About This Project
A data visualization portfolio project exploring factors that influence Portuguese high school student mathematics performance.
Project Overview
This interactive data story analyzes the UCI Student Performance dataset, which contains information on 395 Portuguese high school students enrolled in math courses. The dataset includes demographic, social, and school-related features, with the goal of predicting student academic performance.
The analysis is structured around three research questions examining academic engagement, family background, and lifestyle factors. A decision tree model synthesizes findings to reveal the hierarchical importance of different predictors.
This project demonstrates skills in data storytelling, front-end development, interactive visualization design, and statistical analysis communication.
📚 Dataset Citation
P. Cortez and A. Silva. Using Data Mining to Predict Secondary School Student Performance. In A. Brito and J. Teixeira Eds., Proceedings of 5th FUture BUsiness TEChnology Conference (FUBUTEC 2008) pp. 5-12, Porto, Portugal, April, 2008, EUROSIS, ISBN 978-9077381-39-7.
🛠️ Technology Stack
React framework with App Router for server-side rendering and static export
Component-based UI with hooks for state management
Type-safe JavaScript for better developer experience and fewer runtime errors
Utility-first CSS framework for rapid, responsive design
React-based charting library built on D3 for declarative charts
Low-level library for custom, data-driven visualizations
Production-ready animation library for React
Fast CSV parser for loading and parsing student data