2020 – Building and Sustaining a Culture of High-Quality Data provided opportunities for participants to take a deep dive into data quality topics to learn about data culture change. Participants were able to discover best practices to improve data collection, reporting, analysis, and use. They also engaged with peers and TA providers about trending data quality topics. Each session presented powerful ideas and actionable plans to improve work processes and data quality.

The purpose of this resource is to unpack Part B SPP/APR Indicator 3D to better understand how to use Indicator 3D results to improve outcomes for all children with IEPs. This resource guides the reader through Indicator 3D, including how to calculate it; information on the setting/resetting of its baselines and targets; and considerations when analyzing, reporting, and using Indicator 3D data. As an aid to deepen learning, this resource includes examples with fictitious data.

The NRBA App is an interactive nonresponse bias application powered by state-of-the-art statistical software. We developed this application to help states examine their SPP/APR Indicator 8 and Indicator 14 data through nonresponse bias analysis. The NRBA App allows users to conduct reproducible analyses of response rates, representativeness, and nonresponse bias, tailored to their survey’s data collection method.