research-article

Why Is Gesture Typing Promising for Older Adults?: Comparing Gesture and Tap Typing Behavior of Older with Young Adults

Authors:

Xiaojun BiAuthors Info & Claims

ASSETS '18: Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility

Pages 271 - 281

https://doi.org/10.1145/3234695.3236350

Published: 08 October 2018 Publication History

Abstract

Gesture typing has been a widely adopted text entry method on touchscreen devices. We have conducted a study to understand whether older adults could gesture type, how they type, what are the strengths and weaknesses of gesture typing, and how to further improve it. By logging stroke-level interaction data and leveraging the existing modeling tools, we compared the gesture and tap typing behavior of older adults with young adults. Our major finding is promising and encouraging. Gesture typing outperformed the typical tap typing for older adults, and was very easy for them to learn. The gesture typing input speed was 15.28% higher than that of tap typing for 14 older adults who had none gesture typing experience in the past. One of the main reasons was that older adults adopted the word-level inputting strategy in gesture typing, while often used the letter-level correction strategy in tap typing. Compared with young adults, older adults exhibited little degradation in gesture accuracy. Our study also led to implications on how to further improve gesture typing for older adults.

References

[1]

Anderson, M. and Perrin, A., 2017. Tech Adoption Climb among Older Adults. Pew Research Center.

[2]

Azenkot, S. and Zhai, S., 2012 Touch Behavior with Different Postures on Soft Smartphone Keyboards. In Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services. ACM, 251--260.

Digital Library

[3]

Bi, X., Azenkot, S., Partridge, K., and Zhai, S., 2013. Octopus: Evaluating Touchscreen Keyboard Correction and Recognition Algorithms Via. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 543--552.

Digital Library

[4]

Bi, X., Chelba, C., Ouyang, T., Partridge, K., and Zhai, S., 2012 Bimanual Gesture Keyboard. In Proceedings of the 25th annual ACM symposium on User interface software and technology. ACM, 137--146.

Digital Library

[5]

Cao, X. and Zhai, S., 2007. Modeling Human Performance of Pen Stroke Gestures. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 1495--1504.

Digital Library

[6]

Findlater, L. and Wobbrock, J., 2012. Personalized Input: Improving Ten-Finger Touchscreen Typing through Automatic Adaptation. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 815--824.

Digital Library

[7]

Findlater, L., Wobbrock, J. O., and Wigdor, D., 2011. Typing on Flat Glass: Examining Ten-Finger Expert Typing Patterns on Touch Surfaces. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 2453--2462.

Digital Library

[8]

Fitts, P. M., 1954. The Information Capacity of the Human Motor System in Controlling the Amplitude of Movement. Journal of Experimental Psychology 47, 381--391.

[9]

Fowler, A., Partridge, K., Chelba, C., Bi, X., Ouyang, T., and Zhai, S., 2015. Effects of Language Modeling and Its Personalization on Touchscreen Typing Performance. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 649--658.

Digital Library

[10]

Goel, M., Jansen, A., Mandel, T., Patel, S. N., and Wobbrock, J. O., 2013. Contexttype: Using Hand Posture Information to Improve Mobile Touch Screen Text Entry. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 2795--2798.

Digital Library

[11]

Goodman, J., Venolia, G., Steury, K., and Parker, C., 2002. Language Modeling for Soft Keyboards. In Proceedings of the 7th international conference on Intelligent user interfaces. ACM, 194--195.

Digital Library

[12]

Hagiya, T., Horiuchi, T., and Yazaki, T., 2016. Typing Tutor: Individualized Tutoring in Text Entry for Older Adults Based on Input Stumble Detection. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 733--744.

Digital Library

[13]

Hawthorn, D., 2006. Designing Effective Interfaces for Older Users.

[14]

Ketcham, C. J., Seidler, R. D., Van Gemmert, A. W. A., and Stelmach, G. E., 2002. Age-Related Kinematic Differences as Influenced by Task Difficulty, Target Size, and Movement Amplitude. The Journals of Gerontology: Series B 57, 1, P54-P54.

