עקרון: Run ML clustering on all metrics. Discover natural subgroups. Auto-match to interventions.
🎯 Discovered Phenotypic Clusters:
High-Motivation, Low-Persistence
Best Intervention: Peer-based games (social motivation sustains effort)
Working Memory + Social Anxiety
Best Intervention: Solo tasks first, then group practice
Impulsive + High-Novelty
Best Intervention: Frequent reward rotation, variable schedules
Methodical + Perfectionist
Best Intervention: Error normalization, growth mindset messaging
✅ Cluster Match Found:
High-Motivation, Low-Persistence - This cluster responds 2x better better to peer-collaborative games. Solo games → dropout risk.
💡 ML Advantage:
Humans would miss the "social motivation sustains effort" pattern. ML finds it automatically by clustering on >50 metrics.
