FFL: A Language and Live Runtime for Styling and Labeling Typeset Math Formulas

要旨

As interest grows in learning math concepts in fields like data science and machine learning, it is becoming more important to help broad audiences engage with math notation. In this paper, we explore how authoring tools can help authors better style and label formulas to support their readability. We introduce a markup language for augmenting formulas called FFL, or "Formula Formatting Language," which aims to lower the threshold to stylize and diagram formulas. The language is designed to be concise, writable, readable, and integrable into web-based document authoring environments. It was developed with an accompanying runtime that supports live application of augmentations to formulas. Our lab study shows that FFL improves the speed and ease of editing augmentation markup, and the readability of augmentation markup compared to baseline LaTeX tools. These results clarify the role tooling can play in supporting the explanation of math notation.

著者
Zhiyuan Wu
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Jiening Li
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Kevin Ma
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Hita Kambhamettu
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Andrew Head
University of Pennsylvania, Philadelphia, Pennsylvania, United States
論文URL

https://doi.org/10.1145/3586183.3606731

会議: UIST 2023

ACM Symposium on User Interface Software and Technology

セッション: Data Dreamers: Math, Stats and Visualization

Gold Room
6 件の発表
2023-11-01 18:00:00
2023-11-01 19:20:00