OULAD Student Performance Analysis

This project analyses the Open University Learning Analytics Dataset (OULAD) to predict at-risk students and identify engagement patterns.

Setup Instructions

1. Create a Virtual Environment

# Create a new virtual environment
python -m venv venv

# Activate the environment
# On macOS/Linux:
source venv/bin/activate

# On Windows:
venv\Scripts\activate

2. Install Dependencies

pip install -r requirements.txt

3. Run the Notebooks

Launch Jupyter and open the notebooks:

jupyter lab

Available Notebooks

• oulad_classification.ipynb - At-risk student classification analysis using machine learning models (XGBoost, LightGBM, etc.)
• oulad_clustering.ipynb - Student engagement clustering analysis

Data

The data exceeds 100Mb in size therefore cannot be pushed to the github.

The OULAD dataset files should be placed in the data/ directory (please create it at the root of the project). The dataset can be downloaded from the Open University Learning Analytics Dataset.