Measuring the Struggle: Process Friction Traces as Independent Evidence of Genuine Learning in the Age of Generative AI

The Genuine Learning Probability (GLP) framework — a probabilistic, tier-calibrated, ensemble-based methodology specifying seven observable friction components that constitute independent evidence of genuine human learning when artifact-based assessment is decoupled by generative AI. Connects to the Irreducibly Human seven-tier cognitive taxonomy.