Multimodal item feature extraction for K-12 math assessment. Analyze readability with math-aware normalization via textstat and NLTK, classify math content by Common Core State Standards for Mathematics domain, estimate cognitive load components, extract visual complexity features from images using OpenCV and Pillow, classify item images into 26 visual representation types with an instructional function label, and perform multimodal optical character recognition (OCR) through Gemini and OpenAI vision APIs.
Installation
pip install mathipy
With optional dependencies:
pip install mathipy[nlp] # readability (textstat, nltk)
pip install mathipy[vision] # visual analysis (opencv, pillow)
pip install mathipy[ocr] # OCR via vision LLMs (httpx)
pip install mathipy[documents] # document parsing (python-docx, pdfplumber)
pip install mathipy[all] # all features
From GitHub:
pip install git+https://github.com/mshin77/mathipy.git[all]
Getting Started
See Quick Start and Analyzing Math Items for tutorials.
Citation
- Shin, M. (2026). mathipy: Multimodal item feature extraction for K-12 math assessment (Python package version 0.3.0) [Computer software]. https://github.com/mshin77/mathipy
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