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WebAAS - Web Academic Advisory System

A modern, AI-powered academic advisory system that helps students make informed decisions about their university course selections through personalized assessments and recommendations.

Core Features

Smart Assessment Engine

  • Faculty-specific adaptive testing across core subjects
  • Randomized question delivery system
  • Comprehensive evaluation across 5 key subjects per faculty stream
  • Support for Science, Commerce, and Arts streams

AI-Powered Course Recommendations

  • Powered by Google's Generative AI (Gemini Pro)
  • Data-driven analysis of student performance
  • Personalized course recommendations based on strengths
  • Detailed insights into academic aptitude
  • Identification of both optimal and challenging course paths

User Management

  • Role-based access control (Students & Advisors)
  • Secure authentication via Clerk
  • Faculty-specific user profiles
  • Comprehensive user activity tracking

Technical Stack

  • Frontend: Next.js with Apollo Client
  • Backend: GraphQL API
  • Database: Prisma ORM
  • AI: Google Generative AI (Gemini Pro)
  • Authentication: Clerk
  • Language: TypeScript
  • Architecture: Domain-Driven Design

Key Benefits

  • For Students

    • Data-driven course recommendations
    • Comprehensive subject assessment
    • Personalized academic insights
    • Clear pathway visualization
  • For Advisors

    • AI-assisted advisory tools
    • Student performance analytics
    • Evidence-based recommendations
    • Streamlined advisory process

Implementation Highlights

  • Clean architecture with domain-driven design
  • Robust error handling and data validation
  • Secure API endpoints with proper authentication
  • Scalable database schema
  • Real-time data processing
  • Comprehensive test result analysis

Future Scope

  • Enhanced analytics dashboard
  • Machine learning model integration
  • Mobile application support
  • Integration with university admission systems
  • Extended subject coverage
  • Collaborative advisory features

Getting Started

Getting Started

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.

Deployment

You can access the site at https://web-aas.vercel.app/.

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