[15]

Ketcham, C. J. and Stelmach, G., 2002. Motor Control of Older Adults. {in Ekerdt D.J., Applebaum R.A., Holden K.C., Post S.G., Rockwood K., Schulz R., Sprott R.L., and Uhlenberg P. (Eds.) }. Encyclopedia of Aging.

[16]

Ketcham, C. J. and Stelmach, G. E., 2004. Movement Control in the Older Adult. National Research Council (US) Steering Committee for the Workshop on Technology for Adaptive Aging; Pew RW, Van Hemel SB, editors. Technology for Adaptive Aging 3.

[17]

Kobayashi, M., Hiyama, A., Miura, T., Asakawa, C., Hirose, M., and Ifukube, T., 2011. Elderly User Evaluation of Mobile Touchscreen Interactions, P. CAMPOS, N. GRAHAM, J. JORGE, N. NUNES, P. PALANQUE and M. WINCKLER Eds. Springer Berlin Heidelberg, Berlin, Heidelberg, 83--99.

Digital Library

[18]

Komninos, A., Nicol, E., and Dunlop, M. D., 2015. Designed with Older Adults to Supportbetter Error Correction in Smartphone Text Entry: The Maxiekeyboard. In Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct. ACM, 797--802.

Digital Library

[19]

Kristensson, P.-O. and Zhai, S., 2004. Shark2: A Large Vocabulary Shorthand Writing System for Pen-Based Computers. In Proceedings of the 17th annual ACM symposium on User interface software and technology. ACM, 43--52.

Digital Library

[20]

Kurniawan, S., 2008. Older People and Mobile Phones: A Multi-Method Investigation. International Journal of Human-Computer Studies 66, 12, 889--901.

Digital Library

[21]

MacKenzie, I. S., 2015. A Note on Calculating Text Entry Speed.

[22]

MacKenzie, I. S. and Soukoreff, R. W., 2003. Phrase Sets for Evaluating Text Entry Techniques. In Proceedings of the CHI'03 extended abstracts on Human factors in computing systems. ACM, 754--755.

Digital Library

[23]

Markussen, A., Jakobsen, M. R., and Hornbæk, K., 2014. Vulture: A Mid-Air Word-Gesture Keyboard. In Proceedings of the 32nd annual ACM conference on Human factors in computing systems. ACM, 1073--1082.

Digital Library

[24]

Matias, E., MacKenzie, I. S., and Buxton, W., 1993. Half-Qwerty: A One-Handed Keyboard Facilitating Skill Transfer from Qwerty. In Proceedings of the INTERACT '93 and CHI '93 Conference on Human Factors in Computing Systems. ACM, 88--94.

Digital Library

[25]

Mitzner, T. L., Smarr, C.-A., Rogers, W. A., and Fisk, A. D., 2015. Considering Older Adults' Perceptual Capabilities in the Design Process, R.R. HOFFMAN, P.A. HANCOCK, M.W. SCERBO, R. PARASURAMAN and J.L.E. SZALMA Eds. Cambridge University Press, 1051--1079.

[26]

Nicolau, H. and Jorge, J., 2012. Elderly Text-Entry Performance on Touchscreens. In Proceedings of the 14th international ACM SIGACCESS conference on Computers and accessibility. ACM, 127--134.

Digital Library

[27]

Ortman, J. M., Velkoff, V. A., and Hogan, H., 2014. An Aging Nation: The Older Population in the United States. United States Census Bureau, Economics and Statistics Administration, US Department of Commerce.

[28]

Patel, I. and West, S. K., 2007. Presbyopia: Prevalence, Impact, and Interventions. Community Eye Health 20, 63, 40--41.

[29]

Riddle, D. R., 2006. Brain Aging: Models, Methods & Mechanisms. Taylor & Francis.

[30]

Rodrigues, l., Carreira, M., Gon, D., and alves, 2016. Enhancing Typing Performance of Older Adults on Tablets. Univers. Access Inf. Soc. 15, 3, 393--418.

