Teaching Mathematics Through Image Manipulation

Year: 2013 Authors: Patrick Honner

Core claim

Mathematical image processing with Python can create engaging, authentic learning experiences for secondary students across mathematics, computer science, and art.

Topics

digital image processing, mathematical transformations, project-based learning, secondary mathematics education

Domains

trigonometry, algebra, calculus, functions, digital art, computer graphics, visual manipulation, STEM education

Methods

Python scripting, pixel-level transformations, modular arithmetic, image composition

Media

Python, PIL, Sage, photographs

Source status

This page publishes metadata and extracted analytical signals only. Raw PDF and full OCR text are kept local for now.