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Student Feedback Form - MERN Stack Application

A comprehensive student feedback management system built with the MERN stack (MongoDB, Express.js, React, Node.js) featuring AI-powered insights and recommendations.

Features

Core Functionality

  • CRUD Operations: Complete Create, Read, Update, Delete functionality for students and feedback
  • Student Management: Add, edit, and manage student information
  • Feedback Collection: Comprehensive feedback forms with ratings and comments
  • Admin Dashboard: View and analyze all feedback submissions
  • Real-time Statistics: Live dashboard with feedback metrics

AI-Powered Features

  • Feedback Summarization: AI-generated summaries of student feedback
  • Course Recommendations: Personalized course suggestions based on feedback patterns
  • Insights Generation: AI analysis of overall feedback trends and patterns

Technical Features

  • Modern UI: Material-UI components with responsive design
  • Data Visualization: Interactive tables and charts
  • Form Validation: Client and server-side validation
  • Error Handling: Comprehensive error handling and user feedback

Tech Stack

Backend

  • Node.js - Runtime environment
  • Express.js - Web framework
  • MongoDB - Database
  • Mongoose - ODM for MongoDB
  • OpenAI API - AI-powered features
  • Express Validator - Input validation
  • CORS - Cross-origin resource sharing

Frontend

  • React - Frontend framework
  • Material-UI - UI component library
  • React Router - Client-side routing
  • Axios - HTTP client
  • MUI X Data Grid - Advanced data tables

Installation & Setup

Prerequisites

  • Node.js (v14 or higher)
  • MongoDB (local or cloud instance)
  • OpenAI API key (for AI features)

Backend Setup

  1. Install dependencies:

    npm install
  2. Environment Configuration: Create a .env file in the root directory:

    MONGODB_URI=mongodb://localhost:27017/student_feedback
    JWT_SECRET=your_jwt_secret_key_here
    OPENAI_API_KEY=your_openai_api_key_here
    PORT=5000
  3. Start the backend server:

    npm run dev

    The server will run on http://localhost:5000

Frontend Setup

  1. Navigate to client directory:

    cd client
  2. Install dependencies:

    npm install
  3. Start the React development server:

    npm start

    The frontend will run on http://localhost:3000

Database Setup

  1. Start MongoDB (if running locally):

    mongod
  2. The application will automatically create the database and collections when you first run it.

Usage

For Students

  1. Navigate to the Feedback Form page
  2. Select your student profile from the dropdown
  3. Fill in course details and instructor information
  4. Provide ratings (1-5 scale) for different aspects
  5. Add detailed comments about strengths and improvements
  6. Save as draft or submit the feedback

For Administrators

  1. Admin Dashboard: View all feedback submissions with statistics
  2. Student Management: Add, edit, or remove student profiles
  3. AI Insights: Generate AI-powered analysis of feedback patterns
  4. Course Recommendations: Get personalized course suggestions for students

API Endpoints

Students

  • GET /api/students - Get all students
  • POST /api/students - Create new student
  • PUT /api/students/:id - Update student
  • DELETE /api/students/:id - Delete student

Feedback

  • GET /api/feedback - Get all feedback
  • POST /api/feedback - Create new feedback
  • PUT /api/feedback/:id - Update feedback
  • DELETE /api/feedback/:id - Delete feedback
  • GET /api/feedback/stats/overview - Get feedback statistics

AI Features

  • POST /api/ai/summarize/:feedbackId - Generate AI summary
  • POST /api/ai/recommendations/:studentId - Get course recommendations
  • GET /api/ai/insights - Generate overall insights

Development

Running in Development Mode

# Terminal 1 - Backend
npm run dev

# Terminal 2 - Frontend
cd client && npm start

Production Build

# Build frontend
cd client && npm run build

# Start production server
npm start

About

A comprehensive student feedback management system built with the MERN stack (MongoDB, Express.js, React, Node.js) featuring AI-powered insights and recommendations.

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