AI-Powered Adaptive Learning System

Overview

This project implements an intelligent learning platform that adapts to individual student needs using AI technologies. It combines LSTM and Random Forest algorithms to provide personalized learning experiences and real-time performance tracking.

Features

• Personalized learning path recommendations
• Real-time performance analytics
• Adaptive assessment system
• Interactive dashboard
• Student progress tracking
• AI-powered predictions

Technical Stack

• Backend: Python, Flask
• Frontend: HTML, CSS, JavaScript
• AI/ML: TensorFlow, Scikit-learn
• Data Processing: NumPy, Pandas
• Visualization: Chart.js

Installation

1. Clone the repository

git clone https://github.com/faizalcareers/AdaptiveLearning.git

2. Install dependencies

pip install -r requirements.txt

3. Run the application

python app.py

Project Structure

├── app.py                 # Main Flask application
├── templates/
│   └── index.html        # Main dashboard template
├── static/
│   ├── css/             # Stylesheets
│   └── js/              # JavaScript files
└── models/
    ├── ai_model.py      # AI model implementations
    └── analytics.py     # Analytics processing

AI Models

LSTM Model

• Predicts student performance
• Uses sequence of learning activities
• Features include scores, time spent, and progress

Random Forest Model

• Recommends learning paths
• Considers prerequisites and difficulty levels
• Evaluates student readiness

Usage

1. Start the server
2. Access the dashboard at http://localhost:5000
3. Select a student to view their personalized dashboard
4. Monitor progress and recommendations in real-time

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.