adaptive-course-learner

What problem does it solve?

Adaptive course contexts are built by extracting and organizing knowledge from Canvas course and module content using reinforcement learning and perceptrons to deliver personalized learning contexts.

Core Features & Use Cases

• Content Fetcher: Retrieves course and module data from Canvas APIs, structuring learned knowledge stores.
• Perceptron Network: Extracts features from module items to inform context quality.
• RL Agent: Builds and refines contextual sequences to enhance study outcomes.
• Use Case: A learning analyst can assemble adaptive study guides by iteratively adding modules based on learned usefulness.

Quick Start

Create a project folder named adaptive-learner, install required packages, and run the learner to fetch a course and start building adaptive context.