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Input Accessibility: A Large Dataset and Summary Analysis of Age, Motor Ability and Input Performance

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Published:29 October 2020Publication History

ABSTRACT

Age and motor ability are well-known to impact input performance. Past work examining these factors, however, has tended to focus on samples of 20-40 participants and has binned participants into a small set of age groups (e.g., “younger” vs. “older”). To foster a more nuanced understanding of how age and motor ability impact input performance, this short paper contributes: (1) a dataset from a large-scale study that captures input performance with a mouse and/or touchscreen from over 700 participants, as well as (2) summary analysis of a subset of 318 participants who range in age from 18 to 83 years old and of whom 53% reported a motor impairment. The analysis demonstrates the continuous relationship between age and input performance for users with and without motor impairments, but also illustrates that knowing a user's age and self-reported motor ability should not lead to assumptions about their input performance. The dataset, which contains mouse and touchscreen input traces, should allow for further exploration by other researchers.

References

  1. Chaparro, A., Bohan, M., Fernandez, J., Choi, S.D. and Kattel, B. 1999. The impact of age on computer input device use: Psychophysical and physiological measures. International Journal of Industrial Ergonomics. 24, (1999), 503–513.Google ScholarGoogle Scholar
  2. Czaja, S.J., Boot, W.R., Charness, N. and Rogers, W.A. 2019. Designing for older adults: Principles and creative human factors approaches. CRC press.Google ScholarGoogle Scholar
  3. Devore, J.L. 2015. Probability and Statistics for Engineering and the Sciences. Cengage Learning.Google ScholarGoogle Scholar
  4. Findlater, L., Froehlich, J.E., Fattal, K., Wobbrock, J.O. and Dastyar, T. 2013. Age-related differences in performance with touchscreens compared to traditional mouse input. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’13) (New York, New York, USA, 2013), 343–346.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Findlater, L., Moffatt, K., Froehlich, J.E., Malu, M. and Zhang, J. 2017. Comparing Touchscreen and Mouse Input Performance by People With and Without Upper Body Motor Impairments. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (2017), 6056–6061.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Findlater, L., Zhang, J., Froehlich, J.E. and Moffatt, K. 2017. Differences in Crowdsourced vs. Lab-based Mobile and Desktop Input Performance Data. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (2017), 6813–6824.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Franz, R.L., Wobbrock, J.O., Cheng, Y. and Findlater, L. 2019. Perception and Adoption of Mobile Accessibility Features by Older Adults Experiencing Ability Changes. The 21st International ACM SIGACCESS Conference on Computers and Accessibility (2019), 267–278.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Hertzum, M. and Hornbæk, K. 2010. How Age Affects Pointing With Mouse and Touchpad: A Comparison of Young, Adult, and Elderly Users. International Journal of Human-Computer Interaction. 26, 7 (Jun. 2010), 703–734. DOI:https://doi.org/10.1080/10447318.2010.487198.Google ScholarGoogle ScholarCross RefCross Ref
  9. Hourcade, J. and Berkel, T. 2008. Simple pen interaction performance of young and older adults using handheld computers. Interacting with Computers. 20, 1 (Jan. 2008), 166–183. DOI:https://doi.org/10.1016/j.intcom.2007.10.002.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Hwang, F., Hollinworth, N. and Williams, N. 2013. Effects of Target Expansion on Selection Performance in Older Computer Users. ACM Transactions on Accessible Computing (TACCESS). 5, 1 (2013). DOI:https://doi.org/10.1145/2514848.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. International Organization for Standardization 2002. Ergonomic requirements for office work with visual display terminals (VDTs)—Requirements for non-keyboard input devices.Google ScholarGoogle Scholar
  12. Keates, S. and Trewin, S. 2005. Effect of age and Parkinson's disease on cursor positioning using a mouse. Proceedings of the ACM SIGACCESS Conference on Computers and Accessibility (ASSETS’05) (New York, New York, USA, 2005), 68–75.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. 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. Journal of Gerontology. 57, 1 (Jan. 2002), 54–64.Google ScholarGoogle Scholar
  14. Li, E.K., Lee, S., Patel, S.S. and Sereno, A.B. 2018. Age-dependent Performance on Pro-point and Anti-point Tasks. Frontiers in psychology. 9, (2018), 2519.Google ScholarGoogle Scholar
