docs

Student Simulator Documentation

Welcome to the Student Simulator documentation! This collection of guides will help you understand and use the simulator effectively.

Quick Start

If you're new to the Student Simulator, start here:

1. Getting Started - Basic concepts and a simple example
2. Advanced Simulation - Large-scale simulations with complex skill hierarchies

What is the Student Simulator?

The Student Simulator is a Python library that models how students learn skills over time. It's designed for:

• Educational researchers studying learning progression
• Assessment developers testing item validity
• Data scientists analyzing educational data
• Curriculum designers understanding skill dependencies

Key Features

• Skill-based learning model with prerequisite relationships
• Realistic learning parameters based on educational research
• Flexible assessment generation with customizable item pools
• Student heterogeneity with random skill initialization
• Visualization tools for skill dependencies and mastery
• CSV export for analysis in other tools

Example Use Cases

• Learning Analytics: Track how students progress through skill hierarchies
• Assessment Design: Test the validity of new assessment items
• Curriculum Planning: Understand which skills are prerequisites for others
• Educational Research: Study learning patterns in large student populations

Getting Help

• Check the example scripts in .dev/ for working code
• Review the API documentation for detailed parameter descriptions
• Explore the generated CSV files to understand the data structure

Dependencies

The simulator requires:

• pydantic for data validation
• networkx for skill dependency graphs
• matplotlib for visualization (optional)
• pydot for graph layout (optional)

Install with: pip install pydantic networkx matplotlib pydot