The rapid spread of generative artificial intelligence presents universities with the challenge of continuously developing curricula without being able to wait for long-term accreditation cycles. Traditional, linear models of program development are proving too sluggish for this purpose. This challenge is addressed here, and a step-by-step model for agile curriculum development for AI competences is presented, based on an integrated combination of future skills, subject-specific learning objectives, and curricular framework conditions.
The starting point is the empirically based AI competency model AIComp, which describes key competency requirements for an AI-driven living and working environment. The developed process model systematically translates these abstract competency requirements into course-specific learning objectives, teaching/learning formats, and curricular placements. It is characterized by an iterative, participatory, and experimental approach that allows for small-scale pilot projects within existing structures.
The article combines theoretical concepts from competence and agility research with proven practical formats from universities in Baden-Württemberg. It shows how AI skills can be anchored not as an add-on, but as an integral part of future-oriented curricula.
The rapid development of generative AI poses a challenge for universities: curricula must remain flexible, as traditional models are too slow to adapt. This video shows how universities are integrating AI skills and future skills directly into their degree programs based on the empirical AIComp model—in an iterative, practical, and future-proof manner.
Discover how agile curriculum development is preparing universities for the AI-driven world of work!
Director of the Researchgroup and Professorship for Educational Management and Lifelong Learning
Director of the Researchgroup and Professorship for Educational Management and Lifelong Learning