AI Evaluator

A modern educational testing platform with AI-powered test generation and automated essay grading

📄 Research Paper: AI Evaluator: An AI-Powered Educational Assessment Platform (STM Journals, 2024)

Overview

AI Evaluator is an advanced educational assessment platform that enables teachers to create, manage, and evaluate tests while providing students with a streamlined interface for taking tests and reviewing detailed feedback. The application leverages artificial intelligence to generate test content and evaluate free-response answers.

Features

For Teachers

• Test Creation: Create multiple-choice and free-response questions manually
• AI Test Generation: Generate complete tests on any subject using AI
• Test Management: Edit, delete, and track all created tests
• Automatic Grading: AI-powered evaluation of student paragraph/essay responses
• Dashboard: Overview of all tests with status and statistics

For Students

• Test Taking: User-friendly interface for taking tests with timer functionality
• Detailed Feedback: Comprehensive feedback on test performance
• Progress Tracking: Dashboard showing completed tests and scores
• AI-Generated Feedback: Receive personalized feedback on paragraph answers

For Administrators

• Teacher Approval: Manage teacher account approvals
• System Management: Monitor system usage and performance

Screenshots

Teacher Dashboard

Test Creation

AI Test Generation

Student Test Taking

Test Results and Feedback

Technology Stack

Frontend

• React.js with React Router for navigation
• Tailwind CSS for styling
• Axios for API communication

Backend

• Flask RESTful API
• MongoDB database
• Mistral LLM for AI capabilities
• Authentication system with role-based permissions

Installation and Setup

Prerequisites

• Node.js (v14 or higher)
• Python (v3.8 or higher)
• MongoDB

Frontend Setup

1. Clone the repository:

   git clone https://github.com/yourusername/ai-evaluator.git
   cd ai-evaluator
   

2. Install dependencies:

   npm install
   

3. Run development server:

   npm run dev
   

Backend Setup

1. Navigate to the API directory:

   cd api
   

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Create a .env file with the following variables:

   MISTRAL_API_URL=your_mistral_api_url
   MONGODB_URI=your_mongodb_connection_string
   

5. Run the API server:

   python app.py
   

Usage

Default Admin Account

• Username: admin
• Password: admin

User Roles

• Student: Can take tests and view results
• Teacher: Can create and manage tests (requires admin approval)
• Admin: Can approve teacher accounts and manage the system

Project Structure

ai-evaluator/
├── api/                 # Backend Flask API
│   ├── app.py           # Main API application
│   ├── controllers.py   # API controllers
│   ├── models.py        # Data models
│   ├── database.py      # Database connection
│   └── mistral_wrapper.py  # AI integration
├── src/                 # React frontend
│   ├── components/      # UI components
│   ├── services/        # API service layer
│   └── App.jsx          # Main application component
├── public/              # Static assets
├── package.json         # Frontend dependencies
└── README.md            # Project documentation

AI Integration

The application integrates with the Mistral Large Language Model (LLM) for:

1. Generating complete tests with questions and answers
2. Evaluating student paragraph/essay responses
3. Providing meaningful feedback on written answers

Future Enhancements

• Interactive question types (drag-and-drop, fill-in-blanks)
• Advanced analytics for teachers
• Plagiarism detection
• Group/class management capabilities
• Mobile app version

License

MIT License

Acknowledgments

• Mistral AI for providing the LLM API
• The MongoDB team for the database solution
• TailwindCSS for the styling framework