AI-Powered Academic Performance & Guidance Platform

AcadBoost AI is a full-stack web application that helps students improve their academic performance through AI-driven insights and personalized learning recommendations. The platform analyzes student scores, identifies weak areas, and generates customized study roadmaps, timetables, and learning resources.

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Features

Student & Faculty Authentication

• Secure login and registration using JWT authentication.
• Role-based access for students and faculty.
• Password encryption using bcrypt.

Academic Performance Tracking

• Track scores across:

  • Operating Systems (OS)
  • Computer Networks (CN)
  • Database Management Systems (DBMS)
  • Object-Oriented Programming (OOPS)
  • Data Structures & Algorithms (DSA)
  • Quantitative Aptitude (QA)

• Performance classification as High, Medium, or Low.

AI-Powered Chatbot

• Provides academic guidance and performance insights.
• Answers student queries related to subjects and study plans.
• Generates personalized recommendations using LLaMA models.

Personalized Study Roadmaps

• Subject-wise study plans based on performance.
• Weekly goals and improvement strategies.
• Focus on weak topics and skill development.

AI Study Timetable

• Generates Daily, Weekly, and Monthly study schedules.
• Allocates more study time to weaker subjects.
• Includes realistic study sessions and breaks.

Learning Resources

• Curated study materials and practice platforms.
• Recommended YouTube playlists, notes, and tutorials.
• Subject-specific learning resources.

Analytics Dashboard

• Visual representation of academic performance.
• Subject-wise comparison charts.
• Progress tracking and score trends.

Faculty Management

• View and update student marks.
• Automatic recalculation of performance levels.
• Manage academic records efficiently.

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Tech Stack

Frontend

• React.js
• Vite
• Tailwind CSS
• Recharts
• Framer Motion
• Axios

Backend

• Node.js
• Express.js
• JWT Authentication
• bcrypt

Database

• MongoDB Atlas
• Mongoose

AI Integration

• Groq API
• LLaMA 3.3 70B
• LLaMA 3.1 8B

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System Workflow

1. Student registers and logs in.

2. Academic scores are stored in MongoDB.

3. The system analyzes subject performance.

4. AI generates:

   • Study Roadmaps
   • Study Timetables
   • Learning Resources
   • Performance Insights

5. Students monitor progress through an interactive dashboard.

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Project Structure

AcadBoostAI/
├── client/
│   ├── src/
│   ├── public/
│   └── package.json
│
├── server/
│   ├── controllers/
│   ├── models/
│   ├── routes/
│   ├── services/
│   ├── utils/
│   └── server.js
│
└── README.md

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Installation

Clone the Repository

git clone <repository-url>
cd AcadBoostAI

Install Backend Dependencies

cd server
npm install

Install Frontend Dependencies

cd ../client
npm install

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Environment Variables

Create a .env file inside the server folder:

MONGODB_URI=your_mongodb_connection_string
PORT=3000
JWT_SECRET=your_jwt_secret
GROQ_API_KEY=your_groq_api_key

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Run the Project

Start Backend Server

cd server
node server.js

Start Frontend

cd client
npm run dev

Frontend: http://localhost:5173

Backend: http://localhost:3000

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Future Enhancements

• Real-time performance monitoring
• Attendance tracking
• Assignment management
• AI-powered mock tests
• Mobile application support

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Author

Adarsh Pendyala

B.Tech CSE (Data Science) VNR Vignana Jyothi Institute of Engineering and Technology

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License

This project is developed for educational and research purposes.