🌐 Contextual Learning Engine

FlashGenie's Contextual Learning Engine dynamically adapts your learning experience based on your environment, device, and attention level.

🎯 What is the Contextual Learning Engine?

The Contextual Learning Engine is an AI system that automatically adjusts:

• Question presentation - How cards are displayed
• Interaction methods - How you respond to questions
• Difficulty progression - Challenge level adaptation
• Session structure - Organization of study time
• Content selection - Which cards to show when

Based on contextual factors including:

• Environment - Where you're studying
• Device - What you're using to study
• Time of day - When you're studying
• Attention level - How focused you are
• Energy level - How mentally fresh you are

💡 Key Features

Environment Detection

FlashGenie detects and adapts to different environments:

Environment	Adaptations
Quiet Home	Deeper content, complex interactions
Noisy Public	Visual emphasis, simplified responses
Commuting	Audio focus, brief interactions
Workplace	Professional content priority, timed sessions
Bed	Relaxed pacing, reduced brightness

Device Optimization

# Study optimized for smartphone
python -m flashgenie quiz --device smartphone

FlashGenie adapts to different devices:

• Desktop/Laptop - Full-featured interface, keyboard shortcuts
• Tablet - Touch-optimized layout, gesture controls
• Smartphone - Simplified display, thumb-friendly controls
• E-reader - High contrast, minimal UI elements

Attention-Aware Learning

# Specify your current attention level
python -m flashgenie quiz --attention high

The system adjusts based on attention level:

• Very High - Complex material, challenging questions
• High - Balanced new and review content
• Medium - More review, less new content
• Low - Easy review, confidence building
• Very Low - Ultra-short sessions, familiar content

🚀 Using the Contextual Learning Engine

Basic Usage

# Let FlashGenie auto-detect context
python -m flashgenie quiz "Spanish Vocabulary"

Manual Context Specification

# Fully specify your context
python -m flashgenie quiz "Biology" \
  --environment noisy_public \
  --device smartphone \
  --attention medium \
  --energy 3

Available Context Parameters

Parameter	Description	Values
--environment	Study location	quiet_home, noisy_public, commuting, workplace, bed
--device	Device type	desktop, laptop, tablet, smartphone, e-reader
--attention	Focus level	very_low, low, medium, high, very_high
--energy	Mental energy	1-5 scale
--noise	Ambient noise	0.0-1.0 scale

🧪 The Science Behind It

The Contextual Learning Engine is based on research in:

• Context-Dependent Memory - Environmental cues in memory formation
• Cognitive Load Theory - Mental resource management
• Human-Computer Interaction - Device-specific usability
• Attention Economics - Focus as a limited resource
• Circadian Rhythms - Time-based energy patterns

📱 Environment-Specific Features

Quiet Home Environment

python -m flashgenie quiz --environment quiet_home

Optimizations:

• Deeper content exploration
• Complex question types
• Comprehensive feedback
• Extended study sessions

Commuting Environment

python -m flashgenie quiz --environment commuting

Optimizations:

• Interruption-resistant sessions
• Audio-first presentation
• One-handed interaction
• Quick-response formats

Workplace Environment

python -m flashgenie quiz --environment workplace

Optimizations:

• Professional content priority
• Discreet notifications
• Quick study bursts
• Work-relevant material

🔍 Context Recommendations

Get recommendations for optimizing your current context:

# Get context optimization suggestions
python -m flashgenie context-recommendations

Sample output:

Context Analysis:
- Environment: Noisy Public (detected)
- Device: Smartphone
- Attention: Medium (estimated)

Recommendations:
1. Consider using headphones to reduce distraction
2. Switch to audio mode for better focus
3. Shorter session (15-20 min) recommended for this environment
4. Review-focused content suggested for current attention level

🎯 Tips for Context-Optimized Learning

1. Be honest about your context - Accurate context information leads to better adaptation
2. Use environment-specific modes - Different environments require different approaches
3. Match content to context - Save complex material for high-focus environments
4. Consider time of day - Align difficult material with your peak mental hours
5. Adapt to energy fluctuations - Adjust session intensity based on mental freshness

🚀 Next Steps

• Adaptive Study Sessions - Create optimized study plans
• Learning Velocity Tracking - Track your learning progress
• Advanced Usage Patterns - Master complex study workflows

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FlashGenie v1.5.0 | Last updated: June 2025