EduTrack Student Performance Analysis 📊
🚀 Project Description
The EduTrack Student Performance Analysis project explores and uncovers factors affecting student academic performance across multiple subjects. Using statistical analysis and visualizations, the project highlights trends related to gender, parental education, socioeconomic status, and test preparation, providing actionable insights for targeted interventions and improved learning outcomes.
🎯 Key Objectives
Analyze student performance across subjects: Math, Reading, and Writing
Understand the impact of gender, parental education, lunch type, and test preparation courses on scores
Identify patterns and disparities to suggest equity-focused academic interventions
📂 Dataset
Source: Kaggle – Students Performance in Exams
Features include: Gender, Parental Education Level, Lunch Type, Test Preparation, Math Score, Reading Score, Writing Score
🛠 Tools & Technologies
Programming Language: Python
Libraries: Pandas, NumPy, Matplotlib, Seaborn
Techniques: Statistical summaries, correlation analysis, bar plots, boxplots, trend analysis
Visualization: Distribution plots, comparative charts, performance trends
📌 Key Insights 1️⃣ Gender-Based Performance Trends
Female students outperform males in reading and writing
Male students slightly outperform in math
Low-performing outliers are more frequent among males → indicates need for targeted support
2️⃣ Parental Education Correlation
Higher parental education (Master’s, Bachelor’s) → higher student performance
Lower parental education (High school, Associate’s) → lower student performance
3️⃣ Subject-Level Averages & Variability
Reading: highest average (69.17) & lowest variability → consistent performance
Math: lowest average (66.09) & highest variability → need for targeted interventions
Writing: moderate average, high variability → support struggling students
4️⃣ Lunch Type Effect
Standard lunch students perform better than free/reduced lunch students
Highlights socioeconomic disparities in performance
5️⃣ Test Preparation Courses
Completion of prep courses improves performance, especially in writing
Supports value of institution-sponsored prep programs
6️⃣ Equity & Disparities
Top performers: Female students from higher-income, higher-educated families with prep courses
Lowest performers: Male students from lower-income households with low parental education and no prep course
Suggests multi-tiered interventions and equity-focused programs
📈 Project Outcomes
Provides data-driven recommendations for subject-specific interventions
Highlights demographic disparities to guide policy and academic strategies
Helps educators and institutions improve student learning outcomes
⚡ How to Run the Project
- Clone the repository:
git clone https://github.com/honeyherambmathur/Edu-Track-Performance-Analysis
- Install dependencies:
pip install pandas numpy matplotlib seaborn
- Run the Jupyter Notebook:
jupyter notebook EduTrack_Analysis.ipynb