Archived Resources

The presentation addresses the value of IDEA data managers and staff working with data from systems integrated with general education and early learning programs. Viewers can learn how integrated data can support the SSIP to provide a comprehensive integrated view of children/students, schools, and programs to improve outcomes for children and their families. A helpful handout is included.

This SLDS Technical Brief examines what protecting student privacy means in a reporting context. Current reporting practices are described and each is accompanied by an example table that is used to consider whether the intended protections are successful. The Brief illustrates that some practices work better than others in protecting against disclosures of personally identifiable information about individual students. The Brief concludes with a set of recommended reporting rules that can be applied in reports of percentages and rates that are used to describe student outcomes to the public.

This presentation provides an overview of definitions, confidentiality provisions, and the latest regulatory changes under the FERPA and Part B of the IDEA. The presentation highlights similarities and differences in the requirements between the two statues.

The presentation reviews information on evidence-based strategies and practices to support improvement in mathematics. Helpful handouts are included.

This presentation hosted by CIID highlights successful practices to mitigate privacy concerns which emerge during integration of IDEA data.

The webinar focused on a national overview of state’s Phase I SSIP based on the SSIP content analysis that TA providers completed in summer of 2015. DaSy, ECTA, IDC, and NCSI co-sponsored the webinar. Several early childhood colleagues shared the results of the SSIP content analysis.

The presentation provides strategies for making predictions of the ways in which improvements in data quality will impact the summary statements and describes different ways to impact and measure changes in data quality over time. This can help states currently struggling to predict how improvements in data quality will impact the value of the summary statements describing child outcomes. Helpful handouts are included.