"Aidemics" examined analytically through the connectivist theory: Institutional AI-mediation in higher education via an artificial intelligence center (CILT-AI)

Abstract

The rapid expansion of artificial intelligence (AI) in higher education has intensified calls for pedagogically grounded approaches to AI education that extend beyond tool adoption and participation metrics. This qualitative case study examines how an institutional AI center (CILT-AI: Center for Innovative Learning and Teaching Artificial Intelligence) mediates educators' learning, experimentation, and professional identity. Rooted in connectivist theory, it views AI-mediated learning as a networked process involving educators (faculty-academics), students, structures, and tools. Analysis includes institutional records (n = 567) and interviews with faculty (n = 40) and students (n = 20$). Rather than treating participation as a proxy for learning, the analysis interrogates how, under what conditions, and for whom engagement in AI-focused initiatives translated into pedagogical change, ethical reflection, and shifts in professional self-understanding. The findings show that networked participation only supports learning through collaborative structures that enable disciplinary translation and sustained experimentation; without this mediation, engagement remains aspirational and symbolic. The study introduces Aidemics as an emergent, ethical professional identity formed through sociomaterial engagement within institutional networks, rather than fixed expertise. By complicating assumptions about connectivist networked learning, this research clarifies the role of institutional AI centers and offers design considerations for AI-mediated learning that prioritize both capacity building and ethical reflexivity.