Embedded Files
The EF+Math Program is committed to high standards that meet or exceed our legal obligations and provide transparency in our processes for the protection of the privacy of all participants in our studies. This page contains guidelines and resources to support awardees in engaging in the ethical treatment of student data. We adopt the motto, “If data are good enough to collect, they’re good enough to protect.”
Key Documents describing EF+Math Policies and Practices for Data Management
Key Documents describing EF+Math Policies and Practices for Data Management
Strategies for Protecting Data Privacy
Strategies for Protecting Data Privacy
Data privacy can be compromised through access in individual-level files, aggregated files, or in sharing of findings in tables. A number of resources are available here to help awardees address de-identification and re-identification.
A Visual Guide to Practical Data De-Identification (Future of Privacy Forum)
LDBase (Florida State University repository):Data De-identification
Coming soon: AERDF Data Environment
Coming soon: AERDF Data Environment
A secure cloud environment is being developed by AERDF and the EF+Math Program for data storage, shared data analysis and collaboration that securely hosts Personally Identifiable Information (PII) and de-identified data.
Until this infrastructure is available, awardees are strongly encouraged to use the following secure and legally compliant platform to store data: Box.
Frequently Asked Questions
Frequently Asked Questions
Check back soon for FAQs.
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