learning analytics.md - himent12/FlashGenie GitHub Wiki
FlashGenie provides comprehensive learning analytics to help you understand your progress, identify patterns, and optimize your study strategy.
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
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 |
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 |
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 |
FlashGenie provides visual representations of your learning data:
# Generate learning curve visualization
python -m flashgenie analytics learning-curve "Spanish Vocabulary"
Shows your mastery progression over time, with projections for future performance.
# Generate retention heat map
python -m flashgenie analytics retention-map "Spanish Vocabulary"
Visualizes retention strength across your knowledge base, highlighting strong and weak areas.
# Analyze study patterns
python -m flashgenie analytics study-patterns --period month
Identifies optimal study times, session durations, and frequency patterns.
# Generate knowledge graph
python -m flashgenie analytics knowledge-graph "Spanish Vocabulary"
Creates a visual network of your knowledge, showing connections and clusters.
FlashGenie uses machine learning to provide predictive insights:
Estimates when you'll forget specific cards based on your review history and performance patterns.
Predicts when you'll reach mastery for cards, topics, or entire decks.
Recommends ideal study schedules based on your learning patterns and goals.
Anticipates which cards will become easier or more difficult over time.
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"
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
FlashGenie automatically generates actionable insights:
# Generate strengths and weaknesses report
python -m flashgenie analytics insights strengths-weaknesses "Spanish Vocabulary"
Identifies your strongest and weakest knowledge areas with specific recommendations.
# Analyze and optimize study patterns
python -m flashgenie analytics insights study-optimization
Recommends optimal study times, durations, and frequencies based on your performance data.
# Identify learning blockers
python -m flashgenie analytics insights learning-blockers
Detects persistent challenges and suggests targeted interventions.
# Get mastery acceleration recommendations
python -m flashgenie analytics insights mastery-acceleration
Provides strategies to accelerate your learning velocity.
FlashGenie includes cutting-edge experimental analytics features:
Uses neural networks to predict future performance with high accuracy.
Creates multi-dimensional maps of your knowledge structure.
Estimates cognitive load during study sessions to optimize difficulty.
Identifies your optimal learning patterns and preferences.
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
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
Next: Explore Advanced Study Techniques to apply these insights.