Automation has infiltrated nearly all areas of our lives. Many technologies have not been designed considering older adult populations. Smartphone usage is pervasive among older individuals, but whether age-related differences exist in the use of automated features of mobile devices continues to be researched. This study examined how younger, middle-aged, and older adults use AutoCorrect (AC) to send mobile messages. A total of 138 participants were asked about their perceptions of AC and to write messages in response to four scenarios that varied in complexity. Overall, younger adults had a more favorable perception of AC compared to middle-aged and older adults. Also, when complexity was both high and low, older adults were more likely to proofread their messages, manually correct AC, find AC distracting, and perceive AC to be helpful. Our findings suggest that older adults do engage with automation differently than their younger counterparts, which should be considered by automation designers.
BarnardY.BradleyM. D.HodgsonF.LloydA. D. (2013). Learning to use new technologies by older adults: Perceived difficulties, experimentation behaviour and usability. Computers in Human Behavior, 29(4), 1715–1724. https://doi.org/10.1016/j.chb.2013.02.006
3.
BehrendT. S.SharekD. J.MeadeA. W.WiebeE. N. (2011). The viability of crowdsourcing for survey research. Behavior Research Methods, 43(3), 800–813. https://doi.org/10.3758/s13428-011-0081-0
4.
Calvo-PorralC.Pesqueira-SanchezR. (2020). Generational differences in technology behaviour: comparing millennials and Generation X. Kybernetes, 49(11), 2755–2772. https://doi.org/10.1108/K-09-20190598
5.
CapraniN.DoyleJ.O’GradyM. J.GurrinC.O’ConnorN.CaufieldB.O’HareG. M. P. (2012). Technology use in everyday life: Implications for designing for older users. IHCI 2012: 6th Annual Irish Human Computer Interaction (HCI) Conference.
6.
ForstmannB. U.TittgemeyerM.WagenmakersE. J.DerrfussJ.ImperatiD.BrownS. (2011). The speed-accuracy tradeoff in the elderly brain: A structural model-based approach. Journal of Neuroscience, 31(47), 17242–17249. https://doi.org/10.1007/s00779020-01450-y
7.
GollanT. H.SmirnovD. S.SalmonD. P.GalaskoD. (2020). Failure to stop AC errors in reading aloud increases in aging especially with a positive biomarker for Alzheimer’s disease. Psychology and Aging, 35(7), 1016–1025. https://doi.org/10.1037/pag0000550
8.
HichamB.BachirB. (2020). Using writing assistive technology to improve EFL university students’ performance. Payame Noor University Quarterly of Iranian Distance Education Journal, 2(2), 55–68.
9.
JenkinsA.EslambolchilarP.LindsayS.HareM.ThorntonI. M.TalesA. (2016). Attitudes towards attention and aging: What differences between younger and older adults tell us about mobile technology design. International Journal of Mobile Human Computer Interaction, 8(2), 47–68. https://doi.org/10.4018/IJMHCI.2016040103
10.
MastrototaroJ. (1999). The MiniMed continuous glucose monitoring system (CGMS). Journal of Pediatric Endocrinology and Metabolism, 12(SUPPL. 3), 751–758. https://doi.org/10.1089/15209150050214078
11.
MitznerT. L.BoronJ. B.FaussetC. B.AdamsA. E.CharnessN.CzajaS. J.DijkstraK.FiskA. D.RogersW. A.SharitJ. (2010). Older adults talk technology: Technology usage and attitudes. Computers in Human Behavior, 26(6), 1710–1721. https://doi.org/10.1016/j.chb.2010.06.020
NoblesS.PaganucciL. (2015). Do digital writing tools deliver? Student perceptions of writing quality using digital tools and online writing environments. Computers and Composition, 38, 16–31. https://doi.org/10.1016/j.compcom.2015.09.001
14.
ParasuramanR.SheridanT. B.WickensC. D. (2000). A model for types and levels of human interaction with automation. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 30(3), 286–297. https://doi.org/10.1109/3468.844354
15.
PradhanA.LazarA.FindlaterL. (2020). Use of intelligent voice assistants by older adults with low technology use. ACM Transactions on Computer-Human Interaction, 27(4). https://doi.org/10.1145/3373759
16.
RahimiM.ShahryaniA. (2019). The role of AC software use in learning English as a foreign language. Technology of Education Journal, 13(3), 511–520.
17.
RobinsonP. (2007). Task complexity, theory of mind, and intentional reasoning: Effects on L2 speech production, interaction, uptake and perceptions of task difficulty. IRAL - International Review of Applied Linguistics in Language Teaching, 45(3), 193–213. https://doi.org/10.1515/iral.2007.009
18.
ShankD. B. (2016). Using crowdsourcing websites for sociological research: The case of amazon mechanical turk. American Sociologist, 47(1), 47–55. https://doi.org/10.1007/s12108-015-9266-9
United Nations Department of Economic and Social Affairs, Population Division (2020). World Population Ageing 2020 Highlights: Living arrangements of older persons (ST/ESA/SER.A/451).
21.
WoodN. (2014). AC awareness: Categorizing AC changes and measuring authorial perceptions.
22.
YuanS.HussainS. A.HalesK. D.CottenS. R. (2016). What do they like? Communication preferences and patterns of older adults in the United States: The role of technology. Educational Gerontology, 42(3), 163–174. https://doi.org/10.1080/03601277.2015.1083392
