Developed by: Daniel, Ahmad, Samiha, and Mahamud
Many students face challenges organizing and processing large volumes of study material, particularly when preparing for exams. Traditional study methods, like reviewing static documents, can be repetitive and less engaging, often leading to poor retention.
Quizify addresses this by using AI to transform uploaded class documents (e.g., PDFs) into interactive quizzes and flashcards, making study sessions more engaging and effective.
- Interactive Learning: Converts uploaded study documents into personalized quizzes and flashcards.
- Customized Focus: Generates quizzes tailored to each user's study material, helping to highlight key concepts and improve retention.
- Frontend: Next.js, React
- Backend: Next.js, TypeScript
- Database: Supabase (PostgreSQL)
- AI Integration: OpenAI + LangChain (using the GPT-4o-mini model with structured outputs)
- Upload Documents: Users can upload class notes or study material.
- AI Quiz Generation: AI processes the material and generates quizzes and flashcards.
- User-Friendly Interface: Built with Next.js for fast and responsive performance.
- Authentication Issues: Integrating user authentication with Supabase presented some challenges and required additional troubleshooting.
- New Technologies: Some team members were new to tools like Next.js and LangChain, which required time to learn and adapt.
- Functional Web Application: Successfully built and launched Quizify within the hackathon timeframe.
- AI-Powered Interactivity: Integrated OpenAI capabilities to create interactive and effective study tools.
- Collaboration: Enhanced teamwork skills through effective communication and support.
- Technical Growth: Gained practical experience in Next.js, LangChain, and Supabase, broadening our technological proficiency.
- Real-Time Quiz Mode: Implement a real-time mode for students to take quizzes collaboratively with friends or classmates.
- Group Study Support: Facilitate group study sessions and friendly competitions to increase engagement and knowledge retention further.
First, run the development server:
npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun dev
Open http://localhost:3000 with your browser to see the result.