Student Wellbeing Self-Assessment Tool

Empowering students to understand and manage their mental health through data-driven insights and self-assessment.

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Inspiration

University life can be overwhelming. Many students silently struggle with stress, anxiety, and academic pressure without fully understanding their mental health condition.

After analyzing a real-world student mental health dataset, I realized there was an opportunity to go beyond simple data visualization and create something practical — a tool students could actually use.

This project was inspired by the idea of combining data analytics with a real-time self-assessment system to help students better understand and manage their stress levels.

What it does

This project is a web-based mental health assessment application designed for students.

It has two main components:

  1. 📊 Data Analytics Dashboard

    • Visualizes trends in depression, anxiety, panic attacks, and CGPA
    • Explores relationships between academic performance and mental health

  2. 🧠 Self-Assessment Tool

    • Allows students to answer simple lifestyle and stress-related questions
    • Calculates a stress risk score
    • Displays a visual pie chart representation
    • Provides personalized well-being recommendations

The goal is not to replace professional help, but to provide awareness and early self-reflection.

How I built it

The project was developed using:

  • Python
  • Streamlit for building the interactive web app
  • Pandas for data analysis
  • Matplotlib for visualizations

The dataset was cleaned and analyzed to extract meaningful insights.
Then, I designed a simple stress scoring logic system:

  • Poor sleep increases risk
  • Excessive study hours increase risk
  • Reported stress and panic attacks increase risk

The total score determines whether a student falls into Low, Moderate, or High stress category.

Challenges we ran into

  • Learning how to convert data analysis into a usable application
  • Understanding how to deploy and structure a Streamlit app
  • Designing a scoring logic that is simple but meaningful
  • Making the interface user-friendly and intuitive

This project helped me understand how data science can move from analysis to real-world application.

What I've learned

  • How to build and structure a complete web application
  • How to integrate data analytics with user interaction
  • How to transform raw datasets into actionable insights
  • The importance of designing technology with empathy

What's next for Student Wellbeing Self-Assessment Tool

  • Add AI-based recommendation engine
  • Deploy the application publicly
  • Add anonymous result tracking for research insights
  • Integrate chatbot-style mental health assistant
  • Improve UI/UX design for better engagement

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