Skill Intelligence Meter is a comprehensive, next-generation Learning Management System (LMS) designed specifically to bridge the gap between college students and industry mentors. It provides a highly interactive and data-driven platform for tracking skills, attempting assessments, engaging in live classes, and preparing for real-world tech careers.
- Career GPS & Skill Roadmaps: Guided paths to help students understand what skills they need for their dream jobs.
- AI Skill Gap Analysis: Identifies missing competencies using AI and recommends personalized learning materials.
- Gamification Center: Engage with daily missions, earn badges, and track performance intelligence.
- Proctored Assessments:
- Timed MCQ and Coding assessments.
- Anti-Cheat System: Auto-submits if a student switches tabs more than 3 times.
- Pre-Assessment System Check: Validates internet connection speed before permitting entry.
- Full-screen lock during assessment attempts.
- Mock Interviews & Viva Practice: Features an AI-assisted practice mode that includes facial matching, voice matching, and live feedback.
- Skill-T-Meter: Participate in live, interactive presentations (similar to Mentimeter) with polls, word clouds, and real-time Q&A.
- Resume Builder & Project Portfolio: Keep track of achievements, badges, and projects in one centralized dashboard.
- Role-Based Dashboards: Tailored views for Admins, Sub-Admins, Managers, Mentors, and "Skill T Team" members.
- Staff Dashboard & Classes Management: Organize students, monitor progress, and manage class assignments effectively.
- Live Interactive Sessions (Skill-T-Meter): Create and run live interactive slideshows. Engage students in real-time and review metrics instantly.
- Assessment Management: Create, assign, and review student performance across various assessment types.
- Student Tracking: Monitor student progress, review coding approaches, and manage class assignments.
- Frontend: React.js, Vite, CSS (Vanilla + Modules), Lucide React (Icons)
- Backend: Node.js, Express.js (Running on port 5001)
- Real-time Communication: Socket.io (for Live Polling / Skill-T-Meter)
- Database: MongoDB (via Mongoose)
- Authentication: Firebase Auth (for secure login and user management)
Make sure you have Node.js installed on your machine.
git clone https://github.com/your-username/lms-skill-intelligence-meter.git
cd lms-skill-intelligence-meterBefore running the application, you need to set up environment variables.
- Backend: Create a
.envfile in thebackenddirectory withPORTandMONGO_URI. Also, place yourfirebase-service-account.jsonin thebackenddirectory. - Frontend: Create a
.envfile in thefrontenddirectory with yourVITE_FIREBASE_*configuration variables andVITE_API_URL.
Navigate to the backend directory, install dependencies, and start the server:
cd backend
npm install
npm start
# The backend will start running on http://localhost:5001Open a new terminal window, navigate to the frontend directory, install dependencies, and start the development server:
cd frontend
npm install
npm run dev- Anti-Tab Switching: The system strictly monitors visibility changes. After 3 tab-switches, the assessment is automatically submitted and the student is redirected to the dashboard.
- Network Speed Validation: Ensures students have a stable connection before starting critical assessments, preventing mid-exam disconnections.
- Biometric Pre-Checks: Uses webcam and microphone APIs for Facial Match and Voice Match before accessing specific tests or viva modes.
Contributions, issues, and feature requests are welcome! Feel free to check issues page.
This project is MIT licensed.