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

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cam.issuedOnline2019-10
dc.contributor.authorPalin, K
dc.contributor.authorFeit, AM
dc.contributor.authorKim, S
dc.contributor.authorKristensson, PO
dc.contributor.authorOulasvirta, A
dc.contributor.orcidKristensson, Per Ola [0000-0002-7139-871X]
dc.date.accessioned2020-02-12T15:17:37Z
dc.date.available2020-02-12T15:17:37Z
dc.date.issued2019
dc.description.abstract© 2019 Association for Computing Machinery. 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.
dc.identifier.doi10.17863/CAM.49112
dc.identifier.isbn9781450368254
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/302037
dc.publisherACM
dc.publisher.urlhttp://dx.doi.org/10.1145/3338286.3340120
dc.subjectMobile text entry
dc.subjectword prediction
dc.subjectauto-correct
dc.titleHow do people type on mobile devices? Observations from a study with 37,000 volunteers
dc.typeConference Object
dcterms.dateAccepted2019-06-07
prism.publicationDate2019
prism.publicationNameProceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019
pubs.conference-nameMobileHCI '19: 21st International Conference on Human-Computer Interaction with Mobile Devices and Services
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/R004471/1)
rioxxterms.licenseref.startdate2019-10-01
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.typeConference Paper/Proceeding/Abstract
rioxxterms.versionAM
rioxxterms.versionofrecord10.1145/3338286.3340120
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