Research Summary: ReLEAF: A Socio-Technical Framework Bridging Custodians and Researchers for Trustworthy Data Sharing

Educational real-world data (ERWD) collection is expanding rapidly, presenting significant research opportunities for the Learning Analytics community. However, ethical, regulatory, and governance constraints severely limit data access. The ReLEAF framework is proposed to bridge data custodians and researchers by operationalizing a two-stage data sharing model, focusing on practical implementation beyond just anonymization techniques.

Why it matters

The ability to effectively share and utilize educational real-world data is critical for advancing research and improving learning outcomes. Addressing the current limitations in data access through structured frameworks like ReLEAF can unlock significant analytical potential while upholding privacy and ethical standards.

Key insights

• Growing volumes of educational real-world data are being collected across various learning platforms and institutional systems.
• Access to this data for research purposes is significantly limited due to ethical, regulatory, and governance constraints.
• Prior approaches primarily focused on anonymization, overlooking the practical operational design for data sharing interactions between custodians and researchers.
• The ReLEAF framework offers a socio-technical solution designed to bridge data custodians and researchers.
• The framework operationalizes a two-stage data sharing process, explicitly mentioning differentially private synthetic data in its initial stage.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2610.02720