Smartphone input method performance, satisfaction, workload, and preference with younger and older novice adults
type: CreativeWork
description: Smartphones have dominated the American mobile phone market since mid-2012 (Nielsen, 2012). Forty-five percent of American adults own smartphones (Smith, 2012), and report frequently using their devices for the same tasks: text messaging, emailing, and social networking (comScore, 2013), all of which are dependent on text entry. Hardware and/or software text input options are available, but recently vendors have begun to abandon physical keyboards in their device portfolios. Empirical research does not indicate, comparatively, which smartphone text entry methods are the fastest, most accurate, and most preferred by consumers. Furthermore, potential relationships that users' anthropometry, voice qualities and age-related limitations may have with the accuracy and satisfaction of these input methods have not been addressed. Two experiments explored the impact that five frequently used smartphone input methods (physical and onscreen Qwerty keyboards, tracing, handwriting, and voice recognition) had on novice user performance, perceived workload, satisfaction, and preference. Relationships between anthropometry, speech and voice qualities with the input methods were also examined. Results from Study 1 demonstrate that younger adults were fastest with voice recognition, but committed fewer errors, reported lower workload, higher satisfaction, and preference with the physical keyboard. Results from Study 2 revealed that older adults were fastest, most accurate, reported lower workload, higher satisfaction and preference for voice recognition. A comparison between age groups suggested that older adults were generally slower and committed more errors. However, performance differences were not found between age groups for voice recognition entry rates and word error rates, as well as for physical Qwerty uncorrected error rates. Additionally, both groups had similar satisfaction and preference ratings for most methods.
abstract: Smartphones have dominated the American mobile phone market since mid-2012 (Nielsen, 2012). Forty-five percent of American adults own smartphones (Smith, 2012), and report frequently using their devices for the same tasks: text messaging, emailing, and social networking (comScore, 2013), all of which are dependent on text entry. Hardware and/or software text input options are available, but recently vendors have begun to abandon physical keyboards in their device portfolios. Empirical research does not indicate, comparatively, which smartphone text entry methods are the fastest, most accurate, and most preferred by consumers. Furthermore, potential relationships that users' anthropometry, voice qualities and age-related limitations may have with the accuracy and satisfaction of these input methods have not been addressed. Two experiments explored the impact that five frequently used smartphone input methods (physical and onscreen Qwerty keyboards, tracing, handwriting, and voice recognition) had on novice user performance, perceived workload, satisfaction, and preference. Relationships between anthropometry, speech and voice qualities with the input methods were also examined. Results from Study 1 demonstrate that younger adults were fastest with voice recognition, but committed fewer errors, reported lower workload, higher satisfaction, and preference with the physical keyboard. Results from Study 2 revealed that older adults were fastest, most accurate, reported lower workload, higher satisfaction and preference for voice recognition. A comparison between age groups suggested that older adults were generally slower and committed more errors. However, performance differences were not found between age groups for voice recognition entry rates and word error rates, as well as for physical Qwerty uncorrected error rates. Additionally, both groups had similar satisfaction and preference ratings for most methods.
author: Smith, Amanda Lynn
date published: 2013-05
date modified: 2026-07-24T06:06:11Z
provider: Wichita State University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Wichita State University