Resource Library

The TA guide describes the methods a state might use to appropriately determine which of its districts has a significant discrepancy (including a significant discrepancy by race or ethnicity) in the rates of out-of-school suspensions and expulsions totaling greater than 10 days for children with disabilities.

This TA guide addresses the more common methods for calculating racial/ethnic disproportionality in special education. IDC revised the guide, which the Data Accountability Center (DAC) originally published in October 2011, because of a change in SPP/APR Indicators 9 and 10 to remove underrepresentation from the measure.

The Importance of High-Quality Data and the Role of Business Rules instructional video provides a brief introduction to the concept of using business rules to promote and support the collection of high-quality data within state and local systems for IDEA Part B and C.

The Incorporating Business Rules Into State Data Systems instructional video explores the different ways Part B and Part C state agencies can incorporate business rules into their IDEA state data collection and reporting systems.

IDC designed these two technical assistance products to be used by state personnel responsible for IDEA 618 and/or 616 data. The products include a step-by-step guide on completing an outlier analysis, with a brief introduction on the principles of outlier analyses, and a tool state staff can use to conduct outlier analyses with their local data. IDEA Part B state staff working with LEAs also can use both products to analyze their local data.

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

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.