Digital Library

[31]

Smith, A. L. and Chaparro, B. S., 2015. Smartphone Text Input Method Performance, Usability, and Preference with Younger and Older Adults. Human factors 57, 6, 1015--1028.

[32]

Vertanen, K., Memmi, H., Emge, J., Reyal, S., and Kristensson, P. O., 2015. Velocitap: Investigating Fast Mobile Text Entry Using Sentence-Based Decoding of Touchscreen Keyboard Input. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 659--668.

Digital Library

[33]

Voelcker-Rehage, C., 2008. Motor-Skill Learning in Older Adults-a Review of Studies on Age-Related Differences. European Review of Aging and Physical Activity 5, 1, 5.

[34]

Yeo, H.-S., Phang, X.-S., Castellucci, S. J., Kristensson, P. O., and Quigley, A., 2017. Investigating Tilt-Based Gesture Keyboard Entry for Single-Handed Text Entry on Large Devices. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 4194--4202.

Digital Library

[35]

Yi, X., Yu, C., Shi, W., Bi, X., and Shi, Y., 2017. Word Clarity as a Metric in Sampling Keyboard Test Sets. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 4216--4228.

Digital Library

[36]

Yin, Y., Ouyang, T. Y., Partridge, K., and Zhai, S., 2013. Making Touchscreen Keyboards Adaptive to Keys, Hand Postures, and Individuals: A Hierarchical Spatial Backoff Model Approach. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 2775--2784.

Digital Library

Cited By

Zhang DLi ZAshok VSeiple WRamakrishnan IBi X(2024)Accessible Gesture Typing on Smartphones for People with Low VisionProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676447(1-11)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676447
Jin X(2024)Empowering Autonomous Digital Learning for Older AdultsExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3651133(1-6)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3651133
Jin XTong WWei XWang XKuang EMo XQu HFan M(2024)Exploring the Opportunity of Augmented Reality (AR) in Supporting Older Adults to Explore and Learn Smartphone ApplicationsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3641901(1-18)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3641901
Show More Cited By

Index Terms

Why Is Gesture Typing Promising for Older Adults?: Comparing Gesture and Tap Typing Behavior of Older with Young Adults
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction devices
      1. Graphics input devices
    2. Interaction paradigms
      1. Graphical user interfaces

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cover image ACM Conferences

ASSETS '18: Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility

October 2018

508 pages

ISBN:9781450356503

DOI:10.1145/3234695

General Chair:
Faustina Hwang
University of Reading, UK
,
Program Chairs:
Joanna McGrenere
University of British Columbia, Canada
,
David Flatla
University of Guelph, Canada

Copyright © 2018 ACM.

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Published: 08 October 2018

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ASSETS '18: The 20th International ACM SIGACCESS Conference on Computers and Accessibility

October 22 - 24, 2018

Galway, Ireland

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ASSETS '18 Paper Acceptance Rate 28 of 108 submissions, 26%;

Overall Acceptance Rate 436 of 1,556 submissions, 28%

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Cited By

Zhang DLi ZAshok VSeiple WRamakrishnan IBi X(2024)Accessible Gesture Typing on Smartphones for People with Low VisionProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676447(1-11)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676447
Jin X(2024)Empowering Autonomous Digital Learning for Older AdultsExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3651133(1-6)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3651133
Jin XTong WWei XWang XKuang EMo XQu HFan M(2024)Exploring the Opportunity of Augmented Reality (AR) in Supporting Older Adults to Explore and Learn Smartphone ApplicationsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3641901(1-18)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3641901
Cui WLiu RLi ZWang YWang AZhao XRashidian SBaig FRamakrishnan IWang FBi X(2023)GlanceWriter: Writing Text by Glancing Over Letters with GazeProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581269(1-13)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581269
Li QZeng HPeng ZMa X(2021)Understanding Players’ Interaction Patterns with Mobile Game App UI via VisualizationsProceedings of the Ninth International Symposium of Chinese CHI10.1145/3490355.3490357(9-21)Online publication date: 16-Oct-2021
https://dl.acm.org/doi/10.1145/3490355.3490357

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