Why Competence Models Cannot Simply Be “Implemented” - but need a transformative approach?! Competence frameworks are not plug-and-play instruments.
Laura Eigbrecht, academic researcher at the NextEducation research group at DHBW Karlsruhe, is working in several initiatives on Future Skills and Future Teaching – one of them the recently launched EU initiative DEAL with Digital WBL. Here, she can connect her research on digitalisation and Future Skills with the subject of work-based learning. In this article, Laura will give an insight into the DEAL with WBL project with a focus on how to involve teachers and trainers at DHBW and other institutions to create nothing less than a Future Teaching Competence Framework!
Generative AI is already transforming learning practices in VET and higher education. But one crucial question remains unanswered: Are we helping learners develop real AI competences – or are we simply teaching them how to use tools? In my new article, inspired by the OECD Digital Education Outlook 2026, I argue that the future of education depends on a clear shift: from AI use → to AI competence.
Artificial intelligence excels at what it is designed to do — optimize, predict, and correlate. It recognizes patterns at speeds no human can match. And yet, in this very perfection lies its limitation. Algorithms do not doubt, question, or resist. They process the world; they do not interpret it. That difference isn’t a technical gap. It is the essence of being human.