Resource Library

The IDEA Part B Confidentiality Checklist can aid state and local agencies in identifying actions, policies, and procedures needed to meet confidentiality provisions outlined in the IDEA Part B, 20 U.S.C. §1400.

This tool provides a list of privacy resources for IDEA.

Data Sources for Calculating Significant Disproportionality provides a summary of the data needed to calculate significant disproportionality for identification, placement, and discipline.  For each category of analysis, this resource  provides a description of the data needed to calculate the risk numerator and risk denominator,  and notes the relevant EDFacts file specifications, including which subtotals or category sets, as appropriate. 

Use this interactive PDF to learn more about the different components of high-quality data.

Data for Part B Indicator 3 follow a long and complicated process that begins when a student is registered as a test taker in a state assessment system and ends with public reporting via the SPP/APR. Multiple factors are involved in this process, and regular and ongoing communication and collaboration among the various people involved can make this process easier. This suite of four resources can help states with the work. The interactive infographic provides general information about the process for a typical state.

The IDEA Part B Data Manager Competencies tool outlines foundational knowledge and skills necessary for typical data manager roles and responsibilities. The competencies reflect principles for effective management, support, and use of high-quality IDEA Part B data and fall under one of three overarching categories: content knowledge and skills, technical knowledge and skills, and interpersonal skills. 

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.