Human Grokking: Phase Transitions in Semantic Field Saturation

We propose a structural parallel between ML grokking (sudden generalization after prolonged memorization) and human learning in high-density epistemic environments. A 32-node, 91-edge constellation pedagogy spanning physics, mathematics, EE, and RF engineering serves as both the instrument for accelerating the transition and the experimental apparatus for studying it. Five falsifiable predictions are specified.