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The rapid integration of Generative Artificial Intelligence (GAI) into higher education presents both transformative opportunities and significant pedagogical challenges. While AI tools enhance personalisation, feedback, and creative exploration, they also risk diminishing deep cognitive engagement, ethical responsibility, and authentic authorship. This paper positions engagement as the central mechanism for sustaining meaningful learning in AI-mediated environments through the LEARN framework—Lifelong Learning, Engagement, Active Processing, Reflection, and Neuro-based Design. Drawing on interdisciplinary research from educational psychology, neuroscience, motivation theory, and higher education studies, the paper conceptualises engagement as a multidimensional construct encompassing behavioural, cognitive, emotional, social, and agentic dimensions. The analysis demonstrates that engagement serves as the psychological and neurobiological engine that links motivation, ethical reasoning, metacognition, and sustained learning. Neuroscientific evidence indicates that engaged learning activates attentional networks, dopaminergic reward systems, hippocampal memory consolidation, and prefrontal executive processes—mechanisms essential for deep and durable learning. Within the LEARN framework, engagement enables Active Processing, strengthens Reflection, supports Neuro-based Design, and sustains Lifelong Learning dispositions. The paper further proposes neuroscience-informed assessment redesign strategies that shift from high-stakes performance models toward reflective, formative, and autonomy-supportive practices. Such engagement-centred assessment fosters ethical responsibility, intrinsic motivation, and adaptive expertise in AI-augmented learning contexts. Ultimately, the study argues that engagement is not merely a pedagogical strategy but a neuro-ethical foundation for sustainable higher education in the age of Generative AI.
