edTech_app

Inspiration

Preparing for competitive exams like GATE is tough because resources are scattered and students often lack personalized insights. We wanted to build a simple, modular tool that allows students to practice effectively and track progress in real time. Our inspiration came from seeing how friends struggled to measure their improvement despite solving hundreds of questions.

What it does

The app lets students generate custom practice tests from a structured GATE question bank, attempt them through a Streamlit interface, and instantly view scores. It also provides detailed performance analytics, highlighting accuracy, speed, and weak areas. Over time, it tracks trends so students can prepare smarter instead of just harder.

How we built it

qa.py manages the question bank and retrieval logic.

app.py connects all components and drives the backend flow.

Streamlit app provides the interactive UI for test-taking.

performance_tracker.py computes accuracy, variance, and consistency while also plotting graphs of improvement. We used Python, Streamlit, and Matplotlib/Plotly to create a lightweight yet functional app.

Challenges we ran into

Standardizing question data across topics and difficulties.

Designing the test generator to ensure variety without repetition.

Making the performance tracker fast enough to handle multiple attempts smoothly.

Ensuring the Streamlit interface stayed user-friendly while offering detailed features.

Accomplishments that we're proud of

We are proud that we created a fully working end-to-end app where students can take tests, view real-time results, and track their learning journey. The modular design means new features (like AI-driven recommendations) can be added without breaking the core structure.

What we learned

We learned how to build modular Python applications, design data pipelines for educational apps, and implement performance analytics using simple statistics. We also gained hands-on experience integrating backend logic with a smooth, user-friendly frontend in Streamlit.

What's next for edTech_app

Our next step is to add AI-driven test recommendations so that the app automatically suggests questions based on weak areas. We also plan to expand the question bank, introduce mock full-length GATE exams, and add cloud-based deployment so that more students can access the tool anytime, anywhere.

Built With

• app.py
• gemini
• matplot
• numpy
• numpy-(data-handling
• pandas
• performance-tracker.py)-database:-sqlite-(local-storage-for-questions-and-user-results)-platforms:-streamlit-(interactive-web-app-environment)-cloud-services:-(if-deployed)-streamlit-cloud-/-heroku-/-aws-/-gcp-apis:-none-external-yet
• python
• sql
• statistics)-backend-/-app-logic:-django/flask-(optional-if-you-deployed-with-a-web-backend;-otherwise-pure-streamlit-+-python-modules-qa.py
• streamlit