Archived Resources

The presentation focuses on the key aspects of planning for evaluation of the SSIP. Highlighted information includes the purpose of evaluation, setting the state for evaluation, the importance of focusing on outcomes, evaluation logic, and planning. Helpful handouts are included.

This document provides a list of recommended existing resources for state Part C and Part B 619 staff and TA providers to use to support evaluation planning for program improvement efforts including the SSIP. The document focuses on resources that are more relevant to evaluation and evaluation planning for early intervention and preschool special education.

Selection of a cohort, or Transformation Zone, for SSIP implementation is a principle consideration in developing an action plan. The presentation addresses variables that states should considered in making those decisions and provides information on methods to determine readiness and eliciting involvement of an LEA/EIS.

The Part C Exiting Toolkit allows for one-stop “shopping” for Part C data managers and coordinators. It provides (1) resources for documenting the exiting process, (2) resources to check exiting data, (3) a link to the Part C Exiting Counts app, and (4) other great resources. It is a great tool for both new and experienced staff.

The presentation presents an overview on developing an infrastructure that supports implementation, scale-up, and sustainability of effective practices and highlights core components of implementation. Highlighted components include: Implementation Stages, Implementation Drivers, Implementation Teams, Usable Interventions, and Improvement Cycles.

The 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.

This 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