Artificial intimacy: Generation Z behaviors that affect learning in higher education and what do teachers need to know

Abstract

This article discusses an emerging challenge for teaching in higher education when dealing with Generation Z students, whose executive neurocontrol networks have been modulated by the intense and prolonged use of connected devices, digital platforms, and social media, creating situations of active Artificial Intimacy. This is an interdisciplinary narrative review that articulates evidence from the neuroscience of learning, studies on technological addiction, and recent data on academic performance in order to understand how these hyperstimulating environments reconfigure reward, attention, memory, motivation, and self-regulation circuits in university students. The synthesis of the literature allows us to characterize six recurring behavioral patterns in classrooms: low tolerance for frustration, isolation in algorithmic “bubbles,” preference for parasocial interactions, continuous search for quick external validation, appreciation of apparent performance, and attention jumps in multitasking. Each pattern is analyzed in light of Ausubel's Meaningful Learning, Goleman's Emotional Intelligence, and Dweck's Growth Mindset, highlighting impacts on conceptual depth, empathy, social skills, perseverance, and willingness to face educational challenges. Based on this integrated reading, the work proposes solutions in the curation of learning paths mediated by generative AI, conceived as neurodidactic strategies to intentionally modulate such patterns in face-to-face and hybrid experiences. By treating Artificial Intimacy as a key to explaining Generation Z behaviors and, simultaneously, as an axis for designing educational interventions with AI, the study inaugurates a conceptual and practical framework in the literature on Higher Education, offering teachers a structured repertoire for reorganizing professional training in contexts permeated by algorithms.