Future of education and learning in times of AI

The track welcomes submissions that investigate how AI reshapes teaching, learning, and competence development across universities, professional training environments, and organizational learning ecosystems. We particularly invite contributions that investigate how AI reconfigures pedagogical roles, pedagogical content, redistributes epistemic authority between humans and intelligent systems, and enables new forms of personalised, collaborative, and workplace-integrated learning. Relevant topics include the redesign of curricula and competencies, such as AI literacy, digital judgment, and metacognitive capabilities required for working productively with AI-generated knowledge. The track also welcomes research on AI-supported co-creation of teaching materials, adaptive learning pathways, and hybrid or immersive learning environments. In addition, we invite contributions that explore new assessment approaches addressing the declining reliability of traditional authorship-based evaluation formats. Adopting a socio-technical perspective, the track welcomes submissions that systematically examine how AI reshapes educational systems and organizations in the context of emerging data-driven learning ecosystems that increasingly connect formal education, workplace learning, and digital platforms. Overall, this track provides an opportunity to exchange conceptual ideas and empirical findings. We particularly encourage empirically grounded qualitative and quantitative studies as well as design science research studies that develop and evaluate innovative approaches for integrating AI into teaching and learning practices within socio-technical learning environments.