Summary
Lots of systems explain what skills people should have to work well with digital tools, but knowing rules doesn't always mean you can use them in real life. The authors compare popular skill guides like DigComp and UNESCO's frameworks with the International Digital Driving License (IDDL), which tests how people actually behave when handling digital tasks. The IDDL not only checks if someone knows digital stuff but also if they can show it in real situations and explain their choices. This helps to better understand someone's true digital abilities, especially when using artificial intelligence.
What this means in practice
- •For corporate training teams: Design employee certification programs that measure real-world digital task performance, not just knowledge of digital concepts.
- •For cybersecurity compliance auditors: Use behavioral assessments like IDDL to verify actual cybersecurity awareness in staff beyond theoretical training standards.
A position paper. It proposes an approach and reports no results.
Abstract
Digital competence frameworks define the knowledge, skills, attitudes and values required for participation in digital society. The European Digital Competence Framework for Citizens (DigComp) and UNESCO digital literacy and artificial intelligence competency frameworks provide reference structures for policy, curriculum and competency development. The growth of generative and agentic AI raises a further question: does knowing what constitutes competent digital behaviour provide sufficient evidence that an individual can act competently in an authentic digital situation? This conceptual paper addresses that question through a comparative analysis of DigComp, UNESCO Digital Literacy Global Framework, UNESCO AI Competency Framework for Students, and the International Digital Driving License (IDDL). Rather than treating these frameworks as competing models, the paper distinguishes their functions. DigComp and UNESCO primarily define what individuals should know, understand, value and be able to do. IDDL addresses the subsequent evidentiary problem by assessing digital capability through behaviour observed during authentic digital tasks. Its Knowledge-Capability-Reflection model distinguishes knowing what should be done, demonstrating the required behaviour, and explaining the judgement behind it. IDDL integrates Digital Skills, Cybersecurity Awareness and AI Competency, and extends assessment to human agency under AI delegation. The paper distinguishes defined competence from demonstrated capability and positions IDDL as an interoperable behavioural assessment and certification layer that can operate downstream of international competency frameworks.