Abstract
These days a growing number of adults are using smartphones to fill out online forms or surveys (For a review of recent empirical studies on older adults using smartphone when answering forms see: [2,3,4]). The touchscreen keyboard that pops open on a smartphone when users must type their answers into the form can be challenging to use. This is due to its small size and the fact that for some smartphones, the initial keyboard that opens has only characters, not numbers. If the form requires a number to be entered, a user must press a small button, located in the far-left corner to change the keyboard so that it displays numbers. Using the small touchscreen is challenging for older adults, whose fine motor skills may have deteriorated with age (Loos and Romano Bergstrom [12]). Survey and form designers face the challenge of creating an interface that is both convenient to use while also leading to accurate data entry. More recently, some survey designers have been using a numeric keypad design on mobile phones when the expected entry is a number. This is based on the idea that the numeric keypad, with its bigger touch areas offering only numbers, would lead to an improved user experience. This paper reports the results of an experiment with older adults, comparing performance when using a numeric keypad to that when using a touchscreen character keyboard for number entries on a smartphone. When entering a number, results indicate that the numeric keypad design did not lead to more accurate data entry over the character keyboard design. While overall efficiency was also no different between the two designs, there was some evidence that the keypad design takes users less time to initially enter the number. While participants across both conditions were equally satisfied with their experience completing the survey, they overwhelmingly preferred to use the numeric keypad to enter numbers. For designers creating interfaces for smartphones, the recommendation is to use a numeric keypad for input fields that require a number as the answer.
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References
U.S. Census Bureau: Unofficial preliminary para data analysis 2020 Census. Internal email. 4 Nov 2020
Olmsted-Hawala, E., Nichols, E., Falcone, B., Figueroa, I.J., Antoun, C., Wang, L.: Optimal data entry designs in mobile web surveys for older adults. In: Zhou, J., Salvendy, G. (eds.) ITAP 2018. LNCS, vol. 10926, pp. 335–354. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-92034-4_26
Nichols, E., Olmsted-Hawala, E., Wang, L.: optimal designs of text input fields in mobile web surveys for older adults. In: Zhou, J., Salvendy, G. (eds.) HCII 2019, Lecture Notes in Computer Science, vol. 11592, pp. 463–481 (2019). https://doi.org/10.1007/978-3-030-22012-9_34
Nichols, E., Olmsted-Hawala, E., Raim, A., Wang, L.: Attitudinal and behavioral differences between older and younger adults using mobile devices. In: Gao, Q., Zhou, J. (eds.) HCII 2020. LNCS, vol. 12207, pp. 325–337. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-50252-2_25
Pew Research Center. Mobile Fact Sheet.https://pewresearch-org-preprod.go-vip.co/internet/fact-sheet/mobile/. For more on age breaks down and smartphones. https://pewresearch-org-preprod.go-vip.co/fact-tank/2019/09/09/us-generations-technology-use/
Kakulla, B.N.: Older Adults Keep Pace on Tech Usage: 2020 Tech Trends of the 50 + . American Association of Retired Persons (AARP) Research (2020). https://www.aarp.org/research/topics/technology/info-2019/2020-technology-trends-older-americans.html
Fernández-Ardèvol, M., et al.: Methodological strategies to understand smartphone practices for social connectedness in later life. In: Zhou, J., Salvendy, G. (eds.) HCII 2019. LNCS, vol. 11593, pp. 46–64. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22015-0_4
Antoun, C., Couper, M., Conrad, F.: Effects of mobile versus pc web on survey response quality: a crossover experiment in a probability web panel. Public Opin. Q. 81(S1), 280–306 (2017). https://doi.org/10.1093/poq/nfw088
Couper, M., Peterson, G.: Why do web surveys take longer on smartphones? Soc. Sci. Comput. Rev. 35(3), 357–377 (2015). https://doi.org/10.1177/0894439316629932
Mavletova, A., Couper, M.P.: A meta-analysis of breakoff rates in mobile web surveys. In: Toninelli, E., Pinter, R., de Pedraza, P. (eds.) Mobile Research Methods: Opportunities and Challenges of Mobile Research Methodologies, pp. 81–98. Ubiquity Press, London (2015)
Nichols, E., Olmsted-Hawala, E., Horwitz, R., and Bentley, M.: Optimizing the decennial census for mobile: a case study. Federal Committee on Statistical Methodology (FCSM) (2015) https://nces.ed.gov/fcsm/pdf/I2_Nichols_2015FCSM.pdf
Loos, E.F., Romano Bergstrom, J.: Older adults. In: Romano Bergstrom, J., Schall, A.J. (eds.) Eye Tracking in User Experience Design. pp. 313–329. Elsevier, Amsterdam (2014)
Seidler, R.D., et al.: Motor control and aging: links to age-related brain structural, functional, and biochemical effects. Neurosci. Biobehav. Rev. 34(5), 721–733 (2010). https://doi.org/10.1016/j.neubiorev.2009.10.005
Voelcker-Rehage, C.: Motor-skill learning in older adults—a review of studies on age-related differences. Eur. Rev. Aging Phys. Act. 5, 5–16 (2008)
Hoogendam, Y.Y., et al.: Older age relates to worsening of fine motor skills: a population-based study of middle-aged and elderly persons. Front. Aging Neurosci. 6, 259 (2014)
Kim, S., Son, J., Lee, G., Kim, H., Lee, W.: TapBoard: making a touch screen keyboard more touchable. Conference on Human Factors in Computing Systems - Proceedings. pp. 553–562 (2013)
Schryer, E., Ross, M.: Does the age-related positivity effect in autobiographical recall reflects differences in appraisal or memory? J. Gerontol.: Seri. B 69(4), 548–556 (2014)
Ketcham, C.J., Stelmach, G.E.: Age-related declines in motor control. Handbook of the Psychology of Aging. 5th edn. pp. 313–348. Academic Press, San Diego (2001)
Ketcham, C.J., Stelmach, G.E.: Movement control in the older adult. In: Pew, R.W., Van Hemel, S.B. (eds.) Technology for Adaptive Aging. National Academies Press, Washington, DC (2004)
Ketcham, C.J., Seidler, R.D., Van Gemmert, A.W., Stelmach, G.E.: Age-related kinematic differences as influenced by task difficulty, target size, and movement amplitude. J. Gerontol. B Psychol. Sci. Soc. Sci. 57(1), 54–64 (2002)
Acknowledgements
The study was supported by the U.S. Census Bureau’s Innovation and Operational Efficiency Program. We thank Russell Sanders, Christopher Antoun, Brian Falcone, Ivonne Figueroa, Alda Rivas, Joanna Lineback, Sabin Lakhe, Kevin Younes, and the MetroStar team. We also thank Eugene Loos, Shelley Feuer and Joanne Pascale for their reviews of an earlier draft of this paper.
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Olmsted-Hawala, E., Nichols, E., Wang, L. (2021). Numeric Keypads or Character Keyboards for Numeric Entries on Surveys and Forms: Surprising Results from Older Adults Using Mobile Devices. In: Gao, Q., Zhou, J. (eds) Human Aspects of IT for the Aged Population. Technology Design and Acceptance. HCII 2021. Lecture Notes in Computer Science(), vol 12786. Springer, Cham. https://doi.org/10.1007/978-3-030-78108-8_16
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