Cognitive Efficiency

Efficiency = (Correctness × Confidence) / Time

time_efficiency = {
    "fast_correct": 25,      # <30s, correct
    "moderate_correct": 15,  # 30-60s, correct
    "slow_correct": 10,      # >60s, correct
    "incorrect": 0           # Any time, wrong
}

confidence_alignment = {
    "high_conf_correct": 1.0,      # Confident and right
    "low_conf_correct": 0.6,       # Uncertain but right
    "high_conf_wrong": 0.0,        # Confident but wrong
    "low_conf_wrong": 0.2          # Uncertain and wrong
}

efficiency_trend = {
    "current_efficiency": 0.75,
    "trend_7_days": "improving",
    "trend_30_days": "stable",
    "peak_efficiency": 0.85
}

from cognition_engine import CognitionEngine

engine = CognitionEngine(supabase_url, supabase_key)

# Get efficiency metrics
efficiency = await engine.get_cognitive_efficiency("student_123")

print(f"Overall efficiency: {efficiency['overall_efficiency']:.2f}")
print(f"Time efficiency: {efficiency['time_efficiency']:.2f}")
print(f"Trend: {efficiency['efficiency_trend']}")

skill_efficiency = {
    "algebra": 0.85,        # Strong efficiency
    "geometry": 0.72,       # Good efficiency
    "trigonometry": 0.45,   # Low efficiency - needs attention
    "statistics": 0.78      # Good efficiency
}

# Identify skills needing improvement
weak_skills = [skill for skill, eff in skill_efficiency.items() 
               if eff < 0.60]
print(f"Skills to focus on: {weak_skills}")

if efficiency['cognitive_load_warning']:
    print("High cognitive load detected")
    print("Recommendations:")
    print("- Reduce session length")
    print("- Lower difficulty temporarily")
    print("- Increase breaks between problems")

snapshot = await engine.create_performance_snapshot("student_123")

efficiency_profile = {
    "overall_efficiency": 0.75,
    "cognitive_efficiency_score": 0.68,
    "time_efficiency": 0.82,
    "confidence_accuracy": 0.91,
    "peak_performance_time": "morning",
    "cognitive_load": "moderate"
}