Learning Velocity Tracking.md - himent12/FlashGenie GitHub Wiki
๐ Learning Velocity Tracking
FlashGenie's Learning Velocity Tracking provides predictive analytics to forecast your mastery timeline and optimize your learning efficiency.
๐ฏ What is Learning Velocity?
Learning Velocity measures how quickly you're progressing through your learning material. It tracks:
- Cards per day - How many cards you're processing
- Mastery rate - Percentage of cards you've mastered
- Retention curve - How well you retain information over time
- Efficiency factor - How efficiently you're learning compared to optimal patterns
๐ Key Metrics
Velocity Indicators
FlashGenie tracks several key velocity indicators:
Metric | Description | Ideal Range |
---|---|---|
Cards/Hour | Cards processed per hour of study | 15-30 |
Mastery Rate | Percentage of mastered cards | Steady increase |
Retention Score | How well you retain over time | 0.7-0.9 |
Learning Efficiency | Actual vs. optimal learning | 0.6-1.0 |
Mastery Prediction
# Predict mastery timeline
python -m flashgenie velocity "Spanish Vocabulary" --predict
Sample output:
Current mastery: 43% (86/200 cards)
Predicted 80% mastery: 14 days (ยฑ2 days)
Predicted 95% mastery: 31 days (ยฑ4 days)
Confidence interval: 85%
๐ Using Learning Velocity Tracking
Basic Usage
# View basic velocity metrics
python -m flashgenie velocity "Spanish Vocabulary"
Advanced Analysis
# Comprehensive velocity analysis with predictions
python -m flashgenie velocity "Biology" \
--predict \
--confidence-interval 0.95 \
--lookahead-days 60 \
--chart
Available Parameters
Parameter | Description | Example |
---|---|---|
--predict |
Enable prediction mode | --predict |
--confidence-interval |
Statistical confidence | --confidence-interval 0.9 |
--lookahead-days |
Prediction horizon | --lookahead-days 30 |
--chart |
Generate visual chart | --chart |
--export |
Export data | --export velocity.json |
๐ Visualizing Your Progress
FlashGenie provides several visualization options:
# Generate velocity chart
python -m flashgenie velocity "Spanish" --chart --export chart.html
# View learning curve
python -m flashgenie velocity "Spanish" --learning-curve
# Compare multiple decks
python -m flashgenie velocity "Spanish" "French" "Italian" --compare
๐งช The Science Behind It
Learning Velocity Tracking is based on:
- Ebbinghaus Forgetting Curve - Mathematical model of memory decay
- Spaced Repetition Optimization - Ideal review intervals
- Bayesian Prediction Models - Statistical forecasting with uncertainty
- Learning Efficiency Metrics - Comparative performance analysis
๐ฎ Predictive Features
Mastery Timeline
Predicts when you'll reach specific mastery levels:
# Predict days to reach 90% mastery
python -m flashgenie predict mastery-timeline \
--deck "Spanish Vocabulary" \
--target 0.9
Study Requirements
Forecasts study time needed to reach goals:
# Predict study time required for mastery
python -m flashgenie predict study-time \
--deck "Biology" \
--target 0.95 \
--by-date "2023-12-31"
Struggling Card Prediction
Identifies cards you're likely to struggle with:
# Predict potentially difficult cards
python -m flashgenie predict struggling-cards \
--deck "Physics" \
--threshold 0.7
๐ฏ Optimizing Your Learning Path
FlashGenie can recommend optimal learning paths:
# Get recommended learning paths
python -m flashgenie recommend-paths \
--deck "Spanish Vocabulary" \
--available-time 30 \
--days-per-week 5
Sample output:
Recommended Learning Paths:
1. Conservative (95% confidence): 20 min/day, 5 days/week, 8 weeks
2. Balanced (80% confidence): 30 min/day, 5 days/week, 6 weeks
3. Aggressive (60% confidence): 45 min/day, 5 days/week, 4 weeks
๐ Tracking Long-Term Progress
Monitor your learning velocity over time:
# View velocity trends
python -m flashgenie velocity-trends \
--deck "Spanish Vocabulary" \
--period 90
๐ฏ Tips for Improving Learning Velocity
- Consistent daily practice - Even 10-15 minutes daily is better than occasional long sessions
- Focus on struggling cards - Target cards with low retention scores
- Optimize study environment - Minimize distractions during study
- Use memory techniques - Mnemonics and visualization improve retention
- Follow optimal break schedules - Take breaks at recommended intervals
๐ Next Steps
- Adaptive Study Sessions - Optimize your study sessions
- Contextual Learning Engine - Adapt to your environment
- Performance Analytics - Dive deeper into your learning data
FlashGenie v1.5.0 | Last updated: June 2025