A Korean veterinary licensing exam study platform built around question review, spaced repetition, and community correction.
KVLE turns exam preparation into a structured learning system: students can practice questions, revisit mistakes, search explanations, and use community notes to improve weak areas. The platform is also designed for editor-led review, so question quality and corrections can be managed as the bank grows.
Korean veterinary students preparing for the national licensing exam need a durable way to review past-style questions, track weak areas, and discuss explanations without losing context across scattered files or chat threads.
KVLE combines question browsing, quiz sessions, wrong notes, weakest-area practice, search, and D-day planning so studying becomes a daily loop rather than a one-off cram session.
The project includes Supabase schema work, review status metadata, admin queues, image triage, correction handling, and audit logs so the content pipeline can mature beyond a simple demo bank.
Students move through quiz sessions and question detail pages with subject-aware review.
Attempts, wrong notes, weakest-category practice, and search help students find what to revisit.
Comments, explanations, correction proposals, and suggestion boards capture community knowledge.
Admin screens support question review, reports, signup applications, user controls, and audit logs.