Praxis

Initial screen
Main screen

Inspiration

Praxis was inspired by our team's experience with tutoring and the desire to make quality education accessible to everyone. Recognizing that many students benefit from visual aids and interactive dialogue, we designed Praxis to mimic a tutoring session. It offers real-time problem-solving with visual cues and interactive conversations, providing an affordable alternative to expensive tutoring services.

What it does

Praxis is an ACT and SAT test preparation platform that offers personalized, visually driven learning experiences. It helps high school students study by breaking down test questions visually, catering to the 65% who are visual learners. Students can choose specific sections and problem types, adjust difficulty levels, and navigate easily using a side menu. Praxis provides a free alternative to expensive tutoring. The platform's modern design, text to speech functionality, neomorphism and sans-serif fonts, ensures intuitive navigation and accessibility for all users, including those who are neurodivergent.

How we built it

Praxis was built using a combination of front-end and back-end technologies. The front end is designed to be simple and intuitive. The back end integrates AI-powered tutoring responses and generates easy-to-follow visualizations.

We utilized Flask for the backend API endpoints and JavaScript/React for the frontend interface. We also integrated the Manim Python library to generate animated visualizations for practice questions. To generate the scripts for animations and provide a virtual tutor to answer any follow-up questions during practice problems we leveraged the Perplexity Llama 3.1 Sonar model.

Challenges we ran into

Throughout the development of Praxis, we encountered some difficult challenges:

Installing various dependencies
Getting animations to work (ensuring proper path placement of visualization creation)
Choosing most optimal perplexity prompt format to correctly retrieve Manim script
Numerous API calls to successfully connect frontend to backend

Accomplishments that we're proud of

Overcoming technical challenges: successful API calls, making conversation format with perplexity AI more dynamic/intuitive
User-friendly/accessible user interface

What we learned

Connecting frontend and backend
Implementing findings from user interviews into the user interface

What's next for Praxis

Additional personalized features: user profiles to save and tailor to past questions/answers
Scale to other sections
Text-to-speech and accessibility features