16:30 - 17:30
Parallel sessions 6
16:30 - 17:30
Location: Room 249
The last presenter of the session is kindly asked to take over the moderation of the session helping to keep the time.
Each presenter is invited to use up to 15 min for presentation and up to 5 min for Q&A.
Submission 172
Embedding AI Competence into the Curriculum:The ADM-AI Model for European Higher Education
Presented by: Julia Marcia Mann
Ulf-Daniel Ehlers 1, 2Julia Marcia Mann 1, 2
1 DHBW Karlsruhe
2 NextEducation

Artificial intelligence is reshaping disciplinary practices and academic work, moving higher education beyond technical adoption towards human–AI collaboration as a core graduate capability. This raises a central challenge: how can AI-related human competences be systematically integrated into teaching and learning in ways that foster future-ready skills, while aligning pedagogical transformation with evolving teaching roles and institutional governance?

This paper introduces the Agile Curriculum Development Model (ADM-AI), a governance-compatible framework for systematically integrating AI-related human competences into higher education programmes. Its core contribution is to address the implementation gap between AI competence frameworks and programme-level curriculum transformation under formal higher education governance conditions. The model combines competence clarification, constructive alignment, curriculum mapping, and iterative implementation cycles, enabling continuous curriculum transformation within Bologna-type systems. AIComp serves as a conceptual starting point, providing an empirically grounded competence framework that defines AI competence as a multidimensional capacity for reflective, ethical, and collaborative engagement with AI. The model conceptualises curriculum transformation as a multi-level process linking institutional strategy, programme design, and pedagogical practice.

AI competences are enacted in situated learning environments where learners engage with AI systems as partners in inquiry, problem-solving, and knowledge construction, accompanied by a shift in academic roles towards learning design and facilitation. The model enables embedded, iterative innovation and positions implementation as institutional learning, offering a scalable approach to curriculum transformation in AI-mediated higher education.