We present an adaptive learning engine that elevates binary confidence judgments to a primary adaptive signal driving six interdependent subsystems: asymmetric scoring, confidence-modulated spaced repetition, misconception detection via high-confidence errors, review prioritization, multi-factor readiness prediction, and Bloom's-aligned assessment. The engine is deployed across 20 production applications in four professional domains with over 55,000 items. Submitted to AIED ?2026 Late Breaking Results.
Anthony Perry (2026) studied this question.