AI4Gov-X Evaluation & Certification Framework
The AI4Gov-X Evaluation and Certification Framework defines the system through which learners’ competences are assessed, validated, and recognised across all educational activities of the AI4GovAccelerate programme. Developed under WP2 – Programme Preparation Activities, the framework aligns with ISO 21001:2025 and introduces a coherent, transparent, and auditable approach to competence-based evaluation.
Although the full document is restricted, this public summary outlines its core components.
A Competence-Based Evaluation System
The framework adopts a competence-oriented approach grounded in the EMC³ methodology, ensuring that Intended Learning Outcomes (ILOs) are directly linked to observable performance criteria. Evaluation is based on:
- Structured competence matrices
- Clear indicators and rubrics
- Evidence-based assessment
- Traceable and auditable records
This ensures comparability across institutions and learning formats.
Integration with ISO 21001
The framework translates ISO 21001 requirements into operational processes for:
- Designing learning outcomes
- Delivering training modules
- Evaluating competences
- Issuing credentials
- Monitoring quality and ensuring continual improvement
A full Plan-Do-Check-Act (PDCA) cycle is embedded to guarantee reliability and transparency.
Recognition Pathways
Learners may receive:
- ECTS-based recognition (through participating universities)
- Micro-credentials issued as Open Badge 3.0 digital awards
- Certificates for short learning activities
All credentials are issued through a unified Central Evaluation & Credentialing Unit (CECU).
Digital Credentialing Architecture
The system is built on:
- Open Badge 3.0
- W3C Verifiable Credentials 2.0
- A secure Skill Wallet for learners
- LMS-based validation and automated issuance
- Optional external visibility (LinkedIn, Europass)