Personalized Learning Pathway Generator

Personalized Learning Pathway Generator

Abstract: The Personalized Learning Pathway Generator creates customized learning paths for students based on their goals, interests, and current knowledge levels. Key features include:

  1. Goal-Oriented Pathway Generation: Creates a tailored learning path that aligns with the student’s academic or career goals.
  2. Progress Tracking and Adjustment: Monitors student progress and adjusts the learning path as needed to ensure optimal learning outcomes.
  3. Resource Recommendation: Suggests resources and activities that match the student’s learning style and preferences. The Personalized Learning Pathway Generator aims to guide students through a structured and efficient learning journey.

Software Requirements

  1. Operating System:
    • Windows 10 or later, macOS, or Linux
  2. Programming Languages:
    • Python 3.8+: For backend and ML model integration.
    • JavaScript (React.js): For front-end development.
  3. Frameworks and Libraries:
    • TensorFlow or Keras: For developing the learning pathway models.
    • Flask or Django: For API development.
    • React.js: For the front-end.
  4. Integrated Development Environment (IDE):
    • Visual Studio Code, PyCharm, or Jupyter Notebook.
  5. API and Backend Tools:
    • FastAPI or Flask: For RESTful APIs.
    • Docker: For containerization.
    • Git: For version control.
  6. Database:
    • PostgreSQL or MongoDB: For storing user data and learning pathways.
  7. Cloud Platform (Optional):
    • AWS or Azure: For hosting the application.

Hardware Requirements

  1. Development Machine:
    • Processor: Intel i5 or AMD Ryzen 5 or higher
    • RAM: 16 GB minimum (32 GB recommended)
    • Storage: SSD with at least 500 GB
    • GPU: Optional, but an NVIDIA GPU (e.g., RTX 3060) can accelerate model development.
  2. Server Hardware:
    • Processor: Intel Xeon or AMD EPYC
    • RAM: 64 GB minimum (128 GB recommended)
    • Storage: NVMe SSD with at least 1 TB
    • GPU: High-performance GPU like NVIDIA A100
  3. Cloud-based Infrastructure:
    • AWS EC2 P3 instances or equivalent.

Additional Considerations

  • Customization: Provide options for educators to customize the pathways generated by the tool to align with specific curricula.
  • Data Security: Implement strong security measures to protect sensitive user data, including encryption and access control.
  • Compliance: Ensure that the tool adheres to educational standards and regulations, especially in different regions.