EdRAGon

Inspiration

The inspiration behind EdRAGon stems from the need to enhance learning efficiency and productivity by leveraging user submissions to create personalized flashcards.

What it does

EdRAGon is a project that takes user submissions, extracts key information, and creates flashcards for productive learning. It also includes a productivity tracking feature to monitor and improve study habits.

How we built it

We primarily divided the project into several components. First, we designed a robust system to handle user submissions, processing them for document parsing to extract key information. This extracted information is then used to dynamically generate personalized flashcards for each user, which are stored in MongoDB Atlas for easy access and retrieval. To track productivity, we implemented a system that logs user interactions with the flashcards, such as time spent studying each card and the correctness of their responses. We used NextJS for a responsive and intuitive design for the user interface, with the front end communicating with the backend via RESTful APIs. The backend was built using Node.js and Flask, providing a scalable and efficient API layer, with MongoDB Atlas used as the database to store user data, flashcards, and productivity tracking information. We implemented user authentication using JSON Web Tokens (JWT) and followed best practices for data encryption and security. The application is deployed on AWS and Vercel, ensuring scalability and high availability, with continuous integration and deployment (CI/CD) pipelines used to automate the deployment process. Overall, EdRAGon's technical infrastructure is designed to provide a seamless and personalized learning experience while ensuring data security and scalability.

Challenges we ran into

One of the main challenges we faced was designing an efficient algorithm for extracting relevant information from user submissions while ensuring accuracy and relevance. Additionally, integrating the productivity tracking feature posed technical difficulties that we had to overcome.

Accomplishments that we're proud of

We are proud of creating a functional prototype of EdRAGon that demonstrates the potential for improving learning outcomes through personalized flashcards and productivity tracking.

What we learned

Through building EdRAGon, we learned valuable lessons about text parsing techniques, user interface design, and the importance of user feedback in refining our product. We also gained insights into the challenges and opportunities in the education technology (EdTech) sector.

What's next for EdRAGon

In the future, we plan to further enhance EdRAGon by adding more advanced parsing capabilities, improving the user interface for a seamless experience, and integrating additional features such as collaborative study sessions and progress analytics. We also aim to gather feedback from users to continuously iterate and improve our product.

Built With

• amazon-web-services
• atlas
• mongodb
• nextjs
• nextui
• node.js
• openai
• rest
• s3