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 57 - 63 of 76
Format: Presentations
Building a Strong SSIP Using Implementation DriversImplementation Drivers are the key components of capacity and the functional infrastructure supports that enable a program’s success. The presentation highlights the three categories of implementation drivers (competency, organization, and leadership). An additional focus is on how these drivers support the development of an implementation plan that will result in positive student outcomes. Helpful handouts are included.
Format: Presentations
Moving From Theory to Action - MichiganThis state presentation describes Michigan's SIMR, Theory of Action, and approach to implementation.
Format: Presentations
Moving From Theory to Action - LouisianaThis state presentation describes Louisiana's SIMR, Theory of Action, and approach to implementation.
Format: Presentations
Moving From Theory to Action - PennsylvaniaThis state presentation describes Pennsylvania's SIMR, Theory of Action, and approach to implementation.
Format: Presentations
Understanding Data Quality in the Context of the State Systemic Improvement PlanDuring this session, the presenter applied IDC’s working principles of high-quality data to the SSIP. The presenter focused on applying the principles of data quality at each step in the SSIP evaluation.
Format: Presentations
Moving From Theory to Action - New JerseyThis state presentation describes New Jersey's SIMR, Theory of Action, and approach to implementation.
Format: Presentations
Assessing and Improving Your SSIP Data Quality to Support Your ResultsThis workshop engaged participants in identifying data quality issues that interfere with assessing progress in SSIP implementation and improvement toward the SiMR. A facilitated discussion focused on strategies for improving data quality to support decisionmaking and achievement of results.
