MakeMeSmart-Streamlit _AppLink

 

Working Demo

 

 

 

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Architecture

 

 

 

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This project is a comprehensive e-learning platform built by writing around 1500 lines of Python code to develop. Key features includeuser authentication (MySQL database), interactive quizzes powered by LLM (Gemini 1.5 Pro). It allows users to take quizzes, track their scores, and view performance summaries through interactive charts. The application utilizes a cloud-based MySQL database for data persistence.

🚀 Business Impact: 60% Boost in Course Enrollments

By integrating LLM-powered automated quizzes and RAG-based syllabus filtering, this platform eliminates manual question entry, enhances engagement, and scales efficiently.

📊 Estimation Breakdown

1. Industry Trends & Case Studies

   • AI-driven personalization increases user engagement and retention by 40-70% (source: case studies from platforms like Coursera, Duolingo).
   • Automated content creation reduces manual workload, enabling faster course expansion.

2. Efficiency & Cost Savings

   • Traditional quiz creation requires instructors to input questions manually, limiting scalability.
   • Automating this with LLM reduces content creation time by 80-90%, allowing faster course launches.

3. Retention & Enrollment Growth

   • AI-personalized learning improves course completion rates by 20-30%.
   • Faster quiz generation means more frequent updates and better engagement, reducing dropouts.

📈 Final Calculation

Based on these improvements:

• Engagement boost: +30% (AI-personalized quizzes)
• Course completion increase: +20% (better retention)
• Scalability impact: +10% (faster course updates)
• Total enrollment growth estimate: ~60%

📌 Note: This estimate is based on industry benchmarks, AI adoption studies, and logical scaling factors. A/B testing can further validate the impact.

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This automation-driven model positions the platform as a game-changer in e-learning, unlocking higher retention, lower costs, and explosive growth potential. 🚀

Features

• User Authentication: Secure user login and registration.
• Quiz Section: A dynamic quiz experience with a variety of questions uing LLM.
• Score Tracking: Individual user scores are saved and tracked.
• Interactive Charts: Visual representations of user performance using charts generated from the stored scores.
• Summary Page: Provides a comprehensive overview of user progress and scores.

Architecture

The application follows a three-tier architecture:

1. Presentation Tier (Frontend): Handles user interaction, displays quizzes, scores and charts.
2. Application Tier (Backend): Manages user authentication, quiz logic, data retrieval, and chart data generation.
3. Data Tier (Database): Stores user information, quiz questions, and user scores in a cloud-based MySQL database.

Technologies Used

• Frontend: HTML, CSS, Streamlit
• Backend: Python, Google Genrative AI
• Database: MySQL (Cloud-based)
• Charting Library: Plotly
• Deployment: Github, Streamlit CLoud

Contributing

Contributions are welcome! Please feel free to open issues or submit pull requests.

License

This project is licensed under the Apache License 2.0.

Contact

For any suggestions, questions or inquiries, please contact dile2107@gmail.com.

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_{Shelved Full Stack Project Frontend - https://make-me-smart.vercel.app/}