Designed with Older Adults to SupportBetter Error Correction in SmartPhone Text Entry

Komninos, Andreas; Nicol, Emma; Dunlop, Mark

doi:10.1145/2786567.2793703

Cited by 19 publications

(10 citation statements)

References 13 publications

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“…For example children [21,2], older adults [27,12], users with motor disabilities [26], and users with visual impairments [3,23,17,19,22]. Further, interacting while in augmented or virtual reality poses many design challenges [4,15,16,20].…”

Section: Introductionmentioning

confidence: 99%

Ubiquitous Text Interaction

Vertanen

Montague

Dunlop

et al. 2017

Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems

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Computer-based interactions increasingly pervade our everyday environments. Be it on a mobile device, a wearable device, a wall-sized display, or an augmented reality device, interactive systems often rely on the consumption, composition, and manipulation of text. The focus of this workshop is on exploring the problems and opportunities of text interactions that are embedded in our environments, available all the time, and used by people who may be constrained by device, situation, or disability.This workshop welcomes all researchers interested in interactive systems that rely on text input or output. Participants should submit a short position statement outlining their background, past work, future plans, and suggesting a use-case they would like to explore in-depth during the workshop. During the workshop, small teams will form around common or compelling use-cases. Teams will spend time brainstorming, creating low-fidelity prototypes, and discussing their use-case with the group.Participants may optionally submit a technical paper for presentation as part of the workshop program. The workshop serves to sustain and build the community of text entry researchers who attend CHI. It provides an opportunity for new members to join this community, soliciting feedback from experts in a small and supportive environment.

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Section: Introductionmentioning

confidence: 99%

Ubiquitous Text Interaction

Vertanen

Montague

Dunlop

et al. 2017

Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems

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“…Co-creation and participatory design approaches have been successfully used for designing mobile systems for older adults, e.g. [8] and [11]. Design guidelines and checklists have been produced for the design of mobile phones for older adults [16] but have not considered broader systems issues.…”

Section: Related Workmentioning

confidence: 99%

Supporting Older Adults Using Privacy-Aware IoT Analytics

Mikusz

Davies

Shaw

et al. 2019

Living in the Internet of Things (IoT 2019)

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Mobile computing and the IoT offer the potential to provide new applications to support our ageing population. However, there has been little research into the implications for system design of supporting this specific user demographic. In this paper we consider these implications, focusing in particular on an architectural design that offers the potential for complex cross-device analytics while meeting the privacy and usability concerns of older adults.

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“…However, Kurniawan [17] reported that older adults usually dislike text-prediction features. Therefore, Komninos et al [18] proposed a keyboard that makes users aware of any errors through highlighting text.…”

Section: Text Entry For Older Adultsmentioning

confidence: 99%

Typing Tutor: Individualized Tutoring in Text Entry for Older Adults Based on Statistical Input Stumble Detection

Hagiya

Horiuchi

Yazaki

et al. 2018

Journal of Information Processing

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Many older adults are interested in smartphones. However, most of them encounter difficulties in selfinstruction and need support. Text entry, which is essential for various applications, is one of the most difficult operations to master. In this paper, we propose Typing Tutor, an individualized tutoring system for text entry that detects input stumbles using a statistical approach and provides instructions. By conducting two user studies, we clarify the common difficulties that novice older adults experience and how skill level is related to input stumbles with a 12-key layout for Japanese. Based on the study, we develop Typing Tutor to support learning how to enter text on a smartphone. A two-week evaluation experiment with novice older adults (65+) showed that Typing Tutor was effective in improving their text entry proficiency, especially in the initial stage of use. In addition, we demonstrate the applicability of Typing Tutor to other keyboards and languages with the QWERTY layout for Japanese and English.

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Designed with Older Adults to SupportBetter Error Correction in SmartPhone Text Entry

Cited by 19 publications

References 13 publications

Ubiquitous Text Interaction

Ubiquitous Text Interaction

Supporting Older Adults Using Privacy-Aware IoT Analytics

Typing Tutor: Individualized Tutoring in Text Entry for Older Adults Based on Statistical Input Stumble Detection

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