Archived Resources
The Resource Library houses tools and products that were developed by IDC, developed with its collaborators, or submitted by IDC stakeholders. Search and filtering tools are available to help users navigate through the library.
Archived Resources 1 - 4 of 4
Format: Presentations
What to Know About High-Quality Discipline DataThis session reviewed the working principles of high-quality IDEA data as they relate to the various discipline data states must submit each year for children and youth with disabilities. Discussion topics included how states make sure their data are accurate, timely, and complete. Presenters also discussed how states maintain discipline data security while making the data accessible and usable.
Format: Presentations
Using State Data to Inform Parent Center WorkThe purpose of this presentation was to introduce PTI and CPRC directors and staff to the IDEA data collected and reported by state education agencies and discuss how these data can be used to inform many of the fourteen priority topics for the PTI/CPRC network. These priorities were identified in the most recent OSEP requests for proposals for PTI and CPRC funding.
Format: Toolkits and Templates
Educational Environments 3-5 Data Template: Calculating Local Data WorksheetThis data template provides SEAs and LEAs the opportunity to see in real-time the percentages of their children ages 3-5 attending and receiving services in specific educational environments. When the LEA 618 educational environments data is simply entered on the data tab, the percentages will be calculated and displayed on the percentage tab. The use of this tool will allow SEAs to compare the percentages of children within educational environments across LEAs.
Format: Online Applications
The Uses and Limits of Data: Supporting Data Quality With a Strong Data ChainThis online learning module provides a general overview of how the methods and design of data collection and analysis affect interpretation of the data. The module presents the different links in the data chain (e.g., defining the question, measurement strategy) and describes how each link contributes to quality of data and data analyses. The module also includes examples from a selection of Part B and Part C SPP/APR indicators to illustrate how each step in the data chain contributes to the integrity of the data and its interpretation
