Core EU Principles for Digital Transformation in Higher Education Institutions: Governance, Trust, and Interoperability
Core EU Principles for Digital Transformation in Higher Education Institutions: Governance, Trust, and Interoperability
Ellana Molchanova
TLDR
The article systematizes core EU principles relevant to digital transformation in HEIs and translates them into actionable governance requirements that connect governance, trust, and interoperability that are applicable to HEIs.
Abstract
Digital transformation has become a structural condition of higher education because HEIs increasingly depend on platforms and data infrastructures for teaching, assessment, mobility workflows, and institutional decision-making, while simultaneously facing heightened legal, ethical, and operational exposure. The article systematizes core EU principles relevant to digital transformation in HEIs and translates them into actionable governance requirements that connect governance, trust, and interoperability. A structured documentary analysis is applied to EU strategies, binding legal acts, and implementation-oriented frameworks. Qualitative coding is used to derive principle categories and map each category to institutional controls across the lifecycle of selection, deployment, use, monitoring, and retirement. The analysis shows that EU principles become operational in HEIs only when expressed as auditable controls with ownership and indicators. Core requirements include evidence-based adoption for educational value, accessibility as a release gate, GDPR-aligned minimization and DPIA routines, NIS2-aligned cybersecurity risk management, standards-based interoperability, mobility and credential portability governance, and risk-based AI governance under the AI Act. Digital transformation should be governed as socio-technical change where compliance and quality are properties of systems in use, not merely systems purchased. Future work should validate governance indicators across diverse HEI types, test maturity models against outcomes, and examine how interoperability, privacy, and AI oversight can be co-optimized without increasing administrative burden.