  15. MacKenzie, I.S. and Isokoski, P. 2008. Fitts’ throughput and the speed-accuracy tradeoff. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’08) (New York, New York, USA, 2008), 1633–1636.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. MacKenzie, I.S., Sellen, A. and Buxton, W.A.S. 1991. A comparison of input devices in element pointing and dragging tasks. Proceedings of the SIGCHI conference on Human factors in computing systems (1991), 161–166.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Moffatt, K. and Mcgrenere, J. 2007. Slipping and Drifting: Using Older Users to Uncover Pen-based Target Acquisition Difficulties. (2007), 11–18.Google ScholarGoogle Scholar
  18. Motti, L.G., Vigouroux, N. and Gorce, P. 2013. Interaction techniques for older adults using touchscreen devices: a literature review. Proceedings of the 25th Conference on l'Interaction Homme-Machine (2013), 125–134.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Nicolau, H., Guerreiro, T., Jorge, J. and Gonçalves, D. 2014. Mobile touchscreen user interfaces: Bridging the gap between motor-impaired and able-bodied users. Universal Access in the Information Society. 13, (2014), 303–313. DOI:https://doi.org/10.1007/s10209-013-0320-5.Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Riviere, C.N. and Thakor, N. V 1996. Effects of age and disability on tracking tasks with a computer mouse: accuracy and linearity. Journal of Rehabilitation Research and Development. 33, 1 (1996), 6–15.Google ScholarGoogle Scholar
  21. Salivia, G. and Hourcade, J.P. 2013. PointAssist: assisting Iindividuals with motor impairments. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’13) (2013), 1213–1222.Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Smith, M.W., Sharit, J. and Czaja, S.J. 1999. Aging, motor control, and the performance of computer mouse tasks. Human Factors. 41, 3 (Sep. 1999), 389–396. DOI:https://doi.org/10.1518/001872099779611102.Google ScholarGoogle ScholarCross RefCross Ref
  23. Smith, M.W., Sharit, J. and Czaja, S.J. 1999. Aging, Motor Control, and the Performance of Computer Mouse Tasks. Human Factors: The Journal of the Human Factors and Ergonomics Society. 41, 3 (Sep. 1999), 389–396. DOI:https://doi.org/10.1518/001872099779611102.Google ScholarGoogle ScholarCross RefCross Ref
  24. Soukoreff, R.W. and MacKenzie, I.S. 2004. Towards a standard for pointing device evaluation, perspectives on 27 years of Fitts’ law research in HCI. International Journal of Human-Computer Studies. 61, 6 (Dec. 2004), 751–789. DOI:https://doi.org/10.1016/j.ijhcs.2004.09.001.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Sultana, A. and Moffatt, K. 2019. Effects of Aging on Small Target Selection with Touch Input. ACM Transactions on Accessible Computing (TACCESS). 12, 1 (2019), 1–35.Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Teeken, J.C., Adam, J.J., Paas, F.G.W.C., Van Boxtel, M.P.J., Houx, P.J. and Jolles, J. 1996. Effects of age and gender on discrete and reciprocal aiming movements. Psychology and aging. 11, 2 (1996), 195.Google ScholarGoogle Scholar
  27. Vines, J., Pritchard, G., Wright, P., Olivier, P. and Brittain, K. 2015. An age-old problem: Examining the discourses of ageing in HCI and strategies for future research. ACM Transactions on Computer-Human Interaction (TOCHI). 22, 1 (2015), 1–27.Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Wacharamanotham, C., Hurtmanns, J., Mertens, A., Kronenbuerger, M., Schlick, C. and Borchers, J. 2011. Evaluating Swabbing: a touchscreen input method for elderly users with tremor. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’11) (2011), 623–626.Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Walker, N., Philbin, D.A. and Fisk, A.D. 1997. Age-related differences in movement control: adjusting submovement structure to optimize performance. Journal of Gerontology. 52B, 1 (Jan. 1997), 40–52.Google ScholarGoogle Scholar
  30. Wobbrock, J.O. and Gajos, K.Z. 2008. Goal crossing with mice and trackballs for people with motor impairments: Performance, submovements, and design directions. ACM Transactions on Accessible Computing (TACCESS). 1, 1 (2008), 1–37. DOI:https://doi.org/10.1145/1361203.1361207.Google ScholarGoogle ScholarDigital LibraryDigital Library

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          • Published in

            cover image ACM Conferences
            ASSETS '20: Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility
            October 2020
            764 pages
            ISBN:9781450371032
            DOI:10.1145/3373625

            Copyright © 2020 ACM

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            Publication History

            • Published: 29 October 2020

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            • short-paper
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            Acceptance Rates

            ASSETS '20 Paper Acceptance Rate46of167submissions,28%Overall Acceptance Rate436of1,556submissions,28%

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