📊 Learning Analytics

FlashGenie provides comprehensive learning analytics to help you understand your progress, identify patterns, and optimize your study strategy.

🎯 Core Analytics Framework

FlashGenie's analytics system tracks multiple dimensions of your learning:

graph TD
    A[Learning Activity] --> B[Raw Data Collection]
    B --> C[Metric Calculation]
    C --> D[Pattern Recognition]
    D --> E[Insight Generation]
    E --> F[Recommendations]
    F --> G[Optimized Learning]
    G --> A

📈 Key Performance Metrics

Retention Metrics

Metric	Description	Formula
Retention Rate	Percentage of cards remembered	Correct Answers / Total Reviews
Forgetting Index	Rate of memory decay	Incorrect Answers / Previously Correct
Memory Stability	Consistency of recall	Variance in Retention Rate
Retention Half-life	Time until 50% recall probability	Based on Forgetting Curve

Efficiency Metrics

Metric	Description	Formula
Learning Velocity	Cards learned per study hour	New Cards Mastered / Study Time
Review Efficiency	Time spent per effective review	Total Time / Successful Reviews
Mastery Rate	Speed of reaching mastery	Cards Mastered / Study Sessions
Time to Mastery	Average days to master a card	Sum(Mastery Dates - Introduction Dates) / Cards

Difficulty Metrics

Metric	Description	Formula
Average Difficulty	Mean difficulty of all cards	Sum(Card Difficulties) / Card Count
Difficulty Distribution	Spread of card difficulties	Standard Deviation of Difficulties
Challenge Index	Ratio of difficult cards	Cards with Difficulty > 0.7 / Total Cards
Difficulty Progression	Change in difficulty over time	Slope of Difficulty vs. Time

🔍 Visual Analytics

FlashGenie provides visual representations of your learning data:

1. Learning Curve

# Generate learning curve visualization
python -m flashgenie analytics learning-curve "Spanish Vocabulary"

Shows your mastery progression over time, with projections for future performance.

2. Retention Heat Map

# Generate retention heat map
python -m flashgenie analytics retention-map "Spanish Vocabulary"

Visualizes retention strength across your knowledge base, highlighting strong and weak areas.

3. Study Pattern Analysis

# Analyze study patterns
python -m flashgenie analytics study-patterns --period month

Identifies optimal study times, session durations, and frequency patterns.

4. Knowledge Graph

# Generate knowledge graph
python -m flashgenie analytics knowledge-graph "Spanish Vocabulary"

Creates a visual network of your knowledge, showing connections and clusters.

🧠 Predictive Analytics

FlashGenie uses machine learning to provide predictive insights:

1. Forgetting Prediction

Estimates when you'll forget specific cards based on your review history and performance patterns.

2. Mastery Forecasting

Predicts when you'll reach mastery for cards, topics, or entire decks.

3. Optimal Study Planning

Recommends ideal study schedules based on your learning patterns and goals.

4. Difficulty Forecasting

Anticipates which cards will become easier or more difficult over time.

🔧 Customizing Analytics

Configure analytics to match your learning goals:

# Set mastery threshold
python -m flashgenie config set analytics.mastery_threshold 0.9

# Configure learning velocity calculation
python -m flashgenie config set analytics.velocity_window 14

# Adjust retention calculation method
python -m flashgenie config set analytics.retention_algorithm weighted

# Create custom metrics
python -m flashgenie analytics create-metric "review_efficiency" \
    --formula "total_time / successful_reviews" \
    --unit "seconds/card"

📊 Analytics Dashboard

Access your comprehensive analytics dashboard:

# Open interactive analytics dashboard
python -m flashgenie analytics dashboard

# Generate PDF analytics report
python -m flashgenie analytics report --format pdf --output learning_report.pdf

# Export raw analytics data
python -m flashgenie analytics export --format json --output analytics_data.json

🔍 Learning Insights

FlashGenie automatically generates actionable insights:

1. Strength & Weakness Analysis

# Generate strengths and weaknesses report
python -m flashgenie analytics insights strengths-weaknesses "Spanish Vocabulary"

Identifies your strongest and weakest knowledge areas with specific recommendations.

2. Study Pattern Optimization

# Analyze and optimize study patterns
python -m flashgenie analytics insights study-optimization

Recommends optimal study times, durations, and frequencies based on your performance data.

3. Learning Blockers

# Identify learning blockers
python -m flashgenie analytics insights learning-blockers

Detects persistent challenges and suggests targeted interventions.

4. Mastery Acceleration

# Get mastery acceleration recommendations
python -m flashgenie analytics insights mastery-acceleration

Provides strategies to accelerate your learning velocity.

🧪 Experimental Analytics

FlashGenie includes cutting-edge experimental analytics features:

1. Neural Network Prediction

Uses neural networks to predict future performance with high accuracy.

2. Knowledge Topology Mapping

Creates multi-dimensional maps of your knowledge structure.

3. Cognitive Load Analysis

Estimates cognitive load during study sessions to optimize difficulty.

4. Learning Style Detection

Identifies your optimal learning patterns and preferences.

📱 Mobile Analytics

Access analytics on the go:

# Generate mobile-optimized analytics
python -m flashgenie analytics mobile-summary

# Set up analytics notifications
python -m flashgenie analytics notifications --daily-summary --weekly-insights

🔄 Integration with External Tools

Export analytics to other platforms:

# Export to spreadsheet
python -m flashgenie analytics export --format csv --output spreadsheet.csv

# Export to learning management system
python -m flashgenie analytics export-lms --platform canvas

# Share analytics dashboard
python -m flashgenie analytics share-dashboard --expiry 7d

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Next: Explore Advanced Study Techniques to apply these insights.