Adaptive Quiz Assessment Platform

A comprehensive full-stack quiz and assessment platform built with the MERN stack, featuring adaptive testing algorithms, AI-powered performance analysis, and detailed progress tracking.

Overview

This platform provides an intelligent quiz system designed to assess and improve cognitive abilities through adaptive testing methodologies. The system dynamically adjusts question difficulty based on user performance, provides AI-generated insights, and tracks progress over time.

Key Features

1. Adaptive Assessment System

Dynamic difficulty adjustment based on real-time performance
Intelligent question selection algorithm
Progressive difficulty levels: Very Easy → Easy → Moderate → Difficult
Maximum 30 questions per adaptive test
Automatic level progression after 2 consecutive correct answers

2. Multiple Assessment Modes

Adaptive Assessment: AI-driven difficulty adjustment
Traditional Assessment: Fixed difficulty testing
Selection-Based Assessment: Topic-specific testing
Practice Mode: Mixed practice and difficult practice options

3. AI-Powered Performance Analysis

Integration with Google Gemini AI for intelligent result analysis
Personalized performance insights
Topic-wise strength and weakness identification
Time management analysis
Actionable improvement recommendations

4. Comprehensive Progress Tracking

Detailed test history with timestamps
Question-by-question performance breakdown
Overall statistics dashboard
Average time per question tracking
Correctness percentage by difficulty level

5. User Authentication & Profiles

Secure JWT-based authentication
User registration and login
Profile management
Password encryption using bcrypt
Session persistence

6. Rich Question Database

Over 29,000 questions across multiple difficulty levels
Topics include:
- Permutation and Combination
- Logical Reasoning
- Quantitative Aptitude
- And more
Each question includes:
- Multiple choice options
- Detailed explanations
- Fundamental concepts tags
- Difficulty classification

7. Advanced UI/UX

Responsive design with Tailwind CSS
Smooth animations using Framer Motion
Real-time timer display
Interactive progress indicators
PDF result export capability
Clean, modern interface

Tech Stack

Frontend (Client)

Technology	Purpose
React 19	UI framework
Vite	Build tool and dev server
React Router DOM	Client-side routing
Axios	HTTP client for API calls
Framer Motion	Animations and transitions
Tailwind CSS	Styling framework
Lucide React	Icon library
jsPDF	PDF generation for results
html2canvas	Screenshot capture for PDFs

Backend (Server)

Technology	Purpose
Node.js	Runtime environment
Express.js	Web framework
MongoDB	Database
Mongoose	ODM for MongoDB
JWT	Authentication tokens
bcrypt	Password hashing
Google Generative AI	AI-powered analysis
CORS	Cross-origin resource sharing
dotenv	Environment variable management

Project Structure

quiz/
├── client/                    # Frontend application
│   ├── src/
│   │   ├── assets/
│   │   │   ├── dataset/      # Question database
│   │   │   └── images/       # Application images
│   │   ├── context/          # React context (Auth)
│   │   ├── lib/              # API utilities
│   │   ├── pages/            # Page components
│   │   │   ├── Homepage.jsx
│   │   │   ├── AdaptiveAssess.jsx
│   │   │   ├── auth.jsx
│   │   │   ├── Profile.jsx
│   │   │   ├── Results.jsx
│   │   │   ├── ResultDetail.jsx
│   │   │   └── ... (other pages)
│   │   ├── App.jsx           # Main app component
│   │   └── main.jsx          # Entry point
│   ├── index.html
│   ├── package.json
│   └── vite.config.js
│
└── server/                    # Backend application
    ├── server.js             # Main server file
    ├── package.json
    └── .env                  # Environment variables (not in repo)

Database Schema

User Model

{
  name: String,
  email: String (unique, required),
  passwordHash: String (required),
  gender: String (enum: male, female, other),
  photoUrl: String,
  createdAt: Date,
  updatedAt: Date
}

Result Model

{
  userId: ObjectId (ref: User),
  totalQuestions: Number,
  correct: Number,
  wrong: Number,
  avgTimeSec: Number,
  questions: [{
    questionNumber: Number,
    question: String,
    selectedAnswer: String,
    correctAnswer: String,
    isCorrect: Boolean,
    timeTaken: Number,
    difficulty: String,
    fundamentals: [String]
  }],
  aiSummary: String,
  createdAt: Date,
  updatedAt: Date
}

