Managing Study Sessions

Calculate Spaced Repetition

node scripts/calculate-spaced-repetition.js flashcards.json schedule.json

Track Progress

node scripts/track-progress.js session-log.json progress-report.md

Study Session Workflow

graph TD
    A[Set Learning Goals] --> B[Create Study Plan]
    B --> C[Start Pomodoro Timer]

    C --> D[Focus Session: 25 min]
    D --> E[Short Break: 5 min]

    E --> F{Completed 4 Pomodoros?}
    F -->|No| C
    F -->|Yes| G[Long Break: 15-30 min]

    G --> H[Log Progress]
    H --> I[Update Spaced Repetition]

    I --> J{Goals Achieved?}
    J -->|No| C
    J -->|Yes| K[Session Complete]

    K --> L[Analyze Performance]

Pomodoro Technique

Classic Pomodoro Structure

Session 1: ██████████████████████████ (25 min) → ████ (5 min break)
Session 2: ██████████████████████████ (25 min) → ████ (5 min break)
Session 3: ██████████████████████████ (25 min) → ████ (5 min break)
Session 4: ██████████████████████████ (25 min) → ████████████ (15 min break)

Repeat cycle...

Pomodoro Session Template

## Study Session: [Topic]
**Date**: 2024-03-15
**Total Time**: 2 hours (4 Pomodoros)

### Pomodoro 1 (9:00-9:25)
**Task**: Read Chapter 5, Sections 5.1-5.2
**Completed**: ✓
**Distractions**: 0
**Focus Level**: 4/5

**Break (9:25-9:30)**: 5 minutes
**Activity**: Stretch, water

### Pomodoro 2 (9:30-9:55)
**Task**: Take notes on Section 5.2
**Completed**: ✓
**Distractions**: 2 (phone notifications)
**Focus Level**: 3/5

**Break (9:55-10:00)**: 5 minutes

### Pomodoro 3 (10:00-10:25)
**Task**: Create flashcards from notes
**Completed**: ✓
**Distractions**: 0
**Focus Level**: 5/5

**Break (10:25-10:30)**: 5 minutes

### Pomodoro 4 (10:30-10:55)
**Task**: Practice problems 1-5
**Completed**: ⚠️  (Completed 3/5)
**Distractions**: 1
**Focus Level**: 4/5

**Long Break (10:55-11:10)**: 15 minutes
**Activity**: Walk outside, snack

---

**Session Summary**:
- Total Pomodoros: 4
- Total Focus Time: 100 minutes
- Average Focus Level: 4/5
- Total Distractions: 3
- Completion Rate: 87.5%

Modified Pomodoro Variations

Extended Pomodoro (for deep work):

• Focus: 50 minutes
• Break: 10 minutes
• Long break: 30 minutes (after 2 sessions)

Short Pomodoro (for difficult material):

• Focus: 15 minutes
• Break: 3 minutes
• Long break: 10 minutes (after 4 sessions)

Flexible Pomodoro (task-based):

• Focus: Until subtask complete (max 45 min)
• Break: Proportional (1 min per 5 min work)

Spaced Repetition System

SM-2 Algorithm

Core Principle: Review material at increasing intervals based on recall quality

Formula:

If quality ≥ 3:
    interval = previous_interval × easiness_factor
    easiness_factor = max(1.3, ef + (0.1 - (5 - quality) × (0.08 + (5 - quality) × 0.02)))

If quality < 3:
    interval = 1 day (reset)
    repetition = 0 (restart)

Quality Ratings (0-5)

• 5: Perfect recall, easy
• 4: Correct, with hesitation
• 3: Correct, with difficulty
• 2: Incorrect, but familiar
• 1: Incorrect, guess
• 0: Complete blackout

Spaced Repetition Schedule

timeline
    title Flashcard Review Schedule (Starting March 1)
    March 1 : First Review
            : Quality: 4
    March 2 : Second Review (1 day)
            : Quality: 5
    March 5 : Third Review (3 days)
            : Quality: 4
    March 12 : Fourth Review (7 days)
             : Quality: 5
    March 29 : Fifth Review (17 days)
             : Quality: 5
    May 9 : Sixth Review (41 days)

Spaced Repetition Tracking

const flashcard = {
  id: "fc_001",
  front: "What is a neural network?",
  back: "Computing system inspired by biological neural networks",
  history: [
    { date: "2024-03-01", quality: 4, interval: 1, easinessFactor: 2.5 },
    { date: "2024-03-02", quality: 5, interval: 3, easinessFactor: 2.6 },
    { date: "2024-03-05", quality: 4, interval: 7, easinessFactor: 2.5 },
    { date: "2024-03-12", quality: 5, interval: 17, easinessFactor: 2.6 }
  ],
  nextReview: "2024-03-29",
  masteryLevel: "proficient"  // learning → proficient → mastered
};

Daily Review Schedule

## Today's Review: March 15, 2024

### Due Today (8 cards)
1. Neural network definition - [Review]
2. Backpropagation algorithm - [Review]
3. Gradient descent formula - [Review]
4. Overfitting definition - [Review]
5. Training vs test set - [Review]
6. Activation functions - [Review]
7. Loss function types - [Review]
8. Regularization purpose - [Review]

