Generative Artificial Intelligence and Encounters with Knowledge in STEM Higher Education Curricula

Generative artificial intelligence has garnered significant interest in higher education, with growing concerns about its consequences for teaching, learning, and assessment. Educators are now faced with the task of adopting genAI into curricula in ways that are responsive to both the short- and long-term effects of this technological disruption on learning. This study considers these effects, focusing on the impacts of genAI on the intrinsic value of learning and its influences on shaping transformative encounters with knowledge in STEM curricula. The implications of incorporating genAI into outcomes and assessment tasks are examined using a constructivist approach based on taxonomies of cognitive skills involved in learning and STEM competency development namely, Bloom's and SOLO taxonomies, and Luckett's knowledge planes. The study offers insights into how the incorporation of genAI may influence conceptual knowledge building and the development of certain STEM graduate attributes and makes recommendations for teachers of STEM curricula.