College Review Nepal
The premier platform for finding and reviewing educational institutions across Nepal.
Project Overview
CollegeReviewNepal is a student-first platform that helps Nepali students explore colleges through real experiences instead of marketing claims. It brings together structured reviews, ratings, and community discussions so students can compare institutions, ask questions, and make informed decisions—all in one place.
Why I built this
Choosing a college in Nepal often means relying on scattered opinions, social media posts, or incomplete official websites. There was no trusted, centralized space where students could hear directly from other students, ask honest questions, or compare colleges transparently.
What It Solves
Integrates structured, student-driven reviews and ratings that are easy to compare.
Enables prospective students to ask targeted questions and participate in discussions with students who are already inside those institutions.
Introduces moderation, reporting, and review controls to reduce spam, abuse, and misinformation while keeping discussions authentic.
Aggregates student sentiment into measurable data, giving colleges a clearer picture of how they are perceived over time.
System Architecture
Built as a single Next.js App Router application that serves both server-rendered pages and backend API routes from the same codebase.
Colleges, reviews, forums, and reports are modeled with clear relationships, validation rules, and aggregation logic to keep data consistent and reliable.
Visitors, verified students, and admins have different capabilities, enforced at both the UI and API level to protect sensitive actions.
Reporting pipelines, review blocking, and admin dashboards are baked into the system to maintain content quality as the platform scales.
Uses server components and dynamic metadata so college pages, reviews, and discussions are fast, indexable, and discoverable.
Learnings
Building CollegeReviewNepal highlighted how trust must be engineered, not assumed, in user-generated platforms. I learned how to design moderation-first systems where reporting, review blocking, and admin oversight are core workflows rather than afterthoughts. The project also deepened my understanding of modeling community data—ratings, votes, discussions, and sentiment—in a way that stays consistent and meaningful as activity grows. Most importantly, it showed how transparent feedback loops and carefully scoped user roles can turn raw opinions into reliable, decision-making signals.