student-personalization

Audit adaptive learning and student personalization systems for pedagogical quality. Use when you need to evaluate learning path algorithms (branching, remediation, acceleration), mastery detection models (Bayesian, IRT, threshold-based), knowledge graph prerequisite accuracy, recommendation engine fairness and bias, spaced repetition and interleaving, WCAG 2.1 AA and Section 508 accessibility compliance, IEP/504 accommodation implementation, xAPI/SCORM/LTI data integration, or teacher/student/admin analytics dashboards. Covers platforms like Knewton, DreamBox, ALEKS, IXL, Khan Academy, and custom adaptive systems.