Introducing Handwriting into a Multimodal LATEX Formula Editor

Handwriting has been shown to be a useful input modality for math. However, math recognizers are imperfect, especially when recognizing complex expressions. Instead of improving the recognizer itself, we explore ways to best visualize the recognizer\u27s output to help the user fix recognition mistakes more efficiently. To do this, we propose changes to the visual editing operations in MathDeck, a math-aware search engine and formula editor, as well as the addition of an n-best list of results for each symbol in the recognizer\u27s output. We present two experiments to help us find good ways to help users fix errors in the recognizer, and to test whether these changes help novices input formulas more efficiently than they would if they did not have handwriting as an input modality. In the first experiment, users had the option to fix errors with an in-place drop-down menu of alternate symbols, a side symbol correction panel, or by typing the symbols themselves or dragging them from a symbol palette. In our experiment, most users preferred to fix the errors manually by typing the correct symbols or using the symbol palette. In the second experiment, participants entered formulas using handwriting and/or LaTeX. We found evidence that suggests that novices can input formulas faster when they have access to handwriting, but experts still do better when they can just type LaTeX

SOMNIUM VR Demo

Driven by a desire to overcome challenges from COVID-19 and to explore theatre in a new direction, the fall production of SOMNIUM at the Rochester Institute of Technology took on a completely new concept. Instead of a more traditional, physical theatre piece as it was originally envisioned, the SOMNIUM RIT Team decided to leap into the unknown, and explore a unique blend of devised theatre, film, and 3D game design. This demo allowed audiences to view a short trailer of the production and speak with members of the design team