API Endpoints

Authentication

POST /api/auth/register - Register new user
POST /api/auth/login - User login
GET /api/auth/me - Get current user (protected)

User Management

PUT /api/user/profile - Update user profile (protected)

Results & Analytics

POST /api/results - Save test result (protected)
GET /api/results/history - Get user's test history (protected)
GET /api/results/summary - Get overall statistics (protected)
GET /api/results/:id - Get specific result details (protected)
POST /api/results/:id/summary - Generate AI summary for result (protected)

Health Check

GET /api/health - Server health status

Installation & Setup

Prerequisites

Node.js (v14 or higher)
MongoDB (local or cloud instance)
Google Gemini API key

1. Clone the Repository

git clone https://github.com/MaheshN1821/hackathon.git
cd hackathon

2. Backend Setup

cd server
npm install

Create a .env file in the server directory:

PORT=3000
MONGO_URI=your_mongodb_connection_string
JWT_SECRET=your_jwt_secret_key
GEMINI_API_KEY=your_google_gemini_api_key

Start the backend server:

npm start
# or for development with auto-restart
npm run dev

3. Frontend Setup

cd client
npm install

Update the API endpoints in the following files if needed:

src/context/AuthContext.jsx
src/lib/api.js
src/pages/*.jsx

Start the development server:

npm run dev

The application will be available at http://localhost:5173

4. Build for Production

Backend:

cd server
npm start

Frontend:

cd client
npm run build
npm run preview

Adaptive Testing Algorithm

The platform implements an intelligent adaptive testing algorithm:

Initial Level: All users start at "very_easy"
Progression Logic:
- Advance to next level after 2 consecutive correct answers
- Drop back one level after 2 consecutive wrong answers
Level Sequence: very_easy → easy → moderate → difficult
Question Limit: Maximum 30 questions per test
Dynamic Selection: Questions are randomly selected from available pool at current difficulty
History Tracking: Previously asked questions are tracked to avoid repetition

AI Analysis Features

The platform uses Google Gemini AI to provide:

Performance trends analysis
Topic-wise performance breakdown
Time management insights
Difficulty progression tracking
Personalized improvement recommendations
Strengths and weaknesses identification

Security Features

Password hashing with bcrypt (10 salt rounds)
JWT-based authentication with 7-day expiry
Protected API routes with authentication middleware
Input validation and sanitization
CORS configuration for secure cross-origin requests
MongoDB injection prevention through Mongoose

Deployment

Frontend (Vercel)

The frontend is deployed on Vercel at: https://quiz-jmux.vercel.app

Configuration in client/vercel.json:

{
  "rewrites": [
    { "source": "/(.*)", "destination": "/" }
  ]
}

Backend (Vercel)

The backend is deployed on Vercel at: https://quiz-woad-pi.vercel.app

Configuration in server/vercel.json:

{
  "version": 2,
  "builds": [
    { "src": "server.js", "use": "@vercel/node" }
  ],
  "routes": [
    { "src": "/(.*)", "dest": "/server.js" }
  ]
}

Future Enhancements

Mobile application (React Native)
Real-time multiplayer quiz mode
Leaderboard system
Certificate generation
Admin dashboard for question management
Integration with educational platforms
Video explanations for questions
Voice-based quiz mode
Gamification with badges and achievements
Social sharing features
Advanced analytics with charts and graphs
Custom quiz creation by users
Timed challenge mode
Group study sessions
Performance comparison with peers

Performance Optimizations

Lazy loading of routes
Optimized database queries with indexes
Token-based authentication to reduce server load
Client-side caching of user data
Efficient state management with React Context
Minimized bundle size with Vite

Browser Support

Chrome (latest)
Firefox (latest)
Safari (latest)
Edge (latest)

Contributing

Contributions are welcome! Please follow these steps:

Fork the repository
Create a feature branch (git checkout -b feature/AmazingFeature)
Commit your changes (git commit -m 'Add some AmazingFeature')
Push to the branch (git push origin feature/AmazingFeature)
Open a Pull Request

License

This project is licensed under the ISC License.

Acknowledgments

Google Generative AI for intelligent analysis
MongoDB for robust database solutions
Vercel for seamless deployment
The open-source community for excellent libraries and tools

Contact

For questions or support, please contact the development team.

Built with ❤️ by Team Warriors

Name		Name	Last commit message	Last commit date
Latest commit History 55 Commits
client		client
server		server
README.md		README.md

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