Thematic Pillars and Sub-Themes

Outcome 1: Thematic Pillars and Sub-Themes

SAFIERR-TECH is structured around seven thematic pillars, each designed to produce concrete outputs.

Pillar A: Digital Infrastructure & University Digital Environment

  • Campus connectivity, servers, networks, and data systems
  • Digital labs, software tools, and IT governance
  • Minimum standards and phased upgrade plans

Expected Output: Baseline requirements + investment map for participating universities.

Pillar B: Digital & Blended Learning, OER, and AI in Teaching/Learning

  • Blended learning models and instructional design
  • Digital curricula and open educational resources (OER)
  • AI use cases for learning support, assessment, and analytics

Expected Output: Blended course blueprint + OER priorities + AI-in-teaching guidance.

Pillar C: Faculty Capacity Building and Digital Skills

  • Training tracks for faculty (platforms, assessment, instructional design)
  • Digital competence frameworks and certification pathways

Expected Output: Faculty training plan and capacity framework.

Pillar D: Cybersecurity and Data Governance

  • Data governance, access control, privacy, and protection
  • Cybersecurity baseline and incident response readiness

Expected Output: Baseline cybersecurity and data governance policy pack.

Pillar E: Research, Innovation, and Technology Localization

  • Applied research enablers and scientific resource access
  • Innovation pipelines and technology localization with companies
  • Funding pathways and research support mechanisms

Expected Output: Shortlist of innovation actions + donor-ready pilot concepts.

Pillar F: Partnerships with Digital Economy & Technical Civil Society

  • University–industry cooperation models and labor-market linkages
  • Role of technical civil society in employability and skills development
  • International cooperation and university alliances

Expected Output: Partnership MoU templates + digital economy linkage action plan.

Pillar G: AI in Education and Research

This theme explores applications of artificial intelligence in higher education and scientific research, including support for teaching and learning processes, educational data analysis, and automation of academic and research operations.

It also addresses opportunities, challenges, and ethical as well as regulatory considerations surrounding AI adoption in the university context.