CodeAssist: AI-Driven Hyper-Personalized Learning Ecosystem

🚀 Overview

CodeAssist is an AI-powered learning ecosystem that dynamically curates problem sets, blogs, and challenges based on real-time user performance analysis.

🎯 Key Features

🔹 AI-Driven Recommendation Engine

• Dynamically selects problem sets, blogs, and challenges based on real-time user performance.
• Adapts to individual learning styles and capabilities.

🔹 Scientifically-Backed Mini-Games

• Assesses cognitive abilities like:
  • Problem-solving speed
  • Logical reasoning
  • Memory retention
  • Multitasking efficiency

🔹 Smart Problem Assistance with Echo

If users get stuck, Echo suggests:

• Problem Tags
• Similar Problems
• Relevant Blogs

How It Works:

• Text vectorization is performed on 2500+ problems from various platforms.
• Cosine similarity is used to find the closest vector to the input query.
• Echo provides context-aware recommendations to help users solve problems efficiently.

🔹 Circadian Rhythm-Based Scheduling

• Adapts problem scheduling to a user’s biological clock:
  • Mornings: Memory-intensive tasks.
  • Evenings: Creative problem-solving tasks.

🔹 Progressive Analytics Dashboard (TODO)

• Provides users with behavioral insights, including:
  • Completion rates
  • Accuracy levels
  • Average session time
  • Participation trends
  • Focus levels & problem-solving habits

🔹 Future Scope

• Cognitive fatigue tracking to optimize learning breaks.
• Advanced behavioral analytics for deeper insights.

🔹 UI Snapshots & Screencasts

https://github.com/user-attachments/assets/daa4fd1a-f89d-404e-8e75-f9805cf45e8f

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Contributing

Contributions are welcome! Feel free to open an issue or submit a pull request.

📞 Contact

For any inquiries, reach out at: aryansatija2003@gmail.com