Secure enclaves for privacy-protecting researcher access to student-level data¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article recommends engineering better data access through secure enclaves: the Kinetic team "is developing a secure enclave, which would allow researchers privacy-protecting access to student-level information to run their analyses virtually without exposing the underlying data." This approach is described as of great interest to those with equity-relevant research questions, addressing the tension between equity-relevant research and open science.

Design Implications¶

Context¶

Requirements¶

• Analyses must run virtually inside the enclave without exposing underlying data

Constraints¶

• Navigating FERPA, GDPR, and department-specific review processes raises administrative and technical challenges

Target Learners¶

• Higher education students whose institutional data is analyzed

Target Learning Goals¶

• Enabling equity-relevant research while protecting student privacy

Related Strategies¶

• Co-design and validate context-aware AI through DBIR blended with user-centered design in privacy-preserving enclaves
• Privacy-preserving deployment measures for an ITS under GDPR and EU AI Act

Examples¶

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Key Sources¶

• Schellinger, A., & Roschelle, J. (2024, January). Looking Back to Move Forward. Digital Promise. https://doi.org/10.51388/20.500.12265/203