### Upcoming (Next 3 Days)
- March 16: 5 cards
- March 17: 3 cards
- March 18: 7 cards

### Overdue (2 cards)
- Supervised learning (2 days overdue) - [Priority Review]
- Feature engineering (1 day overdue) - [Priority Review]

**Estimated Time**: 25 minutes (10 cards × 2.5 min avg)

Study Plan Generation

Weekly Study Plan Template

# Week 3 Study Plan: Machine Learning Fundamentals
**Period**: March 15-21, 2024
**Goal**: Complete Chapter 5, Master 50 flashcards

## Monday (2 hours)
- **9:00-9:25**: Read Section 5.1 📖
- **9:30-9:55**: Take notes 📝
- **10:00-10:25**: Create flashcards 🃏
- **10:30-10:55**: Review yesterday's cards (SR) 🔄

## Tuesday (2 hours)
- **9:00-9:25**: Read Section 5.2 📖
- **9:30-9:55**: Watch lecture video 🎥
- **10:00-10:25**: Practice problems 1-5 ✏️
- **10:30-10:55**: Review flashcards (SR) 🔄

## Wednesday (1.5 hours)
- **9:00-9:25**: Read Section 5.3 📖
- **9:30-9:55**: Concept map creation 🗺️
- **10:00-10:25**: Quiz practice 📋

## Thursday (2 hours)
- **9:00-9:25**: Review notes from sections 5.1-5.3 📝
- **9:30-9:55**: Practice problems 6-10 ✏️
- **10:00-10:25**: Create summary sheet 📄
- **10:30-10:55**: Flashcard review (SR) 🔄

## Friday (2 hours)
- **9:00-9:25**: Chapter 5 comprehensive review 🔍
- **9:30-9:55**: Practice exam questions 🎓
- **10:00-10:25**: Identify weak areas 🎯
- **10:30-10:55**: Targeted practice 💪

## Saturday (1 hour)
- **10:00-10:25**: Flashcard marathon (SR) 🔄
- **10:30-10:55**: Optional: Additional practice ➕

## Sunday (Rest/Light Review)
- **Evening**: 15-minute flashcard review 🔄

---

**Total Planned Time**: 10.5 hours
**Focus Distribution**:
- Reading: 30%
- Practice: 25%
- Review (SR): 25%
- Note-taking/Synthesis: 20%

Semester Study Plan

gantt
    title Semester Study Plan
    dateFormat  YYYY-MM-DD
    section Weeks 1-4
    Chapter 1-2           :2024-01-15, 14d
    Midterm 1 Prep        :2024-01-29, 7d
    section Weeks 5-8
    Chapter 3-4           :2024-02-05, 14d
    Project Phase 1       :2024-02-12, 14d
    section Weeks 9-12
    Chapter 5-6           :2024-02-26, 14d
    Midterm 2 Prep        :2024-03-11, 7d
    section Weeks 13-16
    Chapter 7-8           :2024-03-18, 14d
    Project Phase 2       :2024-03-25, 14d
    Final Exam Prep       :2024-04-08, 7d
    Final Exam            :milestone, 2024-04-15, 0d

Progress Tracking

Topic Mastery Levels

const topicProgress = {
  "Neural Networks": {
    status: "learning",           // not-started, learning, proficient, mastered
    timeSpent: 450,                // minutes
    flashcardsCreated: 23,
    flashcardsMastered: 15,
    practiceProblemsCompleted: 8,
    practiceProblemsCorrect: 6,
    accuracy: 0.75,
    lastReviewed: "2024-03-14",
    nextReview: "2024-03-16",
    confidenceLevel: 7,            // 1-10
    notes: "Need more practice with backpropagation"
  }
};

Progress Visualization

gantt
    title Learning Progress: Machine Learning Course
    dateFormat  YYYY-MM-DD
    section Chapter 1
    Completed           :done, 2024-01-15, 7d
    section Chapter 2
    Completed           :done, 2024-01-22, 7d
    section Chapter 3
    Completed           :done, 2024-01-29, 7d
    section Chapter 4
    In Progress         :active, 2024-02-05, 4d
    section Chapter 5
    Not Started         :2024-02-09, 7d

Study Analytics Dashboard

# Study Analytics: Week of March 15-21

## Time Investment
- **Total Study Time**: 12.5 hours
- **Target**: 10 hours ✅
- **Focus Time**: 10 hours (80%)
- **Break Time**: 2.5 hours (20%)

## Productivity Metrics
- **Pomodoros Completed**: 30
- **Average Focus Level**: 4.2/5
- **Distractions**: 8 total (0.27 per Pomodoro)
- **Peak Focus Hours**: 9-11 AM

## Learning Progress
- **Flashcards Reviewed**: 87
- **New Cards Created**: 23
- **Cards Mastered**: 15
- **Average Recall Quality**: 4.1/5

