This edited collection consolidates interdisciplinary research on artificial intelligence in higher education, foregrounding pedagogical practices across the social and hard sciences. While some chapters address generative AI, the volume intentionally adopts a broader AI lens to capture wider perspectives. Positioned as a timely interdisciplinary synthesis, the volume brings together research on the role of AI in teaching and learning in higher education. It balances chapters on generative AI with broader examinations of AI, ensuring that a range of perspectives are represented. By assembling insights from the social and hard sciences, the collection charts how pedagogical practices are being reconsidered, highlights convergences and contrasts across disciplines, and delineates open questions. Addressing a gap in the literature, it offers an integrated view of AI’s educational impact from multiple disciplinary vantage points, providing readers with a structured foundation for interdisciplinary understanding. This book will be invaluable for academics, educators and researchers in higher education, across the social and hard sciences, who are seeking interdisciplinary insight into the pedagogical implications of AI.
