The Third-Party Access Effect: An Overlooked Challenge in Secondary Use of Educational Real-World Data

2026-01-30

AI Summary

This study addresses how privacy protection measures in the sharing of educational empirical data can inadvertently introduce undetected biases that compromise the validity of secondary analyses. It introduces, for the first time, the concept of the “Third-Party Access Effect” (3PAE), which elucidates how communicating re-identification risks alters learners’ behaviors and consequently shifts data distributions. Integrating re-identification risk assessment, user privacy behavior surveys, and sensitivity analysis, the research demonstrates that informing participants about re-identification risks significantly increases their likelihood of withdrawing or withholding information, thereby undermining the reliability of downstream analytical conclusions. By uncovering this implicit linkage between privacy practices and data validity, the work offers a novel perspective for the governance of educational data.

Technology Category

• Machine Learning: Privacy
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Application Domains: Humanities & Computational Social Science

Application Category

• Security and Privacy: Data transparency and provenance
• Responsible Web: Data and user privacy-enhancing technologies for the Web
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

Secondary use of growing real-world data (RWD) in education offers significant opportunities for research, yet privacy practices intended to enable third-party access to such RWD are rarely evaluated for their implications for downstream analyses. As a result, potential problems introduced by otherwise standard privacy practices may remain unnoticed. To address this gap, we investigate potential issues arising from common practices by assessing (1) the re-identification risk of fine-grained RWD, (2) how communicating such risks influences learners'privacy behaviour, and (3) the sensitivity of downstream analytical conclusions to resulting changes in the data. We focus on these practices because re-identification risk and stakeholder communication can jointly influence the data shared with third parties. We find that substantial re-identification risk in RWD, when communicated to stakeholders, can induce opt-outs and non-self-disclosure behaviours. Sensitivity analysis demonstrates that these behavioural changes can meaningfully alter the shared data, limiting validity of secondary-use findings. We conceptualise this phenomenon as the third-party access effect (3PAE) and discuss implications for trustworthy secondary use of educational RWD.

Problem

• real-world data
• third-party access
• re-identification risk
• secondary use
• privacy behaviour

Innovation

• third-party access effect
• real-world data
• re-identification risk
• privacy behavior
• sensitivity analysis