## Topic Coverage
- ✅ Chapter 5 Reading (100%)
- ✅ Practice Problems (80%)
- ⚠️  Concept Maps (60%)
- ❌ Quiz Preparation (30%)

## Weak Areas Identified
1. Backpropagation algorithm (accuracy: 60%)
2. Gradient descent optimization (accuracy: 70%)
3. Overfitting vs underfitting (accuracy: 75%)

## Next Week Goals
- [ ] Complete Chapter 6
- [ ] Master 20 new flashcards
- [ ] Achieve 85%+ on practice quiz
- [ ] Review all weak areas

Break Optimization

Break Activities by Duration

Micro-breaks (1-2 minutes):

• Eye exercises (20-20-20 rule: every 20 min, look 20 feet away for 20 sec)
• Stand and stretch
• Deep breathing
• Drink water

Short breaks (5 minutes):

• Walk around room
• Light stretching
• Healthy snack
• Quick tidying
• Social media (limited)

Long breaks (15-30 minutes):

• Walk outside
• Exercise/yoga
• Full meal
• Power nap (20 min)
• Call friend/family

Avoid During Breaks:

• ❌ Work-related content
• ❌ Heavy meals (causes drowsiness)
• ❌ Stressful news/social media
• ❌ Starting new complex tasks

Break Effectiveness Matrix

Focus Time Optimization

Peak Performance Times

Identify Your Chronotype:

Morning Lark (peak: 8-12 PM):

• Schedule difficult material in morning
• Use afternoon for review and practice
• Earlier sleep/wake schedule

Night Owl (peak: 4-10 PM):

• Warm-up with easier tasks in morning
• Save demanding work for afternoon/evening
• Later sleep/wake schedule

Hummingbird (flexible):

• Multiple shorter study sessions
• Adapt to circumstances
• Mix difficult and easy throughout day

Environmental Optimization

Physical Environment:

• ✅ Clean, organized workspace
• ✅ Good lighting (natural light preferred)
• ✅ Comfortable temperature (68-72°F)
• ✅ Ergonomic seating
• ✅ Minimal visual distractions

Digital Environment:

• ✅ Close unnecessary tabs/apps
• ✅ Use website blockers during Pomodoros
• ✅ Phone on silent/airplane mode
• ✅ Notifications disabled
• ✅ Study music/white noise (if helpful)

Distraction Management

Before Session:

## Pre-Study Checklist
- [ ] Phone on silent, face-down
- [ ] Close social media tabs
- [ ] Water bottle filled
- [ ] Bathroom break taken
- [ ] Study materials prepared
- [ ] Timer set
- [ ] Goals written down

During Session:

• Distraction Log: Write down distractions without acting on them
• Two-Minute Rule: If it takes <2 min, do it during break
• Scheduled Worry Time: Set aside 15 min later to address concerns

Study Session Templates

Exam Preparation Session

# Exam Prep Session: Midterm 2
**Date**: March 20, 2024
**Exam Date**: March 25, 2024
**Duration**: 3 hours

## Session Structure

### Hour 1: Active Recall (3 Pomodoros)
- **Pomodoro 1**: Practice quiz (no notes)
- **Pomodoro 2**: Review incorrect answers
- **Pomodoro 3**: Flashcard sprint (50 cards)

### Hour 2: Problem Solving (3 Pomodoros)
- **Pomodoro 4**: Practice problems set 1
- **Pomodoro 5**: Practice problems set 2
- **Pomodoro 6**: Review solutions

### Hour 3: Synthesis (2 Pomodoros)
- **Pomodoro 7**: Create concept map of all topics
- **Pomodoro 8**: Identify and study weak areas

**Long Break**: 30 minutes (lunch)

**Optional Hour 4**: Spaced repetition review

Deep Learning Session

# Deep Learning Session: New Chapter
**Date**: March 15, 2024
**Topic**: Chapter 5 - Neural Networks
**Duration**: 2 hours

## Session Goals
1. Read and understand Sections 5.1-5.2
2. Create comprehensive notes
3. Generate 20 flashcards
4. Complete 3 practice problems

## Pomodoro Breakdown
- **Pomodoro 1-2**: Active reading with annotations
- **Pomodoro 3**: Note-taking and synthesis
- **Pomodoro 4**: Flashcard creation
- **Pomodoro 5**: Practice problems
- **Pomodoro 6**: Review and self-quiz

**Success Criteria**:
- [ ] Can explain main concepts without notes
- [ ] Created quality flashcards for all key terms
- [ ] Solved practice problems correctly

Advanced Features

For detailed information:

• Spaced Repetition Science: resources/spaced-repetition-science.md
• Study Techniques Guide: resources/study-techniques.md
• Focus Optimization: resources/focus-optimization.md
• Session Templates: resources/session-templates.md

References

• Pomodoro Technique (Francesco Cirillo)
• SM-2 Algorithm (SuperMemo)
• Spaced Repetition research (Ebbinghaus, Piotr Woźniak)
• Peak Performance research (circadian rhythms)
• Cognitive Load Theory for learning optimization