Nested Learning in Higher Education_Data

Data sources included EEG (P300) signals, interaction logs, self-report measures of self-regulated learning, emotional experience and ethical concerns, and semi-structured interviews. In the lab phase, P300 dynamics aligned with key instructional events, providing preliminary evidence that the neuro-adaptive pipeline is sensitive enough to justify larger-scale studies. In the field phase, 87% of students reported higher engagement and 73% perceived improved learning outcomes, while qualitative data highlighted greater clarity, adaptive support and cognitive safety, alongside concerns about privacy and data sovereignty.

Perceived Nested Learning and neuro-adaptive adjustments were moderately associated with enhanced self-regulatory strategies (correlations up to r = 0.57, p < 0.001). We argue that, under robust ethical, data-protection and sustainability frameworks, Nested Learning can strengthen academic resilience, learner autonomy and human-centred uses of AI in higher education.