Voca Web
Overview
A vocabulary learning platform that combines a Chrome Extension for word collection with a web application for systematic study. Save unfamiliar words while browsing, then review them using spaced repetition algorithms.
Features
Word Collection
Right-click any word on any webpage to save it instantly through the Chrome Extension. Words are saved with their context for better retention.
Study Mode
Flashcard-based learning system implementing spaced repetition algorithms. Cards show the word first, then reveal definitions and example sentences.
Progress Tracking
Visual dashboards display daily progress, study streaks, and learning statistics to help monitor improvement over time.
Word Groups
Organize vocabulary into thematic groups for focused study sessions. Each group can be studied independently.
IPA Pronunciation
International Phonetic Alphabet notation provided for accurate pronunciation learning.
Technical Implementation
Architecture
- Frontend: Next.js 15 with TypeScript and Tailwind CSS
- Database: PostgreSQL with Prisma ORM
- Extension: Chrome Extension Manifest V3
- Deployment: Docker Compose for containerized deployment
Key Components
- Spaced repetition algorithm for optimal review scheduling
- Real-time synchronization between extension and web app
- Responsive design supporting desktop and mobile browsers
- Dark mode support for reduced eye strain
Usage Flow
- Install the Chrome Extension from the Chrome Web Store
- Create an account on the web application
- Save words by right-clicking while browsing
- Review saved words in the web app's study mode
- Track progress through the dashboard
Development Notes
The project addresses the gap between word collection tools (which lack study features) and vocabulary apps (which make adding words cumbersome). By integrating both aspects, it creates a seamless learning workflow.
The spaced repetition implementation uses a modified SM-2 algorithm, adjusting review intervals based on user performance. This ensures efficient memorization without overwhelming users with too many reviews.