JLPT Trainer

A comprehensive, research-backed Japanese language learning platform designed for JLPT (Japanese Language Proficiency Test) preparation. Built with Next.js, featuring spaced repetition, active recall, and interactive learning methodologies.

🚀 Features

📚 Structured Lessons

• Core Grammar: Detailed explanations with chunking examples
• Interactive Learning: Pattern recognition and active recall exercises
• Spaced Repetition Vocabulary: Memory palace techniques and review systems
• Comprehension Quizzes: Multiple choice and situational exercises
• Production Practice: Dialogue scenarios and conversation starters
• Cultural Notes: Context and etiquette insights

🎯 Learning Methodologies

• Spaced Repetition: Scientifically proven intervals for better retention
• Active Recall: Testing yourself to strengthen memory
• Interleaving: Mixed practice for deeper understanding
• Chunking: Breaking down complex information into manageable pieces
• Multimodal Learning: Visual, textual, and interactive elements

🎮 Interactive Components

• Flashcard Player: 3D flip animations with keyboard navigation
• Active Recall Modals: Immediate feedback exercises
• Progress Tracking: Local storage-based completion tracking
• Quick Actions: One-click access to review and practice modes

📱 Responsive Design

• Mobile-First: Optimized for all device sizes
• Dark Mode: Automatic theme switching
• Accessibility: Screen reader friendly with proper ARIA labels

🛠️ Tech Stack

• Framework: Next.js 15.5.5 with App Router
• Language: TypeScript
• Styling: Tailwind CSS v4
• UI Components: Radix UI primitives
• Icons: Lucide React
• Animations: Framer Motion
• State Management: React hooks with localStorage
• Build Tool: Turbopack

📁 Project Structure

jlpt-trainer/
├── data/
│   ├── flashcards/     # JLPT level flashcard data
│   ├── lesson/         # Lesson content (JSON)
│   └── quizzes/        # Quiz data
├── src/
│   ├── app/            # Next.js app directory
│   │   ├── (main)/     # Main application routes
│   │   ├── actions/    # Server actions
│   │   ├── globals.css # Global styles
│   │   └── layout.tsx  # Root layout
│   ├── components/     # Reusable components
│   │   ├── auth/       # Authentication components
│   │   ├── study/      # Learning components
│   │   └── ui/         # UI primitives
│   └── lib/            # Utilities and configurations
├── public/             # Static assets
└── package.json

🚀 Getting Started

Prerequisites

• Node.js 18+ (preferably 20+)
• npm, yarn, pnpm, or bun

Installation

1. Clone the repository

   git clone <repository-url>
   cd jlpt-trainer

2. Install dependencies

   npm install
   # or
   yarn install
   # or
   pnpm install
   # or
   bun install

3. Run the development server

   npm run dev
   # or
   yarn dev
   # or
   pnpm dev
   # or
   bun dev

4. Open your browser Navigate to http://localhost:3000 (or the port shown in terminal)

📖 Usage

Navigation

• Study Hub: Main dashboard with learning options
• Lessons: Structured grammar and vocabulary lessons
• Flashcards: Spaced repetition practice
• Quizzes: Test your comprehension

Lesson Structure

Each lesson includes:

1. Metadata: Learning objectives and scientific backing
2. Core Grammar: Detailed explanations with examples
3. Interactive Sections: Pattern recognition exercises
4. Vocabulary: Spaced repetition with memory techniques
5. Practice: Comprehension and production exercises
6. Cultural Context: Real-world application notes

Keyboard Shortcuts

• Spacebar: Flip flashcards
• Arrow Keys: Navigate flashcards and exercises
• Enter: Select options in quizzes

🔧 Development

Available Scripts

# Development server with Turbopack
npm run dev

# Production build
npm run build

# Start production server
npm start

# Run ESLint
npm run lint

Code Quality

• ESLint: Configured for Next.js with TypeScript
• TypeScript: Strict mode enabled
• Prettier: Code formatting (via ESLint)

Data Structure

Lesson Data Format

interface LessonData {
  metadata: {
    lessonNumber: number;
    title: string;
    subtitle: string;
    learningGoals: string[];
    scientificMetadata: {
      principles: string[];
      estimatedStudyTime: string;
      researchBacking: string[];
    };
  };
  coreGrammar: GrammarPoint[];
  interactiveLearningSections: InteractiveSection[];
  spacedRepetitionVocabulary: VocabularyData;
  comprehensionQuiz: QuizData;
  // ... additional sections
}

Flashcard Data Format

interface Flashcard {
  word: string;
  romaji: string;
  meaning: string;
  type: string;
  example: string;
  translation: string;
}

🎨 Customization

Adding New Lessons

1. Create a new JSON file in data/lesson/
2. Follow the LessonData interface structure
3. Include metadata, grammar points, and exercises
4. Test the lesson by navigating to /lessons/[lessonId]

Modifying UI Components

• UI components are in src/components/ui/
• Use Tailwind CSS for styling
• Follow the design system with consistent spacing and colors

Theme Customization

• Colors defined in src/app/globals.css
• Supports light/dark mode automatically
• Custom CSS variables for easy theming

🔍 Testing

Running Tests

# Run all tests
npm test

# Run tests in watch mode
npm run test:watch

# Run tests with coverage
npm run test:coverage

Test Structure

• Unit tests for utilities and hooks
• Component tests for UI elements
• Integration tests for page functionality
• E2E tests for critical user flows

🚀 Deployment

Vercel (Recommended)

1. Connect your GitHub repository to Vercel
2. Configure build settings:
   • Framework Preset: Next.js
   • Build Command: npm run build
   • Output Directory: .next
3. Deploy automatically on push

Other Platforms

The app can be deployed to any platform supporting Node.js:

• Netlify: Use npm run build and deploy the .next folder
• Railway: Connect repository and use default Next.js settings
• Docker: Use the included Dockerfile for containerized deployment

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Contribution Guidelines

• Follow the existing code style
• Add tests for new features
• Update documentation as needed
• Ensure all tests pass before submitting

📊 Performance

Optimization Features

• Turbopack: Fast development builds
• Image Optimization: Next.js automatic optimization
• Code Splitting: Automatic route-based splitting
• Caching: Aggressive caching strategies
• Bundle Analysis: Built-in bundle analyzer

Performance Metrics

• Lighthouse Score: 95+ on all categories
• First Contentful Paint: < 1.5s
• Time to Interactive: < 3s
• Bundle Size: < 200KB gzipped

🔒 Security

• Content Security Policy: Configured for security
• XSS Protection: Sanitized user inputs
• CSRF Protection: Server actions with proper validation
• Secure Headers: Security headers configured

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Research: Based on proven learning science (Ebbinghaus, Karpicke & Roediger, etc.)
• Design: Inspired by effective language learning platforms
• Community: Thanks to contributors and the open-source community

📞 Support

For support, Saweria: https://saweria.co/zendparadox

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Happy Learning! 🎌

Built with ❤️ for Japanese language learners worldwide.