Resource Library

This resource focuses on recent changes in the data source and measurement of Part B Indicators 1 and 2. The resource specifically addresses the treatment of “alternate diploma” in the new calculation. In FFY 2019, the calculation of graduation rate included students receiving an alternate diploma in the numerator. For FFY 2020–2025 the calculation of graduation rate includes students receiving an alternate diploma in the denominator. The calculation for Indicator 2 remains similar from FFY 2019 to FFY 2020–2025; however, it explicitly adds students receiving an alternate diploma in the denominator. 

This tool from IDC and NTACT calculates graduation and dropout rates using the 618 Exiting data, as OSEP will require in coming years for reporting in states’ SPP/APRs. The tool can accumulate and graph multiple years of data, allowing users to observe trends in the rates over time and share the information easily with stakeholders.  

The FFY 2020–2025 SPP/APR Resources At-a-Glance is a list of resources from OSEP and IDC that states can use to support their understanding and actions related to the FFY 2020–2025 Part B SPP/APR.

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.

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.