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Competency-Based Learning: Mastery Skill Tree

This simulation demonstrates competency-based learning principles with a real Bayesian Knowledge Tracing model driving progression. Eleven competencies sit in a prerequisite graph across four tiers — foundation skills, applied skills, integrative skills and a capstone. A competency only becomes practisable once every prerequisite beneath it is mastered, exactly as a mastery-based curriculum gates advancement on demonstrated skill rather than time spent. Practising a node runs a probabilistic attempt scored by slip and guess parameters, then updates a live mastery estimate with the same Bayes-rule update real intelligent tutoring systems use, so you can see how learning rate, slip and guess reshape how quickly — and how reliably — a learner clears the mastery bar and unlocks the next stage.