A reinforcement learning framework for personalized learning. This repository contains code and resources for simulating adaptive learning environments, implementing RL algorithms, and evaluating personalized education strategies.

Features

• Modular RL agent for curriculum adaptation
• Simulated student models
• Customizable learning environments for question sequencing
• Experiment tracking and evaluation scripts

Getting Started

1. Clone the repository.
2. Install dependencies:

   pip install -r requirements.txt

3. If you are doing EDA or data cleaning, add assistments_dataset.csv into 'data' directory

Folder Structure

• agents/ — RL and DKT agent implementations
• environments/ — Simulated learning environments
• models/ — Trained teacher and student models
• trainings/ — Training scripts, logs, and experiment histories
• data/ — Datasets and question banks
• plots/ — Visualization and analysis results

Contact

For questions or contributions, open an issue or submit a pull request.