The Part C Exiting Toolkit allows users to access five different downloadable forms that will assist in the documentation of their Part C Exiting Process and provides checklists they can use to ensure high-quality data. The toolkit also contains the Part C Exiting Counts app. The app is a great tool for understanding the 10 federal Part C Exiting categories. The toolkit also contains links to documents that use Part C Exiting data and to other related resources.
Resource Files & Links
Related Content
Format: Online Applications
Part C Exiting CountsIDC's Part C Exiting Counts app allows users to test their knowledge of the 10 Part C Exiting categories by either starting with a child scenario and deciding which reason and category best fit the scenario or starting with a reason and category and deciding which child scenario best fits that reason and category.
Format: Checklists, Crosswalks, and Rubrics
Part C Exiting Data Matrix: Categories with Child-Level ExamplesThis matrix is both a standalone product and the fourth section of the IDEA Data Center Part C Exiting Data Toolkit. It contains scenarios for each of the 10 exiting categories. The Part C Exiting Data Toolkit is designed to assist states in reporting high-quality Part C exiting data, required under Section 618 of IDEA. The remaining three sections in the Part C Exiting Data Toolkit are: Part C Exiting Reasons and Categories (Section 1); General Challenges and Potential Solutions (Section 2, Part 1); Specific Challenges, Potential Solutions, and Variation (Section 2, Part 2); and Data Check Patterns and Additional Data Check Patterns to Ensure Non-Duplicated Counts of All Eligible Exiting Children (Section 3).
Format: Guides, Papers, and Reports
Examining Part C Exiting Data VariationUsing national averages for each of the exiting categories, this white paper helps state personnel examine differences in their Part C Exiting data. The paper explores Part C Exiting data category definitions, as well as general and specific trends in Part C Exiting data. It also includes suggestions for possible strategies to improve data quality, including clarifying policies and definitions, documenting procedures for implementation of policies, and developing training materials related to reporting exiting data.
