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📚 Personalized Learning Path Recommendation System

This project is an intelligent educational platform designed to recommend personalized study paths based on a learner’s current knowledge, selected goals, and quiz performance. It helps users navigate concepts in Data Structures, Algorithms, and other domains through adaptive assessments and knowledge graph-driven progression.


🚀 Features

  • 🔐 User & Admin Authentication
  • 🌐 Domain & Topic Selection Interface
  • 🧠 Multi-Level Assessments (Easy, Medium, Hard)
  • 📊 Progress Tracking & Feedback
  • 🧭 Knowledge Graph Integration to recommend logical next steps
  • 🤖 Fallback to AI (ChatGPT/Gemini) when topic content is unavailable
  • 💾 CACHE Database Support for managing questions, scores, and prerequisites

🧩 How It Works

  1. User Registration/Login

    • Choose a language and domain to begin.
  2. Initial Quiz (Quiz 1)

    • Basic-level assessment (loops, variables, syntax).
    • Failure → default roadmap; pass → continue to advanced stages.
  3. Knowledge Verification (Quiz 2 & 3)

    • Topic-level Q&A to validate claimed knowledge.
  4. Topic Interest & Prerequisite Quiz (Quiz 4)

    • Based on selected interest, the system tests prerequisite understanding.
  5. Personalized Recommendations

    • Uses quiz scores and knowledge graph traversal to suggest next concepts.
    • Shows what is mastered, what’s pending, and redirects to AI support if needed.

🗃️ Tech Stack

  • Frontend: React + Tailwind CSS
  • Backend: typescript+Node.js + Express
  • Database: MongoDB (CACHE structure)
  • Routing: React Router
  • AI Integration: ChatGPT / Gemini (planned)

🤝 Contributors ..Sai Deepak Nelluri (Project Lead) ..Gnaneshwar ..Deekshitha thotapally ..Subathra ..Hindu

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  • Jupyter Notebook 66.0%
  • TypeScript 24.4%
  • HTML 5.1%
  • Python 2.5%
  • CSS 1.7%
  • JavaScript 0.3%