Date of Award
8-1-2018
Document Type
Masters Thesis
Degree Name
M.S.
Organizational Unit
Daniel Felix Ritchie School of Engineering and Computer Science, Computer Science
First Advisor
Nathan Sturtevant, Ph.D.
Second Advisor
Christopher Coleman
Third Advisor
Scott Leutenegger
Keywords
QWERTY keyboards, Keyboards, Mobile devices
Abstract
In this thesis we explore alternative keyboard layouts in hopes of finding one that increases the accuracy of text input on mobile touchscreen devices. In particular, we investigate if a single swap of 2 keys can significantly improve accuracy on mobile touchscreen QWERTY keyboards. We do so by carefully considering the placement of keys, exploiting a specific vulnerability that occurs within a keyboard layout, namely, that the placement of particular keys next to others may be increasing errors when typing. We simulate the act of typing on a mobile touchscreen QWERTY keyboard, beginning with modeling the typographical errors that can occur when doing so. We then construct a simple autocorrector using Bayesian methods, describing how we can autocorrect user input and evaluate the ability of the keyboard to output the correct text. Then, using our models, we provide methods of testing and define a metric, the WAR rating, which provides us a way of comparing the accuracy of a keyboard layout. After running our tests on all 325 2-key swap layouts against the original QWERTY layout, we show that there exists more than one 2-key swap that increases the accuracy of the current QWERTY layout, and that the best 2-key swap is i ↔ t, increasing accuracy by nearly 0.18 percent.
Publication Statement
Copyright is held by the author. User is responsible for all copyright compliance.
Rights Holder
Amanda Kirk
Provenance
Received from ProQuest
File Format
application/pdf
Language
en
File Size
90 p.
Recommended Citation
Kirk, Amanda, "Improving the Accuracy of Mobile Touchscreen QWERTY Keyboards" (2018). Electronic Theses and Dissertations. 1512.
https://digitalcommons.du.edu/etd/1512
Copyright date
2018
Discipline
Computer science