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CCWIS Self-Assessment Tools Part Two
The CCWIS Self-Assessment Tools Part Two webinar is part two of a 2-part webinar series on CCWIS technical assistance, self-assessment tools, and monitoring reviews. This webinar will focus on the CCWIS self-assessment tools included in CCWIS Technical Bulletin #7. We will discuss how the tools fit into the larger continuum of CCWIS technical assistance and reviews, the format of the tools, and examples of how title IV-E agencies can use the tools at different stages of CCWIS design and development. Metadata-only record linking to the original dataset. Open original dataset below.
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Lessons Learned: CCWIS Technical Assistance Monitoring Reviews Webinar
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A discussion about lessons learned over the past three years from CCWIS Technical Assistance Monitoring Reviews. This webinar, presented May 31, 2023, covers trends in both strengths and challenges in program and technology identified during reviews. Audio Description Version Metadata-only record linking to the original dataset. Open original dataset below.
CCWIS Technical Assistance and Review Process
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This webinar described the Comprehensive Child Welfare Information System (CCWIS) Technical Assistance Review Process. It began with an overview of the lessons learned from the Statewide Automated Child Welfare Information System (SACWIS) review process. The presentation described the iterative review process and it explains the use of self-assessment tools. As of this presentation, some self-assessment tools were available for public comment and others were in development. Metadata-only record linking to the original dataset. Open original dataset below.
CCWIS Technical Bulletin #2
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This technical bulletin, re-issued on November 9, 2022, provides title IV-E agencies that choose to develop a Comprehensive Child Welfare Information System (CCWIS) with guidance on identifying and collaborating with child welfare contributing agencies (CWCAs), options for data sharing, and related cost allocation requirements. Metadata-only record linking to the original dataset. Open original dataset below.
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