|Title:||Statistical Methods for Protecting Personally Identifiable Information in Aggregate Reporting|
|Description:||This Statewide Longitudinal Data Systems (SLDS) Technical Brief examines what protecting student privacy means in a reporting context. To protect a student’s privacy, the student’s personally identifiable information must be protected from public release. When schools, districts, or states publish reports on students’ educational progress, they typically release aggregated data—data for groups of students—to prevent disclosure of information about an individual. However, even with aggregation, unintended disclosures of personally identifiable information may occur. 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 also illustrates that some practices work better than others in protecting against disclosures of personally identifiable information about individual students. Each data protection practice requires some loss of information. The challenge rests in identifying practices that protect information about individual students, while at the same time minimizing the negative impact on the utility of the publicly reported data. Drawing upon the review and analysis of current practices, 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. These reporting rules are intended to maximize the amount of detail that can be safely reported without allowing disclosures from student outcome measures that are based on small numbers of students.
NCES welcomes comments on the recommended reporting rules.
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|Cover Date:||December 2010|
|Web Release:||December 21, 2010|
|Publication #:||NCES 2011603
|Type of Product:||Technical/Methodological Report|
Statewide Longitudinal Data Systems Grant Program (SLDS)
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