TEACHING STRATEGIES FOR AI COMPETENCE DEVELOPMENT

Artificial intelligence (AI) will play an increasingly significant role in shaping the future. As it becomes more ubiquitous and pervasive, it will fundamentally transform industries, redefine professional roles, and demand new competences for individuals to engage with it in a critical, reliable and creative way. Equipping students with AI competences should therefore be a strategic priority for educators.

The paper aims to explore effective strategies for integrating AI competence development into teaching methodologies. The research was conducted through an iterative dialogue with various large language models (LLMs), posing a series of targeted questions to examine how AI can enhance the teaching and learning process. This approach allowed for the generation of diverse insights on how the development of AI competences can be supported. The findings were then validated in a workshop with university professors, where participants critically examined the proposed strategies, discussed their applicability in real-world teaching scenarios, and provided feedback on how AI can be effectively integrated into curriculum design and pedagogy.

A central contribution of the study is the development of an assessment strategy to evaluate the acquisition of AI competencies, encompassing values, knowledge, and skills essential for a comprehensive engagement with AI.