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Understanding age and technology experience differences in use of prior knowledge for everyday technology interactions

Published: 30 March 2012 Publication History

Abstract

Technology designers must understand relevant prior knowledge in a target user population to facilitate adoption and effective use. To assess prior knowledge used in naturalistic settings, we systematically collected information about technologies used over 10-day periods from older adults with high and low technology experience and younger adults. Technology repertoires for younger adults and high technology older adults were similar; differences reflected typically different needs for kitchen and health care technologies between the age groups. Technology repertoires for low-technology older adults showed substantial technology usage in many categories. Lower usage compared to high-tech older adults for each category was limited primarily to PC and Internet technologies. Experience differences suggest preferences among low-technology older adults for basic technology usage and for working with people rather than technologies.
Participants in all groups were generally successful using their everyday technologies to achieve their goals. Prior knowledge was the most common attribution for success, but external information was also commonly referenced. Relevant prior knowledge included technical, functional, strategy, and self knowledge. High tech older adults did not report more problems than younger adults, but they did attribute more problems to insufficient prior knowledge. Younger adults attributed more problems to interference from prior knowledge. Low-tech older adults reported fewer problems, typically attributing them to insufficient prior knowledge or product/system faults. We discuss implications for further research and design improvements to increase everyday technology success and adoption for high-tech and low-tech older adults.

References

[1]
Ackerman, P. L. and Rolfhus, E. L. 1999. The locus of adult intelligence: Knowledge, abilities, and nonability traits. Psych. Aging 14, 314--330.
[2]
Beier, M. E. and Ackerman, P. L. 2005. Age, ability, and the role of prior knowledge on the acquisition of new domain knowledge: Promising results in a real-world learning environment. Psych. Aging, 20, 341--355.
[3]
Blackler, A. 2006. Intuitive interaction with complex artifacts. Doctoral dissertation, Queensland University of Technology, Brisbane, Australia.
[4]
Blackler, A., Popovic, V., and Mahar, D. 2003. The nature of intuitive use of products: An experimental approach. Des. Stud. 24, 491--506.
[5]
Blackler, A., Popovic, V., and Mahar, D. P. 2010. Investigating users' intuitive interaction with complex artefacts. Appl. Ergon. 41, 72--92.
[6]
Carroll, J. M. and Mack, R. L. 1984. Learning to use a word processor: By doing, by thinking, and by knowing. In Human Factors in Computer Systems, J. C. Thomas and M. L. Schneider, Eds., Ablex Publishing Corp., Norwood, NJ, 13--51.
[7]
Czaja, S. J., Charness, N., Dijkstra, K., Fisk, A. D., Rogers, W. A., and Sharit, J. 2006b. Center for research and education on aging and technology enhancement: Computer and technology experience questionnaire (CREATE-TR-2006-03). University of Miami.
[8]
Czaja, S. J., Charness, N., Fisk, A. D., Hertzog, C., Nair, S. N., Rogers, W. A., and Sharit, J. 2006a. Factors predicting the use of technology: Findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psych. Aging 21, 333--352.
[9]
Djajadiningrat, T., Wensveen, S., Frens, J., and Overbeeke, C. 2004. Tangible products: Redressing the balance between appearance and action, Pers. Ubiq. Comput. 8, 294--309.
[10]
Docampo Rama, M. 2001. Technology generations: Handling complex user interfaces. Doctoral dissertation, Technical University of Eindhoven, The Netherlands.
[11]
Freudenthal, A. and Mook, H. J. 2003. The evaluation of an innovative intelligent thermostat interface: Universal usability and age differences. Cogn. Techn. Work 5, 55--66.
[12]
Freudenthal, T. D. 2001. The role of age, foreknowledge and complexity in learning to operate a complex device. Behav. Inf. Techn. 20, 23--35.
[13]
Fu, W.-T. and Gray, W. D. 2004. Resolving the paradox of the active user: Stable suboptimal performance in interactive tasks. Cogn. Sci. Multidisc. J. 28, 901--935.
[14]
Goodman, J., Syme, A., and Eisma, R. 2003. Older adults' use of computers. In Proceedings of the British Computer Society Conference on Human-Computer Interaction.
[15]
Gorard, S. and Selwyn, N. 2008. The myth of the silver surfer. Adults Learn. 19, 5, 28--30.
[16]
Gray, W. D. and Fu, W.-T. 2004. Soft constraints in interactive behavior: The case of ignoring perfect knowledge in-the-world for imperfect knowledge in-the-head. Cogn. Sci. 28, 359--382.
[17]
Healy, M. R., Light, L. L., and Chung, C. 2005. Dual-process models of associative recognition in young and older adults: Evidence from receiver operating characteristics. J. Exp. Psych. Learn. Mem. Cogn. 31, 768--788.
[18]
Hertzog, C., Lineweaver, T. T., and McGuire, C. L. 1999. Beliefs about memory and aging. In Social Cognition and Aging, T. M. Hess and F. Blanchard-Fields, Eds., Academic Press, San Diego, CA. 43--68.
[19]
Horrigan, J. 2007. A typology of information and communication technology users. http://www.pewinternet.org/~/media/Files/Reports/2007/PIP_ICT_Typology.pdf.
[20]
Hurtienne, J. and Langdon, P. 2009. Prior knowledge in inclusive design: The older, the more intuitive? In Proceedings of the 23rd British Computer Society Human Computer Interaction Workshop and Conference (HCI'09).
[21]
Hurtienne, J., Horn, A.-M., and Langdon, P. M. 2010. Facets of prior experience and their impact on product usability for older users. In Designing Inclusive Interactions, P. M. Langdon, P. J. Clarkson, and P. Robinson, Eds., Springer, 123--132.
[22]
ISO. 2006. Ease of operation of everyday products -- Part 1: Design requirements for context of use and user characteristics. ISO Standard 20282-1:2006(E).
[23]
Jacelon, C. S. and Imperio, K. 2005. Participant diaries as a source of data in research with older adults. Qual. Health Res. 15, 991--997.
[24]
Kang, N. E. and Yoon, W. C. 2008. Age- and experience-related user behavior differences in the use of complicated electronic devices. Int. J. Hum.-Comput. Stud. 66, 425--437.
[25]
Langdon, P., Lewis, T., and Clarkson, J. 2007. The effects of prior experience on the use of consumer products. Univ. Access. Inf. Soc. 6, 179--191.
[26]
Lawry, S., Popovic, V., and Blackler, A. 2010. Identifying familiarity in older and younger adults. In Proceedings of the Design Research Society International Conference.
[27]
Leonardi, C., Mennecozzi, C., Not, E., Pianesi, F., and Zancanaro, M. 2008. Designing a familiar technology for elderly people, by the NETCARITY (IST2005-045508) European project. http://i3.fbk.eu/en/system/files/Leonardi_Designing+Familiar+technology.pdf.
[28]
Leung, R., McGrenere, J., and Graf, P. 2011. Age-related differences in the initial usability of mobile device icons. Behav. Inf. Techn. 30, 629--642.
[29]
Lindenberger, U., Kleigl, R., and Baltes, P. B. 1992. Professional expertise does not eliminate age differences in imagery-based memory performance during adulthood. Psych. Aging 7, 585--593.
[30]
McGill, T., Wyer, P. C., Newman, T. B., Keitz, S., Leipzig, R., and Guyatt, G. 2004. Tips for learners of evidence-based medicine: 3. Measures of observer variability (kappa statistic). Can. Med. Assoc. J. 171, 1369--1373.
[31]
Melenhorst, A.-S., Rogers, W. A., and Bouwhuis, D.G. 2006. Older adults' motivated choice for technological innovation: Evidence for benefit-driven selectivity. Psych. Aging 21, 190--195.
[32]
Micro Audiometrics 2008. Earscan audiometer. [email protected].
[33]
Mitzner, T. L., Fausset, C. B., Boron, J. B., Adams, A. E., Dijkstra, K., Lee, C. C., and Fisk, A. D. 2008. Older adults' training preferences for learning to use technology. In Proceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting. HFES, Santa Monica, CA, 2047--2051.
[34]
Monk, A., Blythe, M., and Kim, H. 2010. What do people want from the technology in their homes: Work at the Centre for Usable Home Technology (CUHTec). In Proceedings of the 32nd International Conference on Information Technology Interfaces. 313--318.
[35]
Mykityshyn, A. L., Fisk, A. D., and Rogers, W. A. 2002. Learning to use a home medical device: Mediating age-related differences with training. Human Factors 44, 354--364.
[36]
Neo Insight. 2007. Day in the Life. www.neoinsight.com.
[37]
Newell, A. F. 2008. Accessible computing -- Past trends and future suggestions. ACM Trans. Access Comput. 1, 2, Article 9, 1--7.
[38]
Nielsen, J. 2010. College students on the web: User experience guidelines. http://www.useit.com/alertbox/students.html.
[39]
Norman, D. A. 2002. The design of everyday things. Basic Books, New York.
[40]
O'Brien, M. A. 2010. Understanding human-technology interactions: The role of prior experience and age. Doctoral dissertation, Georgia Institute of Technology, Atlanta, GA.
[41]
O'Brien, M. A. and Rogers, W. A. Design for aging: Enhancing everyday technology use. In Engaging Older Adults with Modern Technology: Internet Use and Information Access Needs, R. Z. Zheng, R. D. Hill, and M. K. Gardner, Eds., IGI Publishing, Hershey, PA, To appear.
[42]
O'Brien, M. A., Rogers, W. A., and Fisk, A. D. 2009a. Discerning prior knowledge use by older adults in human technology interactions. The Southern Gerontological Society Annual Meeting.
[43]
O'Brien, M. A., Rogers, W. A., and Fisk, A. D. 2009b. The role of prior experience in everyday technology interactions. The 62nd Annual Scientific Meeting of the Gerontological Society of America.
[44]
O'Hara, K. P. and Payne, S. J. 1998. The effects of operator implementation cost on planfulness of problem solving and learning. Cogn. Psych. 35, 34--70.
[45]
Olson, K. E., O'Brien, M. A., Rogers, W. A., and Fisk, A. D. 2011. Diffusion of technology for younger and older adults. Ageing Int. 36, 1, 123--145.
[46]
Oulasvirta, A., Wahlström, M., and Ericsson, K. A. 2011. What does it mean to be good at using a mobile device? An investigation of three levels of experience and skill. Int. J. Hum.-Comput. Stud. 69, 3, 155--169.
[47]
Ownby, R, Czaja S. J., Loewenstein, D., and Rubert, M. 2008. Cognitive abilities that predict success in a computer-based training program. Gerontol. 48, 170--180.
[48]
Polson, P.G. and Lewis, C.H. 1990. Theory-based design for easily learned interfaces. Hum.-Comput. Interact. 5, 191--220.
[49]
Preacher, K. J. 2001. Calculation for the chi-square test: An interactive calculation tool for chi-square tests of goodness of fit and independence. http://quantpsy.org.
[50]
Reason, J. T. 1990. Human Error. Cambridge University Press, Cambridge, U.K.
[51]
Rieman, J. 1996. A field study of exploratory learning strategies. ACM Trans. Comput.-Hum. Interact. 3, 189--218.
[52]
Rogers, W. A., O'Brien, M. A., and Fisk, A. D. In Press. Cognitive engineering to support successful aging. In Oxford Handbook of Cognitive Engineering, J. D. Lee and A. Kirlik, Eds., Oxford University Press, Oxford, UK.
[53]
Seale, C. 1999. The Quality of Qualitative Research. SAGE Publications, London.
[54]
Selwyn, N. 2004. The information aged: A qualitative study of older adults' use of information and communications technology. J. Aging Stud. 18, 369--384.
[55]
Serrano Baquero, D., and Rogers, W. A. 2010. Knowledge and intuitive interaction design: Developing a knowledge taxonomy. Tech. rep. HFA-TR-1004, Georgia Tech, gatech.edu/hfa.
[56]
Sharit, J., Hernandez, M. A., Czaja, S. J., and Pirolli, P. 2008. Investigating the roles of knowledge and cognitive abilities in older adult information seeking on the web. ACM Trans. Comput.-Hum. Interact. 15, 1, 3, 25.
[57]
Sharp, K. 1998. The case for case studies in nursing research: The problem of generalization. J. Adv. Nursing, 27, 785--790.
[58]
Shipley, W. C. 1940. A self-administering scale for measuring intellectual impairment and deterioration. J. Psych. Interdisc. Appl. 9, 371--377.
[59]
Singley, M. K. and Anderson, J.R. 1987. A keystroke analysis of learning and transfer in text editing. Hum.-Comput. Interact. 3, 223.
[60]
Vance, A. 2010. With Kinect, Microsoft aims for game changer. The New York Times.
[61]
Verbi Software. 2007. MAXQDA. [email protected].
[62]
Wechsler, D. 1997. Wechsler Memory Scale III. (3rd ed.). The Psychological Corporation, San Antonio, TX.
[63]
Yonelinas, A. P. 2002. The nature of recollection and familiarity: A review of 30 years of research. J. Mem. Lang. 46, 441--517.
[64]
Zacks, R. T., Hasher, L., and Li, K. Z. H. 2000. Human memory. In The Handbook of Aging and Cognition (2nd Ed.), F. I. M. Craik and T. A. Salthouse, Eds., Lawrence Erlbaum Associates Mahwah, NJ. 293--357.
[65]
Zickuhr, K. 2011. Generations and their gadgets. Pew Internet & American Life Project. http://www. pewinternet.org/Reports/2011/Generations-and-gadgets.aspx.

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cover image ACM Transactions on Accessible Computing
ACM Transactions on Accessible Computing  Volume 4, Issue 2
March 2012
62 pages
ISSN:1936-7228
EISSN:1936-7236
DOI:10.1145/2141943
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 30 March 2012
Accepted: 01 January 2012
Revised: 01 August 2011
Received: 01 March 2011
Published in TACCESS Volume 4, Issue 2

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Author Tags

  1. Prior knowledge
  2. aging
  3. older adults
  4. prior experience
  5. technology experience
  6. troubleshooting

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