How do people type on mobile devices? Observations from a study with 37,000 volunteers

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Researchers

Research units

  • Swiss Federal Institute of Technology Zurich
  • University of Cambridge

Abstract

This paper presents a large-scale dataset on mobile text entry collected via a web-based transcription task performed by 37,370 volunteers. The average typing speed was 36.2 WPM with 2.3% uncorrected errors. The scale of the data enables powerful statistical analyses on the correlation between typing performance and various factors, such as demographics, finger usage, and use of intelligent text entry techniques. We report effects of age and finger usage on performance that correspond to previous studies. We also find evidence of relationships between performance and use of intelligent text entry techniques: auto-correct usage correlates positively with entry rates, whereas word prediction usage has a negative correlation. To aid further work on modeling, machine learning and design improvements in mobile text entry, we make the code and dataset openly available.

Details

Original languageEnglish
Title of host publicationProceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019
Publication statusPublished - 1 Oct 2019
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Human-Computer Interaction with Mobile Devices and Services - Taipei International Convention Center, Taipei, Taiwan, Republic of China
Duration: 1 Oct 20194 Oct 2019
Conference number: 21
https://mobilehci.acm.org/2019/

Conference

ConferenceInternational Conference on Human-Computer Interaction with Mobile Devices and Services
Abbreviated titleMobileHCI
CountryTaiwan, Republic of China
CityTaipei
Period01/10/201904/10/2019
Internet address

ID: 38210168