LA researchers and practitioners should adapt to changing regulations across jurisdictions, use regulatory sandboxes, and carefully consider data nature and privacy risks before cross-border data transfer¶

Strategy · All strategies
Evidence · no claims cited

Description¶

This strategy is the authors' forward-looking recommendation from their comparative policy analysis of AI regulation. As regulations shift, they argue that "researchers and practitioners must adapt to changing regulations across international boundaries" and use regulatory sandboxes to minimize risks for learners and developers. Because certain data types such as biometric sensors may become difficult to use for education under strict guidelines, particularly within the EU, the nature of the data and its privacy risks must be considered before transferring data across jurisdictions.

Design Implications¶

Context¶

Requirements¶

• Researchers and institutional leaders must stay updated and comply with global AI regulations to ensure legality and minimize risks

Constraints¶

• Strict guidelines, particularly within the EU, may make certain data types such as biometric sensors challenging to use for education

Target Learners¶

• Learning analytics researchers
• AI system developers
• Educational institution leaders

Target Learning Goals¶

• Designing and deploying ethical and legally compliant AI-driven learning analytics systems across changing regulatory environments

Related Strategies¶

• AI system developers should ensure human-centric design, institutional leaders should stay updated on global AI regulations, and LA experts should engage policymakers through dialogue
• Privacy-preserving deployment measures for an ITS under GDPR and EU AI Act

Examples¶

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Key Sources¶

• Kaliisa, R., Baker, R. S., Wasson, B., & Prinsloo, P. (2025). The Coming but Uneven Storm: How AI Regulation Will Impact AI and Learning Analytics Research in Different Countries. Journal of Learning Analytics, 12(2). https://doi.org/10.18608/jla.